NEW: Outstanding Reviewer 2025 awards from RSC's PCCP and IOP's Mach. Learn. Sci. Technol.
NEW: Outstanding Reviewer 2025 awards from RSC's PCCP and IOP's Mach. Learn. Sci. Technol.
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Sergei Manzhos
Associate Professor
School of Materials and Chemical Technology
Institute of Science Tokyo
Ookayama 2-12-1, Meguro-ku, Tokyo 152-8552 Japan
Web : https://sites.google.com/site/sergeimanzhos/
https://orcid.org/0000-0001-8172-7903
http://scholar.google.com.sg/citations?user=Kj3DwhUAAAAJ
ResearcherID:B-1304-2009
University education (click here for a list of university courses taken)
Publications (click here to see the list of publications on a separate page with links to full text. Click here to read about and obtain the codes of neural network programs)
Conference presentations (click here to see the list of talks on a separate page with links to full text)
Learned society & editorial board memberships, service to the academic community, languages
1. CURRENT POSITION AND RESEARCH PROJECTS
1. CURRENT POSITION AND RESEARCH PROJECTS
Associate Professor,
School of Materials and Chemical Technology
Institute of Science Tokyo (formely Tokyo Institute of Technology)
Research program:
● Computational modeling of materials and interfaces for sustainable energy generation and storage
○ Solar cells and LED with a focus on charge transport materials
○ Solid state ionics for solid state ionic conductors with applications focusing on fuel cells and batteries
○ Molecule-surface interactions
● Machine learning
○ Use of machine learning techniques for modeling of matter, including modeling of interatomic interactions and improvement of ab initio methods
○ Use of machine learning for systems-level modeling including integrated renewable energy systems
○ Machine learning method development
● Large scale ab initio materials simulations based on orbital-free density functional theory and density functional tight binding, including method development in these
● Quantum dynamics including method development to compute anharmonic vibrational spectra and multivariate potential energy surfaces
2. UNIVERSITY EDUCATION
2. UNIVERSITY EDUCATION
Ph.D. – Queen’s University, 2005
M.Sc. – Kharkiv National University, 1999
Details:
May 2000 – December 2004
Graduate Student in Chemistry Dept., Queen’s University, Kingston, ON, Canada, K7L 3N6. Research group of
Prof. Hans-Peter Loock,
(613) 533 2621
Ph.D. thesis “Excited state characterisation of hydrogen halides using velocity map imaging”
September 1994 – July 1999
Department of Radio Physics, Kharkov State University, 4, Svobody Sq., Kharkov, 61001, Ukraine
Master’s Diploma with Honours in Radio Physics and Electronics; satellite diploma (a “minor”) in Teaching.
Thesis “Chaotic synchronization of modified Roessler oscillators for secure communications”
3. AREAS OF EXPERTISE
3. AREAS OF EXPERTISE
RESEARCH (numbers refer to publications in the publications list below)
Modeling of materials for and processes in electrochemical batteries and related phenomena (41, 43, 47, 48-50, 53, 55, 56, 58, 61, 62, 65, 66, 68, 71, 73, 77-80, 85, 86, 88, 92-94, 100, 104, 106, 108, 110, 111, 113, 114, 120, 121, 123, 126, 127, 132, 133, 139, 141, 151, 152, 157, 164, 170, 176, 177, 184, 186, 188, 189, 191, 206, 209, 224, 240, 249, 255)
Modeling of materials for and processes in advanced solar cells and LED (23, 25, 30-35, 37-38, 40, 42, 44-46, 49, 52, 57, 64, 75, 76, 84, 90, 98, 109, 111, 115, 118, 119, 123, 128, 135, 136, 140, 143-145, 147, 153-156, 160-162, 168, 169, 171, 174, 179, 182, 184, 193, 195, 196, 199-202, 204, 205, 214, 217, 229, 232, 233, 238, 239, 245, 246, 250, 260, 270)
Machine learning and materials informatics (Neural Networks, Genetic Algorithms, Gaussian Processes etc), multidimensional data analysis and approximation / interpolation / feature extraction (4, 6, 8, 10, 12-22, 28, 67, 74, 102, 130, 150, 172, 180, 190, 192, 194, 198, 208, 210, 211, 212, 215, 221, 222, 225, 226, 231, 234-237, 241, 243, 244, 246, 247, 251, 252, 256, 257, 259, 263-265, 267-269, 271)
Molecular potential energy surface reconstruction (5-7, 12, 14-16, 19-22, 28, 67, 74, 102, 130, 192, 194, 212, 241)
Computational vibrational spectroscopy (17, 18, 24, 26, 27, 29, 36, 39, 44, 52, 74, 81, 101, 102, 130, 149, 158, 192, 208, 212, 218, 227, 230, 231, 241)
Ab initio methods, molecular dynamics (19-21, 28, 29, 30, 32, 33, 35, 37-38, 40, 42, 45, 46, 83, 84, 91, 95, 97, 111, 123, 148, 150, 172, 219, 242)
Large-scale ab initio and multi-scale modeling (72, 95, 107, 103, 132, 150, 185, 198, 233, 242, 244, 245, 254, 255, 265, 266, 270, 271)
Modeling of interfaces and 2D materials, including molecule-surface interactions and state-of-the art methods for computational vibrational spectroscopy (19, 20, 24, 28, 31, 32, 37, 39, 40, 44, 45, 47, 50, 52, 55, 61, 63, 69, 73, 76, 77, 84, 95, 98, 163, 207, 218)
Modeling of materials for organic and inorganic electronics and related phenomena (54, 59, 87, 99, 103, 105, 112, 116, 117, 124, 131, 134, 137, 138, 142, 159, 165, 166, 173, 181, 183, 187, 196, 197, 203, 213, 220, 223, 248, 250, 253, 258, 261)
Modeling of bio-materials (89, 95, 122, 125)
Modeling of nuclear materials and related phenomena (63, 69, 81, 175, 268)
Modeling of polymers (70, 82, 83, 96, 107)
Non-adiabatic processes, electron-phonon coupling (23, 25, 31, 34)
Photodissociation dynamics (5-7, 11)
Molecular algebra (11)
Energy economics (51, 228, 262)
Modelling of (chaotic) dynamical systems, their use for secure communications (1, 9)
Modeling of nonlinear processes in electrodynamics (2, 3)
EDUCATION & HQP TRAINING
A “minor” diploma in teaching from Kharkiv National University (1999).
Queen’s University Faculty of Arts and Science Curriculum Committee Member in 2003-2004.
Teaching Assistant at Chemistry Dept., Queen’s Univ. in 2000-2004 teaching physical chemistry and spectroscopy , laboratories and tutorials, (2nd and 3rd year) as well as laboratories in general chemistry (1st year).
In 2004, received “Din Lal TA Award in Chemistry for Excellence in Teaching” based, in particular, on student evaluations.
In 2009-2010, taught a quantum chemistry course as well as tutorials for a graduate course in computational chemistry at the Dept. of Chemical System Engineering at the University of Tokyo.
Supervision of 4th year graduation projects at the Dept. of Chemical System Engineering at the University of Tokyo in 2008 - 2010.
Supervision of visiting graduate students’ projects at the Dept. of Chemical System Engineering at the University of Tokyo in 2009 - 2012.
Supervision of graduate and postdoctoral projects at the Dept. of Mechanical Engineering at the National University of Singapore in 2012-2019.
Supervision of graduate projects at the School of Materials and Chemical Technology, Tokyo Institute of Technology, since 2021.
Past courses: ME5516 (Emerging Energy Conversion and Storage Technologies), ME4256 (Functional Materials and Devices), ME6508 (Atomistic Simulations of Materials), ME4251 (Thermal Engineering of Materials)
Current courses: XCO.T487 基盤データサイエンス / Fundamentals of Data Science, XCO.T677 基盤データサイエンス発展 / Fundamentals of Progressive Data Science, ENI.I401 エネルギービッグデータ科学演習 / Big Data in Energy: a practical introduction, ENR.B431 燃料電池・太陽電池・蓄電電池・エネルギーシステムの最新技術 / Recent technologies of fuel cells, solar cells butteries and energy system
PROGRAMMING AND OTHER COMPUTER SKILLS
Electronic structure packages (DFT and orbital-free DFT) Gaussian, GaussView, SIESTA, VASP, CPMD, DFTB+, Quantum Espresso, Castep, FHI-AIMS, PROFESS.
Molecular dynamics packages VMD, NAMD, GULP, LAMMPS
Delphi, Visual Basic, MatLab, Maple, Fortran, NI Component Works, SDL Suite, IPL for scientific and engineering purposes since 1999, including image analysis, pattern recognition, and function approximation software distributed in the scientific community (4, 10, 19).
Experience with Open CV, Clipper, and Prolog languages.
Good knowledge of office and data analysis tools such as Excel, Origin, Word, TeX, etc.
EXPERIENCE WITH EQUIPMENT
Dye, Excimer, and Nd:YAG lasers (visible / UV)
Time-of-flight mass spectrometers
Molecular beam valves, ion optics
Turbo, Diffusion, and Rotary pumps
High-voltage power-supplies / pulsers / delay generators
4. PREVIOUS POSTS
4. PREVIOUS POSTS
May 2019 - Mach 2021
Associate Professor
Centre Énergie Matériaux Télécommunications
Institut National de la Recherche Scientifique
June 2012 – April 2019
Assistant Professor (group leader)
Department of Mechanical Engineering, National University of Singapore
Block EA #07-08, 9 Engineering Drive 1, Singapore 117576
Major research themes:
Computational modeling and design of materials for metal ion batteries (focus on post-lithium and organic) and solar cells and LED (focus on organic charge transport layers). Method development for computational spectroscopy and orbital-free DFT.
April 2008 - May 2012
Project Assistant Professor,
Department of Chemical System Engineering, Laboratory of Computational Molecular Engineering of Prof. Koichi Yamashita, and Research Center for Advanced Science and Technology (RCAST), laboratory of Prof. Hiroshi Segawa, The University of Tokyo, 4-6-1, Komaba, Meguro-ku, Tokyo 153-8904, Japan
Major research themes:
Theoretical modeling of processes in photoelectrochemical solar cells, specifically focusing on non-adiabatic processes leading to reduced efficiency
Theoretical modeling of reactions at surfaces using continuous potential energy surfaces (PES) of high dimensionality as wells as direct dynamics. Development of algorithms to build PESs for molecular and reactive systems from sparse ab initio data using neural networks and dimensionality reduction techniques.
Development of alternative eigensolvers to compute vibrational energy levels from extremely small basis sets. Application to vibrational spectroscopy of molecule-surface/particle complexes.
January 2005 - March 2008
Postdoctoral fellow
Research group of Prof. Tucker Carrington, Jr., Chemistry Dept., Université de Montréal, Montréal, QC, Canada H3C 3J7; now at Dept. of chemistry, Queen’s University, Kingston, ON, Canada, K7L 3N6
Project
Using Neural Networks and High-dimensional Model Representations to develop novel techniques for fitting and reconstruction of molecular potential energy surfaces of high dimensionality.
Developing alternative eigensolvers by combining methods of linear algebra and representations with lower-dimensional functions.
May 2000 – December 2004
Graduate Student (M.Sc. student May 2000-December 2001, Ph.D. student January 2002-December 2004)
Research Group of Prof. H.-P. Loock, Chemistry Dept., Queen’s University, Kingston, ON, Canada, K7L 3N6
Ph.D. thesis “Excited state characterisation of hydrogen halides using velocity map imaging”
Main Areas of Study:
Photodissociation dynamics, reconstruction of potential energy surfaces, vector correlations, photofragment image processing and analysis, pattern recognition, feature extraction.
Techniques:
Photofragment ion imaging and image processing, time-of-flight spectrometry, molecular and pulsed laser techniques, computer simulation, quantum and semi-classical analysis.
September 1998 - May 2000
Electronics Engineer
Research Group of Prof. D. M. Vavriv, Dept. of Microwave Electronics, Institute Of Radio Astronomy of National Academy of Sciences of Ukraine, 4, Chervonopraporna St., 61002, Kharkov, Ukraine.
Main Areas of Study:
Chaotic synchronization and its applications to secure communications.
Non-linear theory of microwave electronic devices, space charge effects.
Techniques:
theoretic exploration and computer simulation of chaotic dynamical systems; theory and modeling of electronic devices.
5. PUBLICATIONS
5. PUBLICATIONS
(corresponding author(s) marked with *)
Editorials
5. S. Manzhos*, J. Sa*, V. Barone*: PhysChem 2 years on: status and plans, PhysChem, 4, 1-2 (2024)
4. J. Sá*, S. Manzhos*, V. Barone*: Welcome to Physchem: status and prospects, PhysChem, 2, 16-17 (2022)
3. V. Barone*, S. Manzhos*, J. Sá*: PhysChem: A new physical chemistry journal, PhysChem, 1, 1-3 (2021)
2. S. Manzhos*: Special Issue “Molecular Engineering for Electrochemical Power Sources”, Molecules, 21(11), 1524 (2016).
1. S. Manzhos*, S. Schmauder, A. Koh, L. H. Poh, S. Joshi, V. Tan: Preface to the IWCMM23 special issue, Comp. Mater. Sci. 94, 1 (2014)
Research articles, reviews, and book chapters
271. M. Chen, M. Pavanello, W. Mi, M. Ihara, S. Manzhos*: Machine learning-enhanced Orbital-Free Density Functional Theory, J. Chem. Theory Comput., accepted, invited perspective review
270. T. Li. R. Li, K. Kameda, M. Ihara, S. Manzhos*: A study of applicability of density functional tight binding – molecular mechanics approach for the calculation of optical properties, J. Comput. Chem., 47, e70335 (2026)
269. S. Manzhos*, M. Ihara: Gaussian Process Regression – Neural Network hybrid with optimized redundant coordinates: a new simple yet potent tool for scientist’s machine learning toolbox, Advanced Intelligent Discovery, accepted
268. H. X. Liu, S. Manzhos, X. H. Wu*: Nuclear mass predictions using a neural network with additive Gaussian process regression-optimized activation functions, Phys. Rev. C, 113, 014305 (2026)
267. Y. Thant, M. Nukunudompanich*, M. Ihara, C.-C. Chueh*, S. Manzhos*: Neural networks for dedicated neurocomputing circuits: a computational study of tolerance to noise and activation function non-uniformity, Artif. Intel. Chem., 3, 100099 (2025)
266. T. Okamoto, K. Kameda, H. Wang, M. Ihara, S. Manzhos*: Comparison of Voronoi tessellation-derived and molecular dynamics-derived atomistic models of polycrystalline titania: a computational study of structures, band structures, and mechanical properties, Adv. Theory Simul., 9, e01245 (2026)
265. S. Manzhos*, J. Luder, P. Golub, M. Ihara: Machine learning-guided construction of an analytic kinetic energy functional for orbital free density functional theory, Mach. Learn. Sci. Technol., 6, 035002 (2025), invited article
264. J. Gao, Z. Gao, X. Fan, S. Manzhos*, T. Zhang*, Y. Liu*: Transfer learning of high-dimensional features via attention-based embedding for Ni-based superalloys, J. Appl. Phys., 138, 024902 (2025), invited article
263. Y. Tang; B. Xiao; M. Ihara; S. Manzhos*, Y. Liu*: Effects of nonlinearity and inter-feature coupling in machine learning studies of Nb alloys with center-environment features, J. Mater. Inform., 5, 38 (2025)
262. H. Lee, K. Kameda, S. Manzhos*, M. Ihara*: A novel encoding method for high-dimensional categorical data for electricity demand forecasting in distributed energy systems, Appl. Energy, 392, 125989 (2025)
261. F. M. Alzubaidi, Q. Liu*, S. Manzhos, P. Sonar*, E. L. Izake*, G. A. Ayoko: A new disposable paper-based chemosensor for the rapid and direct detection of hexavalent chromium in aqueous media, J. Anal. Test., (2025) https://doi.org/10.1007/s41664-025-00380-z
260. R. Li, K. Maeda, K. Kameda, M. Ihara*, S. Manzhos*: Exploring electronic properties of carbon nanoflake-based charge transport materials for perovskite solar cells: a computational study, Phys. Chem. Chem. Phys., 27, 7611-7628 (2025)
259. Y. Cheng, T. Araki, N. Kamimura, E. Masai, M. Nakamura, S. Manzhos*, T. Michinobu*: Accelerated development of novel biomass-based polyurethane adhesives via machine learning, ACS Appl. Mater. Interfaces, 17, 15959–15968 (2025)
258. R. Kothandaraman, W. He, K. Kakaraparthi, S. Manzhos, C. McNeill, Y. Li, Y. Xu, K. Fairfull-Smith, T. Michinobu, P. Sonar*: High performance n-type OFETs enabled by pyridine-substituted diketopyrrolopyrrole organic semiconductor and elastomer stretchable blends, Adv. Mater. Technol., 10, 2401518 (2025)
257. Y. Thant, T. Wakamiya, M. Nukunudompanich*, K. Kameda, M. Ihara*, S. Manzhos*: Kernel regression methods for prediction of materials properties: recent developments, Chem. Phys. Rev., 6, 011306 (2025), featured article
256. Y. Thant, S. Manzhos*, M. Ihara, M. Nukunudompanich*: On the sufficiency of a single hidden layer in feed-forward neural networks used for machine learning of materials properties, PhysChem, 5, 4 (2025)
255. D. Koch, M. Pavanello*, X. Shao, M. Ihara, P. W. Ayers, C. F. Matta*, S. Jenkins*, S. Manzhos*: The analysis of electron densities: from basics to emergent applications, Chem. Rev., 124, 12661–12737 (2024), invited review
254. J. Luder, M. Ihara, S. Manzhos*: A machine-learned kinetic energy model for light weight metals and compounds of group III-V elements, Electr. Struct., 6, 045002 (2024), invited article
253. K. Kakaraparthi, V. Sethumadhavan, S. Kumagai, Y. Xu, A. Erhardt, C. R. McNeill, S. Manzhos, J. Takeya, P.Sonar*: Low band gap furan-flanked diketopyrrolopyrrole-naphthobisthiadiazole based conjugated polymer/stretchable blend for organic field effect transistors, Adv. Electron. Mater., 11, 2400614 (2025)
252. K. Kameda, T. Ariga, K. Ito, M. Ihara*, S. Manzhos*: Machine learning the screening factor in the soft bond valence approach for rapid crystal structure estimation, Digital Discovery, 3, 1967-1979 (2024), invited article, back cover
251. S. Manzhos*, Q.-G. Chen, W.-Y. Lee, H. Yoon, M. Ihara, C.-C. Chueh*: Computational investigation of the potential and limitations of machine learning with neural network circuits based on synaptic transistors, J. Phys. Chem. Lett., 15, 6974-6985(2024)
250. K. Kranthiraja, W. He, H.-W. Yu, Z. Feng, N. Nozaki, H. Matsumoto, M.-H. Yu, Y. Li, S. Manzhos, M. R. Andersson, C.-C. Chueh*, T. Michinobu*, P. Sonar*: Diketopyrrolopyrrole-dioxo-benzodithiophene-based multi-functional conjugated polymers for organic field effect transistors and perovskite solar cells, Solar RRL, 8, 2470143 (2024), back cover
249. T. Okamoto, A. Sorkin, K. Kameda, M. Ihara*, H. Wang*, S. Manzhos*: Natural-like generation of grain boundary models and the combined effects of microstructural elements and lithiation on the plastic behavior of TiO2: a computational study, Comp. Mater. Sci., 239, 112989 (2024)
248. H. Suzuki*, J. Kametaka, S. Nakahori, Y. Tanaka, M. Iwahara, H. Lin, S. Manzhos, A. K. K. Kyaw, T. Nishikawa, Y. Hayashi*: N-DMBI doping of carbon nanotube yarns for achieving high n-type thermoelectric power factor and figure of merit, Small Methods, 8, 2301387 (2024)
247. S. Manzhos*, M. Ihara*: Degeneration of kernel regression with Matern kernels into low-order polynomial regression in high dimension, J. Chem. Phys., 160, 021101 (2024)
246. M. Nukunudompanich, H. Yoon, L. Hyojae, K. Kameda, M. Ihara*, S. Manzhos*: Machine learning of properties of lead-free perovskites with a neural network with additive kernel regression-based neuron activation functions, MRS Adv., 9, 857–862 (2024) Highlighted in MRS Bulletin https://doi.org/10.1557/s43577-025-01051-1
245. R. Li, G. Budiutama, S. Manzhos*, M. Ihara*: Hybrid DFTB – Molecular Mechanics approach: applicability to optical properties, Proceeding of 34th IUPAP Conference on Computational Physics (CCP2023), Springer Proceedings in Physics, accepted
244. S. Manzhos*, J. Lueder, M. Ihara*: Machine learning of kinetic energy densities with target and feature smoothing: better results with fewer training data, J. Chem. Phys., 159, 234115 (2023)
243. S. Manzhos*, M. Ihara*: Neural networks with rules-based parameters and without nonlinear optimization: comparison of fixed-shaped and optimized neuron activation functions, Proceeding of 34th IUPAP Conference on Computational Physics (CCP2023), Springer Proceedings in Physics, accepted
242. M.-I. Trappe*, W. C. Witt, S. Manzhos: Atoms, dimers, and nanoparticles from orbital-free density-potential functional theory, Phys. Rev. A, 108, 062802 (2023)
241. S. Manzhos*, M. Ihara: A controlled study of the effect of deviations from symmetry of the potential energy surface (PES) on the accuracy of the vibrational spectrum computed with collocation, J. Chem. Phys., 159, 211103 (2023)
240. K. Kameda, S. Manzhos, M. Ihara*: Development status of high temperature proton conductors as solid oxide fuel cells/electrolysis cells materials; experimental and computational approaches, Journal of the Hydrogen Energy Systems Society of Japan (HESS), 48, 99-110 (2023). (亀田 恵佑、Sergei Manzhos、伊原 学*: 固体㓟化物燃料㟁池/㟁解セル材料としての㧗温プロトン伝導体の㛤発状況とィ算化学の利用,水素エネルギーシステム48, 99-110 (2023))
239. G. S. Selopal, O. Abdelkarim, J. Kaur, J. Liu, L. Jin, Z. Chen, F. Navarro-Pardo, S. Manzhos, S. Sun, A. Yurtsever, H. Zarrin, Z. M. Wang, F. Rosei*: Surface engineering of two-dimensional hexagonal boron-nitride for optoelectronic devices, Nanoscale, 15, 15810-15830 (2023)
238. M. Nukunudompanich*, K. Suzuki, S. Manzhos, K. Kameda, M. Ihara*: Nano-scale smooth surface of compact-TiO2 layer via spray pyrolysis for controlling the grain size of the perovskite layer in perovskite solar cells, RSC Adv., 13, 27686-27695 (2023)
237. S. Manzhos*, M. Ihara*: Neural network with optimal neuron activation functions based on additive Gaussian process regression, J. Phys. Chem. A, 127, 7823–7835 (2023), Invited article
236. S. Manzhos*, M. Ihara*: Orders-of-coupling representation achieved with a single neural network with optimal neuron activation functions and without nonlinear parameter optimization, Artificial Intelligence Chemistry, 1, 100013 (2023), Invited article
235. S. Manzhos*, M. Ihara*: Rectangularization of Gaussian process regression for optimization of hyperparameters, Mach. Learn. Appl., 13, 100487 (2023)
234. S. Manzhos*, T. Carrington*, M. Ihara*: Orders of coupling representations as a versatile framework for machine learning from sparse data in high-dimensional spaces, Artificial Intelligence Chemistry, 1, 100008 (2023), Invited review
233. G. Budiutama, R. Li, M. Ihara*, S. Manzhos*: Hybrid Density Functional Tight Binding (DFTB) – molecular mechanics approach for a low-cost expansion of DFTB applicability, J. Chem. Theory Comput., 19, 5189-5198 (2023)
232. P. Sundarapura, S. Manzhos*, M. Ihara*: Clarifying effects of nanoscale porosity of silicon on the bandgap and alignment: a combined molecular dynamics – density functional tight binding computational study, Phys. Chem. Chem. Phys., 25, 14566-14577 (2023)
231. N. Yan, S. Hill, S. Manzhos, T. Carrington*: A local Gaussian Processes method for fitting potential surfaces that obviates the need to invert large matrices, J. Mol. Spectrosc., 393, 111774 (2023)
230. S. Manzhos*, M. Ihara*, T. Carrington*: Using collocation to solve the Schrödinger equation, J. Chem. Theory Comput., 19, 1641–1656 (2023), Invited review
229. K. Kim, J. Han, S. Lee, S. Kim, J.-M. Choi, J.-S. Nam, D. Kim, I. Chung, T.-D. Kim, S. Manzhos, S. J. Choi, J. W. Song, D. S. Kim, J. Y. Do, I. Jeon*: Liquid-state dithiocarbonate-based polymeric additives with monodispersity rendering perovskite solar cells with exceptionally high certified photocurrent and fill factor, Adv. Energy. Mater., 13, 2203742 (2023)
228. T. Okubo, T. Shimizu, K. Hasegawa, Y. Kikuchi, S. Manzhos, M. Ihara*: Factors affecting the techno-economic and environmental performance of on-grid distributed hydrogen energy storage systems with solar panels, Energy, 269, 126736 (2023)
227. S. Manzhos*, T. Carrington*: Advances in rectangular collocation for solution of the Schrödinger equation: from obviating integrals to machine learning. In Density Functionals for Many-Particle Systems: Mathematical Theory and Physical Applications of Effective Equations (Eds. B.-G. Englert, M.-I. Trappe), series Lecture Notes Series, Institute for Mathematical Sciences, National University of Singapore, vol. 41, World Scientific, 2023
226. S. Manzhos*, M. Ihara*: The loss of the property of locality of the kernel in high-dimensional Gaussian process regression on the example of the fitting of molecular potential energy surfaces, J. Chem. Phys., 158, 044111 (2023)
225. G. Budiutama*, S. Manzhos, M. Ihara: Investigation of expressive power of a neural network architecture suited for optical neural networks, Proc. SPIE, 12318, 123180G (2022)
224. A. Sorkin, Y. Guo, M. Ihara, S. Manzhos*, H. Wang*: Non-invasive improvement of machining by reversible electrochemical doping: a proof of principle with computational modeling on the example of lithiation of TiO2, Mater. Chem. Phys., 295, 127183 (2023)
223. W. He, Q. Liu, S. Otep, H. Matsumoto, S. Manzhos, P. Sonar, A. K. Kyaw, T. Michinobu*: Tetramethylammonium iodide additive for enhancing the charge carrier mobilities of diketopyrrolopyrrole-based conjugated polymer in ambipolar organic field-effect transistors, Chin. J. Chem., 41, 1028-1036 (2023)
222. S. Manzhos*, S. Tsuda, M. Ihara*: Machine learning in computational chemistry: interplay between (non)linearity, basis sets, and dimensionality, Phys. Chem. Chem. Phys., 25, 1546-1555 (2023), invited perspective review
221. S. Manzhos*, M. Ihara: Optimization of hyperparameters of Gaussian process regression with the help of low-order high-dimensional model representation: application to a potential energy surface, J. Math. Chem., 61, 7–20 (2023)
220. T.-T. Do, Y. Takeda, T. Sekine, Y. Yadav, S. Manzhos, K. Feron, S. P. Singh, S. Tokito, P. Sonar*: Bottom gate top contact organic transistors using thiophene and furan flanked diketopyrrolopyrrole polymers and its comparative study, Flex. Print. Electron., 7, 035014 (2022)
219. D. Koch, S. Manzhos*, M. Chaker: The role of local DFT+U minima in the first-principles modeling of the metal-insulator transition in vanadium dioxide, J. Phys. Chem. A, 126, 3604–3611 (2022)
218. S. Manzhos*, M. Ihara: Computational vibrational spectroscopy of molecule-surface interactions: what is still difficult and what can be done about it, Phys. Chem. Chem. Phys., 24, 15158-5172 (2022), invited perspective review, cover page, PCCP Hot Article
217. H. D. Pham, G. Banappanavar, S. Somasundaram, K. Deshmukh, H. Lim, A. Shukla, V. Ahmad, S. McGregor, S. Manzhos, S.-C. Lo, D. Kabra, E. Namdas, P. Sonar*: Fluorenone and triphenylamine based donor-acceptor-donor (D-A-D) for solution-processed organic light-emitting diodes, Flex. Print. Electron., 7, 025009 (2022)
216. L. Hao*, S. Manzhos*, Z. Zhang: Theoretical insight into diamond doping and its possible effect on diamond tool wear during cutting of steel, Front. Mater. 8, 806466 (2021)
215. S. Manzhos*, M. Ihara: Advanced machine learning methods for learning from sparse data in high-dimensional spaces: a perspective on uses in the upstream of development of novel energy technologies, PhysChem, 2, 72-95 (2022)
214. G. Budiutama, S. Manzhos, M. Ihara*: Effective passivation of TiO2/Si by interlayer SiOx controlled by scanning zone annealing for perovskite/Si tandem solar cell, Solar Energy, 236, 772-781 (2022)
213. Q. Liu, W. He, Y. Shi, S. Otep, W. L. Tan, S. Manzhos, C. McNeill, X. Guo, P. Sonar, Prashant, T. Michinobu, A. K. K. Kyaw*: Directional carrier polarity tunability in ambipolar organic transistors based on diketopyrrolopyrrole and bithiophene imide dual-acceptor semiconducting polymers, Chem. Mater., 34, 3140-3151 (2022)
212. H. Kulik*, T. Hammerschmidt*, J. Schmidt*, S. Botti*, M. A. L. Marques*, M. Boley, M. Scheffler*, M. Todorović, P. Rinke*, C. Oses, A. Smolyanyuk, S. Curtarolo*, A. Tkatchenko, A. Bartok*, S. Manzhos*, M. Ihara, T. Carrington, J. Behler, O. Isayev, M. Veit, A. Grisafi, J. Nigam, M. Ceriotti*, K. T. Schütt*, J. Westermayr, M. Gastegger, R. Maurer, B. Kalita, K. Burke*, R. Nagai, R. Akashi, O. Sugino, J. Hermann, F. Noé, S. Pilati*, C. Draxl, M. Kuban, S. Rigamonti, M. Scheidgen, M. Esters, D. Hicks, C. Toher*, P. Balachandran, I. Tamblyn, S. Whitelam, C. Bellinger, L. M. Ghiringhelli*: Roadmap on machine learning in electronic structure, Electron. Struct., 4, 023004 (2022) , invited review
211. S. Manzhos*, E. Sasaki, M. Ihara: Easy representation of multivariate functions with low-dimensional terms via Gaussian process regression kernel design: applications to machine learning of potential energy surfaces and kinetic energy densities from sparse data, Mach. Learn.: Sci. Technol., 3, 01LT02 (2022)
210. O. Ren, M. Ali Boussaidi, D. Voytsekhovsky, M. Ihara, S. Manzhos*: Random Sampling High Dimensional Model Representation Gaussian Process Regression (RS-HDMR-GPR) for representing multidimensional functions with machine-learned lower-dimensional terms allowing insight with a general method, Comput. Phys. Commun., 271, 108220 (2022)
209. K. Kameda, S. Manzhos, M. Ihara*: Carbon/air secondary battery system and demonstration of its charge-discharge, J. Power Sources, 516, 230681 (2021)
208. S. Manzhos*, M. Ihara, T. Carrington: “Machine learning for vibrational spectroscopy“. In Quantum Chemistry in the Age of Machine Learning (Ed. P. Dral) , Elsevier, Amsterdam (2022)
207. Y. J. Lee, Y. Zhang, A. Sorkin, S. Manzhos*, H. Wang*: Effect of a weak magnetic field on ductile-brittle transition in micro-cutting of single-crystal calcium fluoride, J. Mater. Sci. Technol., 112, 96-113 (2022)
206. D. Koch*, M. Chaker, M. Ihara, S. Manzhos*: Density-based descriptors of redox reactions involving transition metal compounds as a reality-anchored framework: a perspective. Molecules, 26, 5541 (2021), invited, review
205. Q. Liu, D. Moghe, G. Sardar, S. Manzhos, S. E. Bottle, A. K. K. Kyaw, D. Kabra, P. Sonar*: Structural geometry variation of 1,4-naphthalene-based copolymers to tune the device performance of PVK-host-based OLEDs, Polymers, 13, 2914 (2021)
204. S. Manzhos*, G. Giorgi, J. Lüder, M. Ihara: Modeling methods for plasmonic effects in halide perovskite-based systems for photonics applications. In Halide Perovskites for Photonics. (A. Vinattieri and G. Giorgi, Eds.). AIP Publishing, Melville NY, USA (2021)
203. M. D. Gholami, Q. Liu, P. Sonar*, S. Manzhos, G. A. Ayoko, E. L. Izake*: Naphthalene flanked diketopyrrolopyrrole: a new functional dye based optical sensors for monitoring cyanide ions in water, Adv. Mater. Technol., 7, 2100170 (2022)
202. S. Manzhos*, C.-C. Chueh, G. Giorgi*, T. Kubo, S. Gopalan, J. Lüder, P. Sonar, M. Ihara: Materials design and optimization for next generation solar cell and light-emitting technologies, J. Phys. Chem. Lett., 12, 4638–4657 (2021) , invited Perspective review
201. P. Li, J. Fang, Y. Wang, S. Manzhos, L. Cai, Z. Song, Y. Li, T. Song, X. Wang, X. Gao, M. Zhang, D. Ma, B. Sun*: Synergistic effect of dielectric property and energy transfer on charge separation in non-fullerene based solar cells, Angew. Chem. Int. Ed., 60, 15054-15062 (2021)
200. H.-S. Lin, Y. Ma, R. Xiang, S. Manzhos, I. Jeon, S. Maruyama, Y. Matsuo*: One-step direct oxidation of alkoxy to ketone for evaporable fullerene-fused ketone as efficient electron-transport materials, Comm. Chem., 4, 74 (2021)
199. S. Manzhos*, G. Giorgi, J. Lüder, M. Ihara: Modeling of plasmonic properties of nanostructures for next generation solar cells and beyond, Adv. Phys. X, 6, 1908848 (2021), invited review
198. J. Lueder, S. Manzhos*: Non-parametric local pseudopotentials with machine learning: a tin pseudopotential built using Gaussian process regression, J. Phys. Chem. A, 124, 11111–11124 (2020), invited article to Emily A. Carter Festschrift
197. Q. Liu, S. Chavhan, H. Zhang, H. Sun, A. Brock, S. Manzhos, Y. Chen, K. Feron, S. E. Bottle, J. McMurtrie, J.-H. Jou, H.-S. Chen, M. R. Nagar, W. Hu, Y.-Y. Noh, Y. Zhen, P. Sonar*: Short alkyl chain engineering modulation on naphthalene flanked diketopyrrolopyrrole towards high-performance single crystal transistors and organic thin film displays, Adv. Electr. Mater., 7, 2000804 (2021)
196. Q. Liu, Y. Wang, L. Arunagiri, M. Khatib, S. Manzhos, K. Feron, S. E. Bottle, H. Haick, H. Yan, T. Michinobu, P. Sonar*: Versatile nature of anthanthrone based polymers as active multifunctional semiconductors for various organic electronic devices, Mater. Adv., 1, 3428-3438 (2020)
195. T. T. Do, S. Meera, S. Manzhos, P. L. Burn, P. Sonar*: Pyrrolo[3,2-b]pyrrole-1,4-dione (IsoDPP) end capped with napthalimide or phthalimide: novel small molecular acceptors for organic solar cells, Molecules, 25, 4700 (2020)
194. S. Manzhos*, T. Carrington: Neural network potential energy surfaces for small molecules and reactions, Chem. Rev., 121, 10187–10217 (2021) , invited review
193. Y. Ma, H. Ueno, H. Okada, S. Manzhos*, Y. Matsuo*: Solvation-free Li+ Lewis acid enhancing reaction: kinetic study of [5,6]-Li+@PCBM to [6,6]-Li+@PCBM, Org. Lett., 22, 7239–7243 (2020)
192. M. A. Boussaidi, O. Ren, D. Voytsekhovksy, S. Manzhos*: Random Sampling High Dimensional Model Representation Gaussian Process Regression (RS-HDMR-GPR) for multivariate function representation: Application to molecular potential energy surfaces, J. Phys. Chem. A, 124, 7598−7607 (2020), invited article
191. D. Koch*, S. Manzhos*: Oxygen redox activity in cathodes – a common phenomenon calling for density-based descriptors, J. Phys. Chem. C, 124, 19962−19968 (2020), invited article to Emily A. Carter Festschrift
190. S. Manzhos*, P. Golub: Data-driven kinetic energy density fitting for orbital-free DFT: linear vs Gaussian process regression, J. Chem. Phys., 153, 074104 (2020), invited article
189. D. Koch*, S. Manzhos*: Can doping of transition metal oxide cathode materials increase achievable voltages with multivalent metals? Int. J. Quantum Chem., 121, e26439 (2021) , invited article
188. D. Koch*, S. Petnikota, Z. Yang, M. Srinivasan, S. Manzhos*: Electrochemical performance of B-type vanadium dioxide as sodium-ion battery cathode: a combined experimental and theoretical study, ChemElectroChem, 7, 3151-3159 (2020)
187. W. Jang, S. Rasool, B. G. Kim, J. Yoon, S. Manzhos, H. K. Lee, I. Jeon*, D. H. Wang*: Superior noise suppression, response time, and device stability of non-fullerene system over fullerene counterpart in organic photodiode, Adv. Funct. Mater., 30, 2001402 (2020)
186. D. Koch*, S. Manzhos*: Interstitial vs. substitutional metal insertion in V2O5 as post-lithium ion battery cathode: a comparative GGA/GGA+U study with localized bases, MRS Commun., 10, 259-264 (2020), invited article
185. P. Golub*, S. Manzhos*: CONUNDrum: a program for Orbital-Free Density Functional Theory calculations, Comput. Phys. Commun., 256, 107365 (2020)
184. S. Manzhos*: Aggregate state effects in the atomistic modeling of organic materials for electrochemical energy conversion and storage devices: a perspective, Molecules, 25, 2233 (2020), review
183. Q. Liu, S. Kumagai, S. Manzhos, I. Angunawela, M. Morshed Nahid, K. Feron, S. E. Bottle, J. Bell, H. Ade, J. Taketa, P. Sonar*: Synergistic use of pyridine and selenophene in a diketopyrrolopyrrole-based conjugated polymer enhances the electron mobility in organic transistors, Adv. Funct. Mater., 30, 2000489 (2020)
182. H.-S. Lin, S. Okawa, Y. Ma, S. Yotsumoto, C. Lee, S. Tan, S. Manzhos, M. Yoshizawa, S. Chiashi, H. M. Lee, T. Tanaka, H. Kataura, I. Jeon*, Y. Matsuo, S. Maruyama, Polyaromatic nano-tweezer on semiconducting carbon nanotubes for the growth and interfacing of lead-halide perovskite crystal grains in solar cells, Chem. Mater., 32, 5125–5133 (2020)
181. Q. Liu, Y. Wang, S. Manzhos, S. Bottle, J. Bell, A. Kohara, H. Matsumoto, Y. Chen, K. Feron, Y. Ren, T. Michinobu, P. Sonar*: Diketopyrrolopyrrole-based dual-acceptor copolymers to realize tunable charge carrier polarity of organic transistors and high-performance non-volatile ambipolar flash memories, ACS Appl. Electron. Mater., 2, 1609–1618 (2020)
180. S. Manzhos*: Machine learning for the solution of the Schrödinger equation, Mach. Learn.: Sci. Technol., 1, 013002 (2020), invited perspective review
179. Q. Liu, K. Kanahashi, K. Matsuki, S. Manzhos, K. Feron, S. E. Bottle, K. Tanaka, T. Nanseki, T. Takenobu, H. Tanaka, P. Sonar*: Triethylene glycol substituted diketopyrrolopyrrole- and isoindigo-dye based donor-acceptor copolymers for organic light-emitting electrochemical cells and transistors, Adv. Electr. Mater., 6, 1901414 (2020), cover page
178. D. Koch*, Y. Chen, P Golub, S. Manzhos*: Reply to the 'Comment on “Revisiting π backbonding: the influence of d orbitals on metal–CO bonds and ligand red shifts”' by G. Frenking and S. Pan, Phys. Chem. Chem. Phys., 2019, 22, DOI: 10.1039/C9CP05951B, Phys. Chem. Chem. Phys., 22, 5380-5382 (2020)
177. J. Lüder*, S. Manzhos*: First-principle insights into molecular design for high-voltage organic electrode materials for Mg based batteries, Front. Chem., 8, 83 (2020)
176. D. Koch*, S. Manzhos: First-principles study of the electrochemical sodiation of rutile-type vanadium dioxide, MRS Adv., 5, 1467-1474 (2020)
175. T. Tian, T. Xu, S. R. Kirk*, I. T. Rongde, T. Y. Boon, S. Manzhos, Y. Shigeta, S. Jenkins*: Intramolecular mode coupling of the isotopomers of water: a non-scalar charge density-derived perspective, Phys. Chem. Chem. Phys., 22, 2509-2520 (2020)
174. H. D. Pham, S. M. Jain*, M. Li, Z.-K. Wang, S. Manzhos, K. Feron, S. Pitchaimuthu, Z. Liu, N. Motta, J. R. Durrant, P. Sonar*: All-rounder low cost dopant free D-A-D hole transporting materials for efficient indoor and outdoor performance of perovskite solar cells, Adv. Electronic Mater., 6, 1900884 (2020), Top Cited Article 2020-2021
173. Q. Liu, Y. Wang, A. Kohara, H. Matsumoto, S. Manzhos, K. Feron, S. E. Bottle, J. Bell, T. Michinobu, P. Sonar*: Tuning the charge carrier polarity of organic transistors by varying the electron affinity of the flanked units in diketopyrrolopyrrole-based copolymers, Adv. Funct. Mater., 30, 1907452 (2020)
172. J. Ku, A. Kamath, T. Carrington, S. Manzhos*: Machine learning optimization of the collocation point set for solving the Kohn-Sham equation, J. Phys. Chem. A, 123, 10631-10642 (2019)
171. J. Salunke, A. Singh, D. He, H. D. Pham, Y. Bai, L. Wang, S. Dahlström, M. Nyman, S. Manzhos, K. Feron, R. Österbacka, A. Priimagi, P. Vivo, P. Sonar*: Fluorination of pyrene-based organic semiconductors enhances the performance of light emitting diodes and halide perovskite solar cells, Organic Electronics, 77, 105524 (2020)
170. D. Koch, S. Manzhos*: Ab initio modeling and design of vanadia based electrode materials for post-Li batteries, J. Phys. D: Appl. Phys., invited review, 53, 083001 (2020)
169. I. Jeon, A. Shawky, H. Okada, H.-S. Lin, J.-W. Lee, A. Pal, S. Tan, A. Anisimov, E. Kauppinen, Y. Yang, S. Manzhos, S. Maruyama, Y. Matsuo*: Controlled redox of lithium-ion endohedral fullerene for efficient and stable metal electrode-free perovskite solar cells, J. Am. Chem. Soc., 141, 16553-16558 (2019)
168. H.-S. Lin, I. Jeon, Y. Chen, X. Yang, T. Nakagawa, S. Maruyama, S. Manzhos, Y. Matsuo*: Highly selective and scalable fullerene-cation-mediated synthesis accessing cyclo[60]fullerenes with 5-membered-carbon-ring and their application to perovskite solar cells, Chem. Mater., 31, 8432-8439 (2019)
167. D. Koch*, Y. Chen, P Golub, S. Manzhos*: Revisiting π backbonding: the influence of d orbitals on metal-CO bonds and ligand red shifts, Phys. Chem. Chem. Phys., 21, 20814-20821 (2019)
166. M. D. Gholami, S. Manzhos, P. Sonar, G. A. Ayokoa, E. L. Izake: Dual chemosensor for the rapid detection of mercury (II) pollution and biothiols, Analyst, 144, 4908-4916 (2019)
165. Q. Liu, H. Sun, S. P. Ponnappa, K. Feron, S. Manzhos, S. E. Bottle, J. Bell, Y.-Y. Noh, P. Sonar*: Naphthalene flanked diketopyrrolopyrrole: a new DPP family member and its comparative optoelectronic properties with thiophene- and furan- flanked DPP counterparts, Organic Electronics, 74, 290-298 (2019)
164. Y. Chen, C.-R. Cho, S. Manzhos*: Lithium attachment to C60 and nitrogen- and boron-doped C60: a mechanistic study, Materials, 12, 2136 (2019), cover page
163. Y. J. Lee, L. Hao, J. Lüder, A. Chaudhari, S. Wang, S. Manzhos, Hao Wang*: Micromachining of ferrous metal with an ion implanted diamond cutting tool, Carbon, 152, 598-608 (2019)
162. T.-T. Do, J. Subbiah, S. Chavan, T.-H. Ou, S. Manzhos, D. Jones, J. M. Bell, J. H. Jou, P. Sonar*: Naphthalimide end-capped diphenylacetylene: a versatile organic semiconductor for blue light emitting diodes and donor or acceptor for solar cells, New J. Chem., 43, 9243-9254 (2019)
161. H. D. Pham, L. Gil-Escrig, K. Feron, S. Manzhos, S.Albrecht, H. J. Bolink, P. Sonar*: Boosting inverted perovskite solar cells performance by using functionalized 9,9-bis(4-diphenylaminophenyl)fluorenes with triphenylamine as dopant-free hole transporting materials, J. Mater. Chem. A, 7, 12507-12517 (2019)
160. S. Manzhos*, A. Pal, Y. Chen, G. Giorgi: Effect of organic cation states on electronic properties of mixed organic-inorganic halide perovskite clusters, Phys. Chem. Chem. Phys., 21, 8161-8169 (2019)
159. T. T. Do, K. Matsuki, T. Sakanoue, F.-L. Wong, S. Manzhos, C.-S. Lee, J. Bell, T. Takenobu, P. Sonar*, Indenofluorene-based copolymers: influence of electron-deficient benzothiadiazole (BT) and benzooxadiazole (BO) moieties on light emitting devices, Org. Electron., 70, 14-24 (2019)
158. Y. B. Tan, I. R. Tay, L. Y. Loy, K. F. Aw, Z. L. Ong, S. Manzhos*: A scheme for ultrasensitive detection of molecules by using vibrational spectroscopy in combination with signal processing, Molecules, 24, 776 (2019)
157. A.Tripathi, Y. Chen, H. Padhy, S. Manzhos*, P. Balaya*: Experimental and theoretical studies of trisodium-1,3,5- benzene tricarboxylate as a low voltage anode material for sodium ion batteries. Energy Technol., 7, 1801030 (2019) , Highlighted by Advances in Engineering
156. I. Jeon, A. Thote, H.-S. Lin, S. Manzhos, T. Nakagawa, D. Suh, J. Hwang, M. Kashiwagi, J. Shiomi, S. Maruyama*, H. Daiguji*, Y. Matsuo*: High working-pressure sputtering of ZnO for stable and efficient perovskite solar cells, ACS Appl. Electronic Mater., 1, 389-396 (2019)
155. P. Sonar*, H. D. Pham, S. M. Jain, L. Meng, S. Manzhos, K. Feron, S. Pitchaimuthu, Z. Liu, N. Motta, H. Wang, J. Durrant: Dopant-free, novel hole transporting materials based on quinacridone dye for high-performance and humidity stable mesoporous perovskite solar cells, J. Mater. Chem. A., 7, 5315-5323 (2019)
154. H. D. Pham, L. Xianqiang, L. Wenhui, S. Manzhos, A. K. Kyaw, P. Sonar*: Organic interfacial materials for perovskite-based optoelectronic devices, Energy Environ. Sci., 12, 1177-1209 (2019), review
153. S. Arabnejad, A. Pal, K. Yamashita, S. Manzhos*: Effect of nuclear motion on charge transport in fullerenes: a combined Density Functional Tight Binding – Density Functional Theory investigation, Frontiers in Energy Research, 7, 3 (2019)
152. S. Manzhos*: Organic electrode materials for lithium and post-lithium batteries: an ab initio perspective on design, Curr. Opin. Green Sustain. Chem., 17, 8-14 (2019), invited review
151. D. Koch, S. Manzhos: A comparative first-principles study of lithium, sodium and magnesium insertion energetics in brookite titanium dioxide, MRS Adv., 4, 837-842 (2019)
150. P. Golub*, S. Manzhos*: Kinetic energy densities based on the fourth order gradient expansion: performance in different classes of materials and improvement via machine learning, Phys. Chem. Chem. Phys., 21, 378-395 (2019)
149. A. Kamath, S. Manzhos*: Inverse multiquadratic functions as basis for the rectangular collocation method to solve the vibrational Schrödinger equation, Mathematics, 6, 253 (2018)
148. S. Manzhos*, T. Carrington: Using rectangular collocation with finite difference derivatives to solve electronic Schrödinger equation, J. Chem. Phys., 149, 204105 (2018)
147. H.-S. Lin, I. Jeon*, R. Xiang, S. Seo, J.-W. Lee, C. Li, A. Pal, S. Manzhos, M. S. Goorsky, Y. Yang, S. Maruyama, Y. Matsuo*: Achieving high efficiency in solution-processed perovskite solar cells using C60/C70 mixed fullerenes, ACS Appl. Mater. Interfaces, 10, 39590-39598 (2018)
146. D. Koch, S. Manzhos*: The role of solvent charge donation in the stabilization of metal ions in aqueous solution, MRS Commun., 8, 1139-1144 (2018), Invited article
145. H. D. Pham, H. Hu, F.-L. Wong, C.-S. Lee, W.-C. Chen, K. Feron, S. Manzhos, H. Wang, N. Motta, Y. M. Lam, P. Sonar*: Acene-based organic semiconductors for organic light-emitting diodes and perovskite solar cells, J. Mater. Chem. C, 6, 9017-9029 (2018)
144. Ang Siong Tuan, A. Pal, S. Manzhos*: Comparison of optical absorption spectra of organic molecules and aggregates computed from real frequency dependent polarizability to TD-DFT and the dipole approximation, J. Chem. Phys., 149, 044114 (2018)
143. T. T. Do, J. Subbiah, S. Manzhos, D. Jones, J. Bell, P. Sonar*: Phthalimide and naphthalimide: effect of end-capping groups on molecular properties and photovoltaic performance of 9-fluorenone based acceptors for organic solar cells, Organic Electronics, 62, 12-20 (2018)
142. Q. Liu, H. Sun, S. P. Ponnappa, K. Feron, S. Manzhos, S. Bottle, Y.-Y. Noh, P. Sonar*: Naphthalene flanked diketopyrrolopyrrole based organic semiconductors for high performance organic field effect transistors, New J. Chem, 42, 12267-13184 (2018), journal cover
141. D. Koch, S. Manzhos*: First-principles study of the calcium insertion in layered and non-layered phases of vanadia, MRS Adv., 3, 3507-3512 (2018)
140. A. Pal, S. Arabnejad, K. Yamashita, S. Manzhos*: Influence of the aggregate state on band structure and optical properties of C60 computed with different methods, J. Chem. Phys., 148, 204301 (2018)
139. D. Koch, P. Golub, S. Manzhos*: Stability of charges in titanium compounds and charge transfer to oxygen in titanium dioxide, J. Phys.: Conf. Ser. 1136, 012017 (2018)
138. T.-T. Do, Y. Takeda, S. Manzhos, J. Bell, S. Tokito, P. Sonar*: Naphthalimide end capped anthraquinone based solution-processable n-channel organic semiconductors: effect of alkyl chain engineering on charge transport, J. Mater. Chem. C, 6, 3774-3786 (2018)
137. Q. Liu, A. Surendran, K. Feron, S. Manzhos, X. Jiao, C. R. McNeill, S. E. Bottle, J. Bell, W. L. Leong, P. Sonar*: Diketopyrrolopyrrole based organic semiconductors with different numbers of thiophene units: symmetry tuning effect on electronic devices, New J. Chem., 42, 4017-4028 (2018)
136. H. D. Pham, T. T. Do, J. Kim, C. Charbonneau, S. Manzhos, K. Feron, W. C. Tsoi, J. R. Durrant, S. M. Jain*, P. Sonar*: Molecular engineering using an anthanthrone dye for low cost hole transport materials: a strategy for dopant free, high efficiency and stable perovskite solar cells, Adv. Energy Mater., 8, 1703007 (2018), video highlight
135. H.-D. Pham, K. Hayasake, J. Kim, T. T. Do, H. Matsui, S. Manzhos, K. Feron, S. Tokito, T. Watson, W. C. Tsoi, N. Motta, J. R. Durrant, S. M. Jain*, P. Sonar*: One step facile synthesis of novel anthanthrone dye based, dopant-free hole transporting material for efficient and stable perovskite solar cells. J. Mater. Chem. C, 6, 3699-3708 (2018)
134. V. Kulish, W. Liu, F. Benistant, S. Manzhos*: Dopant-dopant interactions in beryllium doped indium gallium arsenide: an ab initio study, J. Mater. Res., 33, 401-413 (2018), invited article
133. V. Kulish, D. Koch, S. Manzhos*: Insertion of mono- vs. bi- vs. trivalent atoms in prospective active electrode materials for electrochemical batteries: an ab initio perspective, Energies, 10, 2061 (2017), invited review
132. Y. Chen, J. Lueder, M. F. Ng, M. Sullivan, S. Manzhos*: Polyaniline and CN-functionalized polyaniline as organic cathodes for lithium and sodium ion batteries: a combined molecular dynamics and Density Functional Tight Binding Study in solid state, Phys. Chem. Chem. Phys., 20, 232-237 (2018)
131. M. Pilz da Cunha, T. T. Do, S. D. Yambem, H. D. Pham, Samuel Chang, S. Manzhos, Ryuzi Katoh, P. Sonar*: A triphenylamine-substituted quinacridone derivative for solution processed organic light emitting diodes, Mater. Chem. Phys., 206, 56-63 (2018)
130. A. Kamath, R. A. Vargas-Hernández, R. V. Krems, T. Carrington Jr., S. Manzhos*: Neural Networks vs Gaussian Process regression for representing potential energy surfaces: a comparative study of fit quality and vibrational spectrum accuracy, J. Chem. Phys., 148, 241702 (2018), invited article, Editor's Pick
129. S. Manzhos*, X. Wang, T. Carrington*: A multimode-like scheme for selecting the centers of Gaussian basis functions when computing vibrational spectra, Chem. Phys., 509, 139–144 (2018), invited article
128. A. Pal, Lai Kai Wen, Chia Yao Jun, I. Jeon, Y. Matsuo, S. Manzhos*: Comparative Density Functional Theory – Density Functional Tight Binding Study of fullerene derivatives: effects due to fullerene size, addends, and crystallinity on bandstructure, charge transport and optical properties, Phys. Chem. Chem. Phys., 19, 28330-28343 (2017)
127. D. Koch, V. Kulish, S. Manzhos*: A first-principles study of the potassium insertion in crystalline vanadium oxide phases as possible potassium-ion battery cathode materials, MRS Commun., 7, 819-825 (2017), invited article
126. H. Padhy, Y. Chen, J. Lüder, S. R. Gajella, S. Manzhos*, P. Balaya*: Charge and discharge processes and sodium storage in disodium pyridine-2,5-dicarboxylate anode - insights from experiments and theory, Adv. Energy Mater., 8, 1701572 (2018), DOI: 10.1002/aenm.201701572
125. R. Momen , A. Azizi, L. Wang, Y. Ping, T. Xu, S. R. Kirk*, W. Li, S. Manzhos, S. Jenkins*: Exploration of the Forbidden Regions of the Ramachandran Plot (ϕ-ψ) with QTAIM, Phys. Chem. Chem. Phys., 19, 26423-26434 (2017)
124. N. Valsange, F. L. Wong, C. S. Lee, V. A. L. Roy, S. Manzhos, K. Feron, P. Sonar*, P. P. Wadgaonkar*: A new pyrene cored small organic molecule with a flexible alkyl spacer: a potential solution processable blue emitter with bright photoluminescence, New J. Chem., 41, 11383-11390 (2017)
123. D. Koch, S. Manzhos*: Addition to “On the charge state of titanium in titanium dioxide”, J. Phys. Chem. Lett., 8, 3945-3946 (2017)
122. R. Momen, A. Azizi, L. Wang, P. Yang, T. Xu, S. R. Kirk*, W. Li, S. Manzhos, S. Jenkins*: The role of weak interactions in characterizing peptide folding preferences using a QTAIM interpretation of the Ramachandran plot (ϕ-ψ), Int. J. Quantum Chem., 118, e25456 (2018)
121. J. Lueder, F. Legrain, Y. Chen, S. Manzhos*: Doping of active electrode materials for electrochemical batteries: an electronic structure perspective, MRS Commun., 7, 523-540 (2017), invited Prospective review
120. V. Kulish, D. Koch. S. Manzhos*: Ab initio study of Li, Mg and Al insertion into rutile VO2: Fast diffusion and enhanced voltages for multivalent batteries, Phys. Chem. Chem. Phys., 19, 22538-22545 (2017)
119. H. D. Pham, H. Hu, K. Feron, S. Manzhos, H. Wang, Y. M. Lam, P. Sonar*: Thienylvinylenethienyl and naphthalene core substituted with triphenylamines - highly efficient hole transporting materials and their comparative study for inverted perovskite solar cells, Solar RRL, 1, 201700105 (2017), journal cover
118. H. D. Pham, Z. Wu, K. Ono, S. Manzhos, K. Feron, N. Motta, Y. Qi*, P. Sonar*: Low cost alternative high performance hole transport material for perovskite solar cells and its comparative study with conventional SPIRO-OMeTAD, Adv. Electronic Mater., 3, 1700139 (2017)
117. V. Kulish, W. Liu, S. Manzhos*: A model for estimating chemical potentials in ternary semiconductor compounds: the case of InGaAs, MRS Adv., (2017) DOI: 10.1557/adv.2017.356
116. B. Wanga, P. Sonar*, S. Manzhos, H. Haick*: Diketopyrrolopyrrole copolymers based chemical sensors for the detection and discrimination of volatile organic compounds., Sens. Actuator B-Chem., 251, 49-56 (2017)
115. T. T. Do, H. D. Pham, S. Manzhos, J. M. Bell, P. Sonar*: Molecular engineering strategy for high efficiency fullerene-free organic solar cells using conjugated 1,8-naphthalimide and fluorenone building blocks, ACS Appl. Mater. Interfaces, 9, 16967–16976 (2017)
114. Y. Chen, J. Lueder, S. Manzhos*: Disodium pyridine dicarboxylate vs disodium terephthalate as anode materials for organic Na ion batteries: effect of molecular structure on voltage from the molecular modeling perspective, MRS Adv., (2017) DOI: 10.1557/adv.2017.323
113. J. Lueder, M. H. Cheow, S. Manzhos*: Understanding doping strategies in the design of organic electrode materials for Li and Na ion batteries: an electronic structure perspective, Phys. Chem. Chem. Phys., 19, 13195-13209 (2017)
112. P. Sonar*, S. Ponnappa, S. Armugam, S. Manzhos, H. Spratt, A. OMullane, J. Macleod: Investigation of thiophene flanked diketopyrrolopyrrole monomers with straight and branched alkyl chains and their electropolymerization study, J. Mater. Res., 32, 2707-2718 (2017)
111. D. Koch, S. Manzhos*: On the charge state of titanium in titanium dioxide, J. Phys. Chem. Lett., 8, 1593-1598 (2017), highlighted by C&EN news
110. V. Kulish, S. Manzhos*: Comparison of Li, Na, Mg and Al-ion insertion in vanadium pentoxides and vanadium dioxides, RSC Adv., 7, 18643 (2017)
109. T. T. Do, K. Rundel, Q. Gu, E. Gann, S. Manzhos, K. Feron, J. Bell, C. McNeill, P. Sonar*: 9-fluorenone and 9,10-anthraquinone potential fused aromatic building blocks to synthesize electron acceptors for organic solar cells, New J. Chem., 41, 2899-2909 (2017), journal cover
108. S. Song*, M. Kotobuki, Y. Chen, S. Manzhos, C. Xu, N. Hu, L. Lu: Na-rich layered Na2Ti1-xCrxO3-x/2 (x=0, 0.06): Na-ion battery cathode materials with high capacity and long cycle life, Sci. Rep., 7, 373(2017)
107. S. Arabnejad, K. Yamashita, S. Manzhos*: Defects in crystalline PVDF: a Density Functional Theory – Density Functional Tight Binding study, Phys. Chem. Chem. Phys., 19, 7560-7567 (2017)
106. V. V. Kulish, D. Koch, S. Manzhos*: Aluminium and magnesium insertion in sulfur-based spinels: a first-principles study, Phys. Chem. Chem. Phys., 19, 6076-6081 (2017)
105. P. Sonar*, S. Ponnappa, S. Armugam, H. Spratt, S. Manzhos, A. OMullane, G. Ayoko: A comparative study of electrochemical, optical properties and electropolymerization behaviour of thiophene and furan substituted diketopyrrolopyrrole, J. Mater. Res., 32, 810-821 (2017)
104. F. Legrain, S. Manzhos*: A first-principles comparative study of lithium, sodium, and magnesium storage in pure and gallium-doped germanium: competition between interstitial and substitutional sites, J. Chem. Phys., 146, 034706 (2017)
103. W. Liu, Mahasin Alam Sk, S. Manzhos*, I. Martin-Bragado*, F. Benistant, S. A. Cheong: Grown-in beryllium diffusion in indium gallium arsenide: An ab initio, continuum theory and kinetic Monte Carlo study, Acta Materialia, 125, 455-464 (2017)
102. E. Castro, G. Avila*, S. Manzhos*, J. Agarwal, H. F. Schaefer III, T. Carrington*: Applying a Smolyak collocation method to Cl2CO, Mol. Phys., 115, 1775-1785 (2017)
101. S. Manzhos*, T. Carrington*: Using an internal coordinate basis and a space-fixed Cartesian coordinate kinetic energy operator to compute a vibrational spectrum with Gaussian basis functions and rectangular collocation, J. Chem. Phys., 145, 224110 (2016)
100. Y. Chen, S. Manzhos*: Voltage and capacity control of polyaniline based organic cathodes: an ab initio study, J. Power Sources, 336, 126-131 (2016)
99. P. Sonar*, J. Chang, J. H. Kim, K.-H. Ong, E. Gann, S. Manzhos, J. Wu, C. McNeill: High mobility ambipolar organic thin film transistor processed from a non-chlorinated solvent, ACS Appl. Mater. Interfaces, 8(37), 24325–24330 (2016)
98. S. Manzhos*, K. Kotsis: Computational study of interfacial charge transfer complexes of 2-anthroic acid adsorbed on a titania nanocluster for direct injection solar cells, Chem. Phys. Lett., 660, 69-75 (2016)
97. Sk Mahasin Alam, Y. Chen, S. Manzhos*: Orbital order switching in molecular calculations using GGA functionals: qualitative errors in materials modeling for electrochemical power sources and how to fix them, Chem. Phys. Lett., 659, 270-276 (2016)
96. S. Arabnejad, S. Manzhos*, V. P. W. Shim: Molecular dynamics study of the effect of surface treatment on the mode I debonding of interface between silica and nylon6, MRS Adv., (2016) DOI: 10.1557/adv.2016.530
95. W. Li, K. Kotsis, S. Manzhos*: Comparative Density Functional Theory and Density Functional Tight Binding study of arginine and arginine-rich cell penetrating peptide TAT adsorption on anatase TiO2, Phys. Chem. Chem. Phys., 18, 19902-19917 (2016)
94. F. Legrain, K. Kotsis, S. Manzhos*: Mg and K insertion in glassy amorphous carbon vs graphite as potential anode materials: an ab initio study, MRS Adv., (2016) DOI: 10.1557/adv.2016.507
93. Sk Mahasin Alam, S. Manzhos*: Sodium interaction with disodium terephthalate molecule: an ab initio study, MRS Adv., (2016) DOI: 10.1557/adv.2016.452
92. Sk Mahasin Alam, S. Manzhos*: Exploring the sodium storage mechanism in disodium terephthalate as anode for organic battery using density-functional theory calculations, J. Power Sources, 324, 572-581 (2016)
91. F. Legrain, S. Manzhos*: Understanding the difference in cohesive energies between alpha and beta tin in DFT calculations, AIP Adv., 6, 045116 (2016)
90. S, Manzhos*, K. Kotsis: Adsorption and light absorption properties of 2-anthroic acid on titania: a Density Functional Theory – Time-Dependent Density Functional Theory study, MRS Adv. (2016) DOI: 10.1557/adv.2016.242
89. H. Tan, W. Luo, L. Wei, B. Chen, W. Li, L. Xiao*, S. Manzhos*, Z. Liu*, S. Liang: Quantifying the distribution of the stoichiometric composition of anti-cancer peptide Lycosin-I on lipid membrane with single molecule spectroscopy, J. Phys. Chem. B, 120, 3081-3088 (2016)
88. Y. Chen, S. Manzhos*: Comparative computational study of lithium and sodium insertion in van der Waals and covalent tetracyanoethylene (TCNE) -based crystals as promising materials for organic lithium and sodium ion batteries, Phys. Chem. Chem. Phys., 18, 8874-8880 (2016)
87. J. K. Salunke, F. L. Wong, K. Feron, S. Manzhos, M. F. Lo, D. Shinde, A. Patil, C. S. Lee, V. A. L. Roy, P. Sonar*, P. P. Wadgaonkar: Phenothiazine and carbazole substituted pyrene based electroluminescent organic semiconductors for OLED devices, J. Mater. Chem. C, 4, 1009-1018 (2016)
86. Y. Chen, S. Manzhos*: A computational study of lithium interaction with tetracyanoethylene (TCNE) and tetracyaniquinodimethane (TCNQ) molecules, Phys. Chem. Chem. Phys., 18, 1470-1477 (2016)
85. F. Legrain, O. I. Malyi, C. Persson, S. Manzhos*: Comparison of alpha and beta tin for lithium, sodium, and magnesium storage: an ab initio study including phonon contributions, J. Chem. Phys., 143, 204701 (2015)
84. S. Manzhos*: Comparative Density Functional Theory and Density Functional Tight Binding study of 2-anthroic acid on TiO2, Chem. Phys. Lett., 643, 16-20 (2016)
83. N. Capel, D. Bharania, S. Manzhos*: A comparative Density Functional Theory and Density Functional Tight Binding study of phases of nitrogen including a high energy density material N8, Computation, 3(4), 574-585 (2015)
82. S. Arabnejad, S. Manzhos*: Defects in alpha and gamma crystalline nylon6: a computational study, AIP Adv., 5, 107123 (2015)
81. S. Manzhos*, T. Carrington, L. Laverdure, N. Mosey: Computing the anharmonic vibrational spectrum of UF6 in 15 dimensions with an optimized basis set and rectangular collocation, J. Phys. Chem A, 119(36), 9557-9567 (2015). Invited article for the special issue “Spectroscopy and Dynamics of Medium-Sized Molecules and Clusters: Theory, Experiment, and Applications”.
80. F. Legrain, J. Sottmann, K. Kotsis, S. Gorantla, S. Sartori, S. Manzhos*: Amorphous (glassy) carbon a promising material for sodium ion battery anodes: a combined first principles and experimental study, J. Phys. Chem. C 119(24), 13496–13501 (2015)
79. Y. Chen, S. Manzhos*: Li and Na Storage on TCNE: A Computational Study, In Proceedings of the 14th Asian Conference on Solid State Ionics (ACSSI 2014), Eds. S. Adams and J. Kawamura, Research Publishing, Singapore, 2015, pp. 374-380, doi: 10.3850/978-981-09-1137-9_197
78. F. Legrain, O. I. Malyi, S. Manzhos*: Comparative ab Initio Study of Lithium Storage in Amorphous and Crystalline TiO2, In Proceedings of the 14th Asian Conference on Solid State Ionics (ACSSI 2014), Eds. S. Adams and J. Kawamura, Research Publishing, Singapore, 2015, pp. 85-92, doi: 10.3850/978-981-09-1137-9_054
77. Y. Chen, S. Manzhos*: Lithium and sodium storage on tetracyanoethylene (TCNE) and TCNE-(doped)-graphene complexes: a computational study, Mater. Chem. Phys., 156, 180-187 (2015)
76. S. Manzhos*, G. Giorgi, K. Yamashita: A Density Functional Tight Binding study of acetic acid adsorption on crystalline and amorphous surfaces of titania, Molecules, 20, 3371-3388 (2015)
75. W. H. Tu, Y. Y. Tan, O. Rege, S. Manzhos*: Computational design of small phenothiazine dyes for dye-sensitized solar cells by functionalizations affecting the thiophene unit, J. Mol. Model., 21, 67 (2015)
74. M. Majumder, S. E. Hegger, R. Dawes, S. Manzhos, X.-G. Wang, T. Carrington* Jr., J. Li, H. Guo: Explicitly-correlated MRCI-F12 potential energy surfaces for methane fit with several permutation invariant schemes and full-dimensional vibrational calculations, Mol. Phys., 113(13-14), 1823-1833 (2015). Invited article for the Special Issue in Honour of Nicholas C. Handy.
73. O. I. Malyi*, K. Sopiha, V. Kulish, T. L. Tan, S. Manzhos*, C. Persson: A computational study of Na behavior on graphene, Appl. Surf. Sci., 333, 235-243 (2015)
72. F. Legrain, S. Manzhos*: Highly accurate local pseudopotentials of Li, Na, and Mg for Orbital Free Density Functional Theory, Chem. Phys. Lett., 622, 99-103 (2015)
71. F. Legrain, O. I. Malyi, S. Manzhos*: Insertion energetics of lithium, sodium, and magnesium in crystalline and amorphous titanium dioxide: a comparative first-principles study, J. Power Sources, 278, 197-202 (2015)
70. S. Arabnejad, S. Manzhos*, C. He, V. P. W. Shim: Shear-induced conformation change in α-crystalline Nylon6, Appl. Phys. Lett., 105, 221910 (2014)
69. Y.-W. Koh, K. Westerman, S. Manzhos*: A computational study of adsorption and vibrations of UF6 on graphene derivatives: conditions for 2D enrichment, Carbon, 81, 800-806 (2015)
68. F. Legrain, S. Manzhos*: Aluminum doping improves the energetics of lithium, sodium, and magnesium storage in silicon: a first-principles study, J. Power Sources, 274, 65-70 (2015)
67. S. Manzhos*, R. Dawes, T. Carrington*: Neural network based approaches for building high dimensional and quantum dynamics-friendly potential energy surfaces, Int. J. Quantum Chem., 115(16), 1012-1020 (2015). Invited review.
66. Y. Chen, S. Manzhos*: Li Storage on TCNE and TCNE-(doped)-graphene complexes: a computational study, MRS Proc., 1679 (2014) DOI: 10.1557/opl.2014.849
65. F. Legrain, O. I. Malyi, S. Manzhos*: A comparative computational study of Li, Na, and Mg insertion in α-Sn, MRS Proc., 1678 (2014) DOI: 10.1557/opl.2014.743
64. W.-H. Tu, Y.-Y. Tan, S. Manzhos*: Achieving improved solar absorbance of small organic dyes featuring quinoidized five-membered heterocycles, MRS Proc., 1667 (2014) DOI: 10.1557/opl.2014.736
63. Y.-W.Koh, K. Westerman, S. Manzhos*: Adsorption of UF6 on graphene derivatives: a computational study of conditions for 2D enrichment, MRS Proc., 1683 (2014) DOI: 10.1557/opl.2014.481
62. F. Legrain, O. Malyi, S. Manzhos*: Comparative computational study of the energetics of Li, Na, and Mg storage in amorphous and crystalline silicon, Comput. Mater. Sci., 94, 214-217 (2014)
61. T.-L. Tan, O. Malyi, S. Manzhos*: A comparative computational study of the diffusion of Na and Li Atoms in Sn(111) nanosheets, Solid State Ionics, 268, 273-276 (2014)
60. S. Manzhos, T. Carrington: Representing potential energy surfaces with neural networks and high dimensional model representations, AIP Conf. Proc. 1504, 785-787 (2012)
59. P. Sonar*, T. J. Ha, Y. Seong, S. Yeh, C. T. Chen, S. Manzhos, A. Dodabalapur*: A study of diphenylfumaronitrile and furan-substituted diketopyrrolopyrrole alternating copolymer and its thin-film transistors, Macromol. Chem. Phys., 215(8), 725-732 (2014)
58. V. V. Kulish*, O. I. Malyi, M.-F. Ng, Z. Chen, S. Manzhos*, P. Wu*: Controlling Na diffusion by rational design of Si-based layered architectures, Phys. Chem. Chem. Phys., 16(9), 4260-4267 (2014)
57. Y. Y. Tan, W. H. Tu, S. Manzhos*: Computational design of small organic dyes with strong visible absorption by controlled quinoidization of the thiophene unit, Chem. Phys. Lett., 593, 14-19 (2014)
56. F. Legrain, O. I. Malyi, S. Manzhos*: Comparative computational study of the diffusion of Li, Na, and Mg in silicon including the effect of vibrations, Solid State Ionics, 253, 157-163 (2013)
55. A. Carvalho, M. J. Rayson, P. R. Briddon, S. Manzhos*: Effect of the adsorption of ethylene carbonate on Si surfaces on the Li insertion behavior, Chem. Phys. Lett., 585, 157-161 (2013)
54. P. Sonar*, S. P. Singh, E. L. Williams, S. Manzhos, A. Dodabalapur*: A benzothiadiazole end capped donor-acceptor based small molecule for organic electronics, Phys. Chem. Chem. Phys., 15(40), 17064-17069 (2013)
53. F. Legrain, O. I. Malyi, T. L. Tan, S. Manzhos*: Computational study of Mg insertion into amorphous silicon: advantageous energetics over crystalline silicon for Mg storage, MRS Proc. 1540 (2013) DOI: 10.1557/opl.2013.1036
52. S. Manzhos*, M. Chan, T. Carrington: Favorable dimensionality scaling of rectangular collocation with adaptable basis functions up to 7 dimensions, J. Chem. Phys. 139(5), 051101 (2013) Top 20 Most Read in August 2013
51. S. Manzhos*: On the choice of the discount rate and the role of financial variables and physical parameters in estimating the levelized cost of energy, International Journal of Financial Studies, 1(3), 54-61 (2013)
50. Y. W. Koh, S. Manzhos*: Curvature drastically changes diffusion properties of Li and Na on graphene, MRS Commun., 3, 171-175 (2013) Highlighted by Materials360
49. S. Manzhos*, G. Giorgi: Bridging the fields of solar cell and battery research to develop high-performance anodes for photoelectrochemical cells and metal ion batteries, Challenges, 4(1), 116-135 (2013)
48. T. L. Tan, O. I. Malyi, F. Legrain, S. Manzhos*: Role of inter-dopant interactions on the diffusion of Li and Na atoms in bulk Si anodes, MRS Proc. 1541 (2013), DOI: 10.1557/opl.2013.756
47. O. I. Malyi*, T. L. Tan, S. Manzhos*: A computational study of the insertion of Li, Na, and Mg atoms into Si(111) nanosheets, Nano Energy, 2(6), 1149-1157 (2013)
46. S. Manzhos*: Effects of nuclear vibrations on the energetics of polythiophene: quantized energy molecular dynamics, Aust. J. Chem., 66(9), 1021-1028 (2013)
45. S. Manzhos*, H. Segawa, K. Yamashita: Effect of isotopic substitution on elementary processes in dye-sensitized solar cells: deuterated amino-phenyl acid dyes on TiO2, Computation, 1(1), 1-15 (2013). Feature article.
44. M. Chan, T. Carrington, S. Manzhos*: Anharmonic vibrations of the carboxyl group in acetic acid on TiO2: implications for adsorption mode assignment in dye-sensitized solar cells, Phys. Chem. Chem. Phys., 15(25), 10028-10034 (2013). Invited article for the special issue “Spectroscopy and dynamics of medium-sized molecules and clusters”.
43. O. I. Malyi*, T. L. Tan, S. Manzhos*: In search of high performance anode materials for Mg batteries: computational studies of Mg in Ge, Si, and Sn, J. Power Sources 233, 341-345 (2013)
42. S. Manzhos*: Computational design of new organics dyes with improved solar absorbance for dye-sensitized solar cells, MRS Commun. 3(1), 37-39 (2013)
41. O. I. Malyi*, T. L. Tan, S. Manzhos*: A comparative computational study of structures, diffusion, and dopant interactions between Li and Na insertion into Si, Appl. Phys. Express 6(2), 027301 (2013)
40. S. Manzhos*, H. Segawa, K. Yamashita: Effect of nuclear vibrations, temperature, co-adsorbed water, and dye orientation on light absorption, charge injection and recombination conditions in organic dyes on TiO2, Phys. Chem. Chem. Phys. 15(4), 1141-1147 (2013)
39. M. Chan, K. Yamashita, T. Carrington, S. Manzhos*: Towards accurate spectroscopic identification of species at catalytic surfaces: anharmonic vibrations of formate on AuPt, MRS Proceedings 1484 (2012), DOI: 10.1557/opl.2012.1623
38. S. Manzhos*, M. Komatsu, J. Nakazaki, H. Segawa, K. Yamashita: Theoretical analysis of the solvatochromism of organic dyes differing by the conjugation sequence, J. Photonics Energy 2, 028001 (2012)
37. S. Manzhos*, H. Segawa, K. Yamashita*: Effect of nuclear vibrations, temperature, and orientation on injection and recombination conditions in amino-phenyl acid dyes on TiO2, Proc. SPIE 8438, 843814 (2012)
36. M. Chan, S. Manzhos*, T. Carrington, K. Yamashita: Parameterized bases for calculating vibrational spectra directly from ab initio data using rectangular collocation. J. Chem. Theory Comput., 8(6), 2053-2061 (2012)
35. S. Manzhos*, J. Nakazaki, H. Segawa, K. Yamashita*: Theoretical analysis of the absorption spectra of organic dyes differing by the conjugation sequence: illusion of negative solvatochromism, Proc. SPIE 8435, 84351K (2012)
34. S. Manzhos*, J. Fujisawa, H. Segawa, K. Yamashita: Isotopic substitution as a strategy to control non-adiabatic dynamics in photoelectrochemical cells: surface complexes between TiO2 and dicyanomethylene compounds, Jpn. J. Appl. Phys., 51(10), 10NE03 (2012)
33. S. Manzhos*, H. Segawa, K. Yamashita: Computational dye design by changing the conjugation order: failure of LR-TDDFT to predict relative excitation energies in organic dyes differing by the position of the methine unit, Chem. Phys. Lett., 527, 51-56 (2012)
32. S. Manzhos*, H. Segawa, K. Yamashita*: The effect of ligand substitution and water co-adsorption on the adsorption dynamics and energy level matching of amino-phenyl acid dyes on TiO2, Phys. Chem. Chem. Phys., 14(5), 1749-1755 (2012)
31. S. Manzhos*, R. Jono, K. Yamashita*, J. Fujisawa, M. Nagata, H. Segawa: Study of interfacial charge transfer bands and electron recombination in the surface complexes of TCNE, TCNQ, and TCNAQ with TiO2, J. Phys. Chem. C 115 (43), 21487–21493 (2011)
30. S. Manzhos*, M. Komatsu, J. Nakazaki, H. Segawa, K. Yamashita*: Theoretical study of the origin of the large difference in the visible absorption spectra of organic dyes containing a thienylmethine unit and differing by the methine unit position, Proc. SPIE 8109, 810908 (2011), invited article
29. S. Manzhos*, T. Carrington*, K. Yamashita*: Non-spectral methods for solving the Schroedinger equation for electronic and vibrational problems, J. Phys. Chem. Lett., invited Perspective, 2(17), 2193-2199 (2011)
28. S. Manzhos*, K. Yamashita: Dynamics on ab-initio potential energy surfaces for predictions of reactivity: a general method. In Advances in Applied Surface Engineering (eds. S. Kumar Thakur and R. Gopal Krishnan), Research Publishing Services, Singapore, 2011
27. S. Manzhos*, K. Yamashita, T. Carrington*: On the advantages of a rectangular matrix collocation equation for computing vibrational spectra from small basis sets, Chem. Phys. Lett. 511(4-6), 434-439 (2011)
26. S. Manzhos, T. Carrington, K. Yamashita: Solving the vibrational Schrödinger equation without a potential energy surface using a combined neural network collocation approach. In Computer Physics, pp.237-266, Nova Publishers, 2011
25. S. Manzhos*, H. Segawa, K. Yamashita*: A model for recombination in Type II dye-sensitized solar cells: catechol-thiophene dyes, Chem. Phys. Lett., 504(4-6), 230-235 (2011)
24. S. Manzhos*, T. Carrington, K. Yamashita: Calculating anharmonic vibrational frequencies of molecules adsorbed on surfaces directly from ab initio energies with a molecule-independent method: H2O on Pt(111), Surf. Sci., 605(5-6), 616-622 (2011)
23. S. Manzhos*, H. Segawa, K. Yamashita: Derivative coupling constants of NK1, NK7 dyes and their relation to excited state dynamics in solar cell applications, Chem. Phys. Lett., 501(4-6), 580-586 (2011)
22. S. Manzhos*, K. Yamashita*, T. Carrington*: Extracting functional dependence from sparse data using dimensionality reduction: Application to potential energy surface construction. In Coping with Complexity: Model Reduction and Data Analysis, series Lecture Notes in Computational Science and Engineering, vol. 75, pp. 133-149, Springer Verlag, 2011
21. S. Manzhos*, K. Nakai, K. Yamashita: Three-body interactions in clusters CO-(pH2)n, Chem. Phys. Lett. 493(4-6), 229-233 (2010)
20. S. Manzhos*, K. Yamashita: A model for the dissociative adsorption of N2O on Cu(100) using a continuous potential energy surface, Surf. Sci. 604(5-6), 555-561 (2010)
19. S. Manzhos*, K. Yamashita*, T. Carrington*: Fitting sparse multidimensional data with low-dimensional terms, Comput. Phys. Comm., 180(10), 2002-2012 (2009)
18. S. Manzhos*, K. Yamashita*, T. Carrington*: Using a neural network based method to solve the vibrational Schrödinger equation for H2O, Chem. Phys. Lett., 474(1-3), 217-221 (2009)
17. S. Manzhos, T. Carrington*: An improved neural network method for solving the Schrödinger equation, Can. J. Chem., invited article for Tom Ziegler special issue, 87(7), 864-871 (2009)
16. S. Manzhos*, T. Carrington*: Using neural networks, optimized coordinates and high dimensional model representations to obtain a vinyl bromide potential surface, J. Chem. Phys. 129(22), 224104 (2008)
15. S. Manzhos*, T. Carrington*: Using redundant coordinates to represent potential energy surfaces with lower-dimensional functions, J. Chem. Phys. 127(1), 014103 (2007)
14. S. Manzhos*, T. Carrington*: Using neural networks to represent potential surfaces as sums of products, J. Chem. Phys. 125(19), 194105 (2006)
13. S. Manzhos*, T. Carrington*: A Random-Sampling High Dimensional Model Representation neural network for building potential energy surfaces, J. Chem. Phys. 125(8), 084109 (2006)
12. S. Manzhos, X.-G. Wang, R. Dawes, and T. Carrington*: A nested molecule-independent neural network approach for high-quality potential fits, J. Phys. Chem. A, invited article for special issue “John C. Light Festschrift” 110(16), 5295 – 5304 (2006).
11. S. Manzhos, J. Underwood*, C. Romanescu, and H.-P. Loock: Two photon state selection and angular momentum polarization probed by velocity map imaging: application to H atom photofragment angular distributions from the photodissociation of two-photon state selected HCl and HBr, J. Chem. Phys., 121(23), 11802-11809 (2004).
10. S. Manzhos, H.-P. Loock*: Photofragment image analysis via pattern recognition, Rev. Sci. Instrum., 75(7), 2435-2445 (2004)
9. S. Manzhos*: Possibilities of signal masking using chaotic synchronisation of modified Rossler oscillators, Bulletin of Kharkov National University, No. 622, 73-81 (2004, in Russian)
8. M. Jakubinek, Z. Tong, S. Manzhos, Hans-Peter Loock*: Configuration of ring-down spectrometers for maximum sensitivity, Can. J. Chem., 82(6), 873-879 (2004)
7. C. Romanescu, S. Manzhos, D. Boldovsky, J. Clarke, and H.-P. Loock*: Superexcited state reconstruction of HCl using photoelectron and photoion imaging, J. Chem. Phys., 120(2), 767-777 (2004)
6. S. Manzhos, H.-P. Loock*: Photofragment image analysis using the Onion-Peeling algorithm. Comp. Phys. Com., 154(1), 76-87 (2003)
5. R. J. Le Roy*, G. T. Kraemer, and S. Manzhos: 1 potential, 2 potentials, 3 potentials – 4: untangling the UV photodissociation spectra of HI and DI, J. Chem. Phys., 117(20), 9353 -9369(2002).
4. S. Manzhos, H.-P. Loock*, B. L. G. Bakker, and D. H. Parker: Photodissociation of hydrogen iodide in the A-band region 272 nm - 288 nm, J. Chem. Phys., 117(20), 9347-9352 (2002).
3. S. Manzhos, K. Schünemann, S. Sosnitsky, and D. Vavriv*: Clinotron: A promising source for THz regions. Radio Physics and Radio Astronomy, 5(3), 265-273 (2000).
2. S. Manzhos, K. Schünemann, and D. Vavriv:: Plasma frequency reduction coefficients for an electron beam scattering on metallic surfaces. Radio Physics and Radio Astronomy, 4(1), 5-12 (1999).
1. S. V. Manzhos*: Synchronization of Modified Rossler Oscillators in a Chaotic Regime for Hidden Information Transmission, Telecommunications and Radio Engineering 53(4-5), 61-67 (1999) (Original: S. Manzhos: Chaotic synchronization of modified Rossler oscillators for secure communications, Bulletin of Kharkov National University, Radiophysics series, 101 (1999), in Russian).
Book Review
H.-P. Loock*, S. Manzhos: Light-matter interaction: Fundamentals and applications. By Weiner and Ho, Wiley-Interscience, Int. J. Quantum Chem., 98(6), 528-529 (2004).
Other publications
12. S Manzhos*, S Tsuda, H Lee, M Ihara: Hybrid models combining neural networks (NN), Gaussian process regressions (GPR), and high-dimensional model representations (HDMR) for more powerful machine learning. 人工知能学会全国大会論文集 第 37 回 (Proceedings of the 37th Annual Meeting of the Japanese Society for Artificial Intelligence) (2023), 2U4IS2c01-2U4IS2c01, https://doi.org/10.11517/pjsai.JSAI2023.0_2U4IS2c01
11. S. Manzhos*: Effects of aggregate state in atomistic modeling of materials for electrochemical energy conversion and storage devices (Conference Presentation), Proc. SPIE 11387, Energy Harvesting and Storage: Materials, Devices, and Applications X, 1138703 (Presented at SPIE Defense + Commercial Sensing: April 27, 2020, DOI: 10.1117/12.2556164.6151373892001.
10. D. Koch, S. Manzhos*: The Efficacy of Fiction or More on the Charge State of Ti in TiO2 and Formal Oxidation States. https://arxiv.org/abs/1707.06851
9. S. Manzhos: Electrochemical batteries: where mechanics goes quantum, Engineering Research Newsletter (ERN), 02.2014
8. S. Manzhos: Review of “AgNP stability in humic solutions”, Can. Y. Sci. J. no. 1, 10 (2013)
7. S. Manzhos: Reflections of a computer poet on American social dynamics (or how this makes sense), Advances in Literary Study, 2(2), 47-57 (2014)
6. S. Manzhos, R. Jono, K. Yamashita, J. Fujisawa, M. Nagata, H. Segawa: A study of interfacial charge transfer bands and electron recombination in surface complexes of TCNE, TCNQ, and TCNAQ with TiO2. Technical digest of the 21st International Photovoltaic Science and Engineering Conference, November 28 - December 2, 2011, Fukuoka, Japan
5. S. Manzhos: Review of "Finding correlations by comparing clusters to gas levels of 2D - circulating fluidized beds", Can. Y. Sci. J. no. 3, 40 (2011)
4. T. Carrington, S. Manzhos: Some new neural network based tools for fitting potential surfaces, In Molecular Potential Energy Surfaces in Many Dimensions, Eds. M. M. Law and A. Ernesti, CCP6, Daresbury, Warrington, UK (2009)
3. S. Manzhos: Theory or practice? Can. Y. Sci. J. no. 2, 45-47 (2009)
2. S. Manzhos: Review of "Molecular ions on the edge of stability", Can. Y. Sci. J. no. 2, 21 (2009)
1. S. Manzhos: Review of "Inhibitory effects of Colicin on the growth of gastric pathogen Halicobacter Pylori", Can. Y. Sci. J. no. 1, 9 (2009)
6. INVITED TALKS, LECTURES, AND SEMINARS
6. INVITED TALKS, LECTURES, AND SEMINARS
137. Data-driven kinetic energy functionals for orbital-free DFT: from ML to formulae. At HANAMI Second High Level Symposium (HLS2), Chamonix, France, December 9-11, 2025.
136. Electron density based methods for large-scale atomistic modeling of materials. Seminar at the College of Chemistry and Chemical Engineering, Hunan Normal University, Changsha, Hunan, China, November 3, 2025.
135. Efficient machine learning from sparse data in high-D feature spaces. At The 4th National Symposium on Machine Learning Applications in Nuclear Physics and Nuclear Data (第四届全国核物理及核数据中的机器学习应用研讨会), Hengyang, China, October 30 – November 3, 2025.
134. Computational techniques for modeling and discovery of functional ceramics: from large scale atomistic models to informatics. At the Institute of Science Tokyo, Dalian University of Technology, Tsinghua University Joint Workshop on Advance Materials and Chemical Technology, Tokyo, Japan, October 24-26, 2025.
133. Towards more realistic modeling of microstructured ceramics for solid state ionics and beyond: from large-scale MD to large-scale electronic structure. At International Workshop on Multiscale, Multiphysics, and Multidisciplinary Research on Materials and Structures (m3MS), Singapore, September 24-26, 2025.
132. Large-scale density functional based methods for atomistic modeling of large scale phenomena. Seminar at the Department of Mechanical Engineering, National University of Singapore, Singapore, September 22, 2025.
131. Methods for faster, interpretable and portable machine learning. Seminar at the Department of Chemical Engineering, Chulalongkorn University, Bangkok, Thailand, September 19, 2025.
130. Atomistic modeling for batteries and fuel cells. Guest lecture at King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand, September 17, 2025.
129. Combining the power of machine learning and portability and interpretability of analytic formulas when constructing kinetic energy functionals. At New Generation Nuclear Density Functionals 2025, Beijing, China, June 26-29, 2025.
128. Towards faster, insightful, interpretable and portable machine learning models: from dedicated circuits to ML-guided analytics. Seminar at Materials Genome Institute, Shanghai University, Shanghai, China, June 23, 2025.
127. 一般的な手法を超える洞察的な機械学習. At 新化学技術推進協会 (Japan Association for Chemical Innovation, JACI), Hakone, Japan, June 13, 2025. (Insightful machine learning beyond off-the-shelf methods)
126. 機械学習による強化した大規模な電子密度ベースの第一原理計算：大規模現象から材料情報学かけて計算化学の将来へ. At 新化学技術推進協会 (Japan Association for Chemical Innovation, JACI), Tokyo, Japan, May 13, 2025. (Machine-learning enhanced large-scale density functional based methods: from large scale phenomena to materials informatics)
125. Large-scale electronic structure materials modeling with the help of machine learning-enhanced DFTB and OF-DFT. At the 3rd CEMDI-PAIMS Symposium, Kyushu University, Fukuoka, Japan, April 23-25, 2025.
124. Materials informatics with speed and insight. Seminar at Singapore University of Technology and Design, Singapore, March 12, 2025.
123. Machine learning for large(r) scale materials modeling: simple's the best. At International Workshop on Massively Parallel Programming for Quantum Chemistry and Physics (MPQCP 2025), RIKEN Center for Computational Science, Kobe, Japan, January 21-22, 2025.
122. Modeling of microstructured ceramics – from large-scale molecule dynamics to large-scale electronic structure. Seminar at the Department of Mechanical Engineering, National University of Singapore, Singapore, January 9, 2025.
121. Large(r) scale electronic structure calculations for materials modeling. Seminar at the Department of Chemistry, Mahidol University, Bangkok, Thailand, September 25, 2024.
120. Large(r) scale electronic structure calculations for materials modeling. Seminar at the Department of Tool and Materials Engineering, King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand, September 25, 2024.
119. Kinetic energy density-based machine learning models of kinetic energy using gradient expansion based features. At Towards Routine Orbital-free Large-Scale Quantum-Mechanical Modelling of Materials, Institute for Advanced Studies in Mathematics (IASM), Zhejiang University, Hangzhou, China, September 8-13, 2024.
118. Materials Informatics with Hybrid Machine Learning Methods. Seminar at The Zhejiang University-University of Illinois Urbana-Champaign Institute, Zhejiang University, Hangzhou, China, September 11, 2024.
117. At the intersection of material informatics and machine learning method development. Seminar at the Materials Genomics Institute (MGI), Shanghai University, Shanghai, China, September 6, 2024.
116. Advancing Orbital-Free DFT and DFTB for large-scale ab initio materials modeling with machine learning. Seminar at the Department of Physics, Shanghai University, Shanghai, China, September 5, 2024.
115. Additive kernel based methods for stable machine learning from sparse data: from materials informatics to orbital-free DFT. At 14th International Conference on Ceramic Materials and Components for Energy and Environmental Systems, Budapest, Hungary, August 18-22, 2024.
114. Machine learning with kernel methods in high dimensional spaces. At the Department of Chemistry, Queen’s University, Kingston ON, Canada, June 3, 2024.
113. Hybrid approaches to machine learning from small datasets for applications from materials informatics to large-scale DFT. At the 2nd Annual CEMDI Symposium, Montreal QC. Canada, May 27-29, 2024.
112. Reliable machine learning from sparse data in high dimension with additive kernel based methods. At Chemical Compound Space Conference 2024 (CCSC 2024), Heidelberg, Germany, May 21-24, 2024.
111. Insightful machine learning beyond traditional neural networks and kernel regression. Seminar at the Department of Tool and Materials Engineering, King Mongkut’s University of Technology Thonburi (KMUTT), Thailand, March 13, 2024.
110. Beyond silicon solar cells. Guest lecture at King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand, March 11, 2024.
109. Beyond neural networks and kernel regression: hybrid methods for machine learning from sparse data in high-dimensional spaces. Seminar at the Department of Chemical Engineering, National Taiwan University, Taipei, Taiwan, February 27, 2024.
108. Machine learning for advancing large scale ab initio materials modeling. Seminar at the Center for Theoretical and Computational Physics, National Sun Yat-sen University, Kaohsiung, Taiwan, February 23, 2024.
107. Machine learning beyond off-the-shelf methods. Seminar at the Department of Materials and Optoelectronic Science, National Sun Yat-sen University, Kaohsiung, Taiwan, February 21, 2024.
106. Machine learning in computational chemistry beyond off-the-shelf methods: how to cut the cost, handle overfitting, and obtain elements of insights. At International Workshop on Massively Parallel Programming for Quantum Chemistry and Physics (MPQCP 2024), Wako, Saitama, Japan, January 9-10, 2024.
105. Machine learning beyond plain neural networks and kernel methods: from getting rid of non-linear optimization and overfitting to building many-body representations, At Hierarchical Structure and Machine Learning (HISML2023), Tokyo, Japan, October 2-13, 2023.
104. Materials informatics for materials for new energy. Guest lecture at King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand, September 19, 2023.
103. Metal ion batteries and elements of solid state ionics. Guest lecture at King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand, September 19, 2023.
102. Neural networks with additive Gaussian processes based neuron activation functions: combining high expressive power of a NN with robustness of a linear regression. Seminar at the Department of Mechanical Engineering, National University of Singapore, Singapore, July 3, 2023.
101. Machine learning in computational chemistry: the connections. At the Department of Chemistry, University of Perugia, Italy, May 18, 2023
100. Computation-assisted and -guided development of renewable energy technologies. At King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand, March 14, 2023.
99. Beyond silicon solar cells. At King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand, March 14, 2023.
98. Reversible electrochemical lithiation as a way to facilitate the machining of ceramics: a computational study. At the Asian Conference on Electrochemical Power Sources 11 (ACEPS’11), Singapore, December 11-14, 2022.
97. Machine learning outside of comfort zone: interplay between (non)linearity, basis sets, and dimensionality. Seminar at the Department of Mechanical Engineering, National University of Singapore, Singapore, December 6, 2022.
96. Advanced machine learning for renewable energy technologies from material to system level. Guest lecture at the School of Engineering, King Mongkut's Institute of Technology Ladkrabang, Thailand, November 15, 2022.
95. Machine learning of potentials and functionals from sparse data and how to get insight with a black box method. At the 29th Canadian Symposium on Theoretical and Computational Chemistry (CSTCC), Kelowna BC, Canada, June 27 - July 1, 2022.
94. Machine learning in computational chemistry: the connections. Seminar at the Institut National de la Recherche scientifique, Centre Energie Matériaux Télécommunications, Varennes QC, Canada, June 20, 2022.
93. Machine learning of interatomic potentials and density functionals from sparse data and how to get insight with a black box method. Seminar at Sungkyunkwan University, April 7, 2022.
92. Non-parametric machine learning for orbital-free DFT simulations. At the 46th International Conference and Exposition on Advanced Ceramics and Composites (ICACC2022), Daytona Beach FL, USA (Virtual), January 24 - 28, 2022.
91. Enhancing the bond valence representation for prescreening of solid state ionic conductors. At the Electronic Materials and Applications 2022 (EMA 2022), (Virtual), January 19-21, 2022
90. Machine learning for large-scale ab initio simulations with orbital-free DFT. At the 31st Annual Meeting of MRS-J, Yokohama, Japan, December 13-15, 2021.
89. Insight with a black box method beyond automatic relevance determination with the help of high-dimensional model representation. At the International Symposium on Machine Learning in Quantum Chemistry (SMLQC), November 12-14, 2021, Xiamen, China.
88. Machine learning for orbital-free DFT, At the EU-Japan Workshop on HPC-Based Material Sciences, November 9–10, 2021.
87. Rectangular collocation as a promising approach for accurate computational vibrational spectroscopy of molecules on surfaces. At the CECAM workshop Challenges in reaction dynamics of gas-surface interactions and methodological advances in dissipative and non-adiabatic processes, Toulouse, France, September 27-30, 2021 .
86. Machine learning in quantum chemistry: from black box to insight. At the 104th Canadian Chemistry Conference and Exhibition, virtual, August 13-20,2021.
85. Machine learning of kinetic energy functionals for orbital-free DFT: the choice of variables is key. At the 8th International Congress on Ceramics (ICC8), Busan, Korea, April 25-30, 2021, Busan, Korea.
84. Calculs de spectres. At the Atelier ANR-NMC, Grenoble, France, June 1-4, 2021.
83. Towards large-scale modeling of materials with orbital free DFT with the help of machine learning: Gaussian process regression of kinetic energy densities. At the 45th International Conference and Exposition on Advanced Ceramics (ICACC 2021), virtual, February 8-12, 2021.
82. Addressing bottlenecks in large scale materials modeling with orbital free DFT: machine learning of kinetic energy functionals and Iocal pseudopotentials. Seminar at the Department of Materials and Optoelectronic Science, National Sun Yat-sen University, ROC Taiwan, August 12, 2020.
81. Effects of aggregate state in atomistic modeling of materials for electrochemical energy conversion and storage devices, At the SPIE Defense + Commercial Sensing Digital Forum, April 27 – May 1, 2020.
80. Ab initio inspired design strategies and methodology issues in materials modeling for post-lithium and organic batteries. At the Institute of High-Performance Computing (IHPC), A*STAR, Singapore, February 19, 2020.
79. Rectangular collocation for the solution of Schrödinger equation. At the Department of Physics, Concordia University, Montreal QC, Canada, February 5, 2020.
78. Role of organic cation-centered states in formamidinium lead iodide: Bulk vs nanoparticle models. At the 44th International Conference and Exposition on Advanced Ceramics and Composites (ICACC 2020), Daytona Beach FL, USA, January 26-31, 2020.
77. Ab initio modeling of materials for post-lithium and organic batteries: ab initio inspired design strategies and methodology issues. Seminar at the Department of Chemistry, York University, Toronto ON, Canada, January 24, 2020.
76. Ab initio modeling of materials for post-lithium and organic batteries: ab initio inspired design strategies and methodology issues. At the New York University at Shanghai, Shanghai, China, November 26, 2019.
75. Ab initio modeling of materials for advanced metal ion batteries & Advances in collocation for solution of the Schrödinger equation. At the Shandong University, Qingdao, China, November 25, 2019.
74. Ab initio modeling of materials for post-lithium and organic batteries: ab initio inspired design strategies and methodology issues. At the Nanjing Tech University, Nanjing, China, November 22, 2019.
73. Machine learning for Orbital-free DFT. At the Quantum International Frontiers, Shanghai University, Shanghai, China, November 18-22, 2019.
72. Rectangular collocation for the solution of the Schroedinger equation. At the Density Functionals for Many-Particle Systems: Mathematical Theory and Physical Applications of Effective Equations, Institute for Mathematical Sciences, Singapore, September 2 – 27, 2019.
71. (tutorial lecture) Machine learning techniques for orbital-free DFT. At the Density Functionals for Many-Particle Systems: Mathematical Theory and Physical Applications of Effective Equations, Institute for Mathematical Sciences, Singapore, September 2 – 27, 2019.
70. Advances in rectangular collocation for solution of the Schrödinger equation. At CHITEL/ QUITEL 2019 - International Conference of Theoretical Chemists of Latin Expression, Montreal, Canada, August 25-30, 2019
69. Methodological issues in DFT based modeling of active electrode materials for advanced metal-ion batteries. At 2nd Global Forum on Advanced Materials and Technologies for Sustainable Development (GFMAT-2), Toronto, Canada, July 21 – 26, 2019..
68. Machine learning in the context of atomistic simulation methods. Lecture at the summer school Modeling and Simulations Across Molecular Sciences and Engineering, Concordia University, Montreal QC, Canada, July 8-12, 2019.
67. Computational materials modelling and design for post-lithium and organic batteries: practical design strategies and methodological issues. At the Department of Physics, Jilin University, Changchun, China, March 15, 2019.
66. Rectangular collocation for the solution of the Schrödinger equation and machine-learned kinetic energy functionals to address methodology bottlenecks in atomistic materials modeling. At the Institute of Theoretical Chemistry, Jilin University, Changchun, China, March 15, 2019.
65. Ab initio modelling and design of materials for post-lithium and organic metal ion batteries: practical design strategies and methodological issues. At the Institute of Theoretical Chemistry, Jilin University, Changchun, China, March 14, 2019.
64. Alleviating bottlenecks in atomistic modeling: OFDFT development with machine learning and collocation for the solution of Schrödinger equation. At the University of Tsukuba, Tsukuba, Ibaraki, Japan, January 9, 2019.
63. Computational modelling and design of materials for post-lithium and organic metal ion batteries: practical design strategies and methodological issues, At Queen’s University, Kingston ON, Canada, December 10, 2018.
62. Computational materials modelling and design for post-lithium and organic batteries: practical design strategies and methodological issues. At the University of Michigan – Shanghai Jiao Tong University Joint Institute, Shanghai, China, November 26, 2018.
61. Materials modeling for electrochemical power sources & dealing with methodology bottlenecks. At the Miniworkshop on Molecular and Materials Sciences, Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy, November 16-19, 2018.
60. Rectangular collocation for electronic Schrödinger equation. At Quantum International Frontiers 2018, October 17-21, 2018, Changsha, Hunan, China
59. Computational modelling of materials for advanced electrochemical batteries and bringing anharmonic spectroscopy to materials modelling. At the Tsinghua-Berkeley Shenzhen Institute, Shenzhen, China, September 26, 2018.
58. Ab initio modeling and design of vanadia based electrode materials for post-Li batteries. At the Materials Challenges in Alternative and Renewable Energy (MCARE 2018), Vancouver BC, Canada, August 20-23, 201
57. Computational materials modelling and design: practical design strategies and methodological issues for advanced electrochemical batteries and bringing anharmonic vibrational spectroscopy to materials modelling. At Technion Israel Institute of Technology, Haifa, Israel, July 12, 2018.
56. Computational materials modelling and design for next generation energy conversion and storage technologies & methods for 21st century. At Shanghai University, Shanghai, China, July 5, 2018.
55. Ab initio perspective on modelling and design of materials for post-lithium and organic batteries: practical design strategies and methodological issues. At Chemistry Department, Queen’s University, Kingston ON, Canada, June 12, 2018.
54. Computational materials modelling and design for next generation solar cell and metal-ion battery technologies. At the Dipartimento di Ingegneria Civile e Ambientale (DICA) & CNR-ISTM c/o Dipartimento di Chimica, Università degli Studi di Perugia, Perugia, Italy, April 23, 2018.
53. Rectangular collocation for solution of the Schrödinger equation. At the AMOC 2018 (Anharmonicity in Medium-Sized Molecules and Clusters), Budapest, Hungary, April 16-19, 2018
52. Computational materials modelling and design for next generation energy conversion and storage technologies: practical design strategies and improved methods. At the New Jersey Institute of Technology, Newark NJ, USA, February 6, 2018.
51. Calculations of optical properties of fullerenes in aggregate state: some drawbacks of TD-DFT and of the dipole approximation and how to circumvent them. At the Global Workshop on Functional Materials and Devices, Singapore, January 11-13, 2018.
50. Using machine learning to resolve outstanding problems in materials modelling: from ionic and interatomic potentials to solution of the Schrödinger equation. At the AIST (National Institute of Advanced Science and Technology), Tsukuba, Ibaraki, Japan, November 20, 2017.
49. Potential active electrode materials for mono- vs. bi- vs. trivalent atoms: an ab initio perspective. At the Institute for Materials Chemistry and Engineering, Kyushu University, Fukuoka, Japan, September 5, 2017.
48. Doping of organic and inorganic active electrode materials for advanced electrochemical batteries: an electronic structure perspective. At the Departement de Chimie Moléculaire, Université Grenoble-Alpes, Grenoble, France, July 7, 2017.
47. Insertion of mono- vs. bi- vs. trivalent atoms in potential active electrode materials: a theoretical perspective, At the 3rd International Freiberg Conference on Electrochemical Storage Materials (ESTORM), Technische Universität Bergakademie Freiberg, Germany, June 12-14 2017.
46. A First Principles Comparative Study of Lithium, Sodium and Magnesium Storage in Pure and Gallium-Doped Germanium—Competition between Interstitial and Substitutional Sites. At the 2017 MRS Spring Meeting & Exhibit, Phoenix AZ, USA, April 17-21, 2017.
45. Ab initio study of charge transfer complexes of 2-anthroic acid and TiO2 nanoparticles for direct injection solar cells. At the 10th International Conference on Computational Physics (ICCP10), Macau, China, January 16-20, 2017.
44. Ab initio modeling and design of electrode materials for organic post-lithium batteries. At the City University of Hong Kong, Hong Kong, China, January 13, 2017.
43. Comparative Density Functional Theory and Density Functional Tight Binding study of arginine and arginine-rich cell penetrating peptide TAT adsorption on anatase TiO2: qualitative difference between small and big molecule adsorption. At the 9th Singapore International Chemical Conference (SICC-9), Singapore, December 11-14, 2016.
42. Ab initio modeling for post-Li and organic electrochemical batteries. At the National Institute for Materials Science, Tsukuba, Ibaraki, Japan, December 14, 2016.
41. Ab initio modeling of small vs large organic molecules on oxides: comparative Density Functional and Density Functional Tight Binding studies from aminoacids to peptides. At the Freie Univesitat Berlin, Berlin, Germany, October 7, 2016.
40. High-dimensional potential energy surfaces and vibrational spectra: HMDR and dimensionality reduction and how to get rid of a PES altogether. At the Department of Chemistry, Princeton University, Princeton NJ, USA, July 27, 2016.
39. Comparative Density Functional and Density Functional Tight Binding studies of small and large organic molecules adsorbed on titania: where DFTB might fail and where it wins over the DFT parent. At the Department of Chemistry, Rutgers University, Newark NJ, USA, July 9, 2016.
38. Ab initio modeling of organic and biomolecule - oxide surfaces: qualitative difference between small and big and the good and the bad of density functional tight binding. At the Department of Chemistry, University of Montreal, Montreal QC, Canada, June 3, 2016.
37. Ab initio modeling of organic and biomolecule - oxide surfaces: qualitative difference between small and big and the good and the bad of density functional tight binding. At the National Research Council, Ottawa ON, Canada, June 1, 2016.
36. Ab initio modeling of organic and biomolecule - oxide surfaces: qualitative difference between small and big and the good and the bad of density functional tight binding. At the Department of Chemistry, University of Waterloo, Waterloo ON, Canada, May 30, 2016.
35. Ab initio modeling of organic and biomolecule - oxide surfaces: qualitative difference between small and big and the good and the bad of density functional tight binding. At the Department of Chemistry, Queen’s University, Kingston ON, Canada, May 24, 2016.
34. Large-scale density functional based methods from the perspective of computational materials science. At the Kobe workshop for material design on strongly correlated electrons in molecules and materials, RIKEN Advanced Institute for Computational Science (AICS), Kobe, Japan, February 17-18, 2016.
Session chair.
33. Multidimensional quantum dynamics with and without a potential energy surface: Parameterized bases and anharmonic spectra in up to 15D, At the International Chemical Congress of Pacific Basin Societies (Pacifichem), Honolulu HI, USA, December 15-20, 2015.
Session chair.
32. Computational dye design for solar cells: applications and methodology issues. At the Golden Jubilee Chemistry Conference, National University of Singapore, Singapore, August 6-8, 2015.
31. Approaches for larger-scale electronic and nuclear quantum chemistry: beyond Kohn-Sham DFT & beyond potential energy surfaces, At the Centre for Materials Science and Nanotechnology (SMN), University of Oslo (UiO), Oslo, Norway, July 21, 2015.
30. Approaches for larger-scale electronic and nuclear quantum chemistry: beyond Kohn-Sham DFT & beyond potential energy surfaces, At the Scuola Normale Superiore, Pisa, Italy, July 14, 2015.
29. Computational modeling of materials for electrochemical energy conversion and storage: computational dye design and materials for Li, Na, and Mg storage. At the Centre for Materials Science and Nanotechnology (SMN), University of Oslo (UiO), Oslo, Norway, June 24, 2015.
28. First principles studies of the interaction of Li, Na, and Mg with different phases of TiO2 and with TCNE. At the Research Center for Advance Science and Technology, University of Tokyo, Tokyo, Japan, November 4, 2014.
27. Ab initio modeling of anode materials for Li, Na, and Mg ion batteries: post-Li issues, role of different phases, and computational matters. At the Freie Universität Berlin, Berlin, Germany, September 29, 2014.
26. Ab initio modeling of anode materials for Li, Na, and Mg ion batteries: post-Li issues, role of different phases, and computational matters. At the Institut für Materialprüfung, Werkstoffkunde und Festigkeitslehre (IMWF), Universität Stuttgart, Stuttgart, Germany, September 26, 2014.
25. Ab initio modeling of anode materials for Li, Na, and Mg ion batteries: post-Li issues, role of different phases, and computational matters. At the Bremen Center for Computational Materials Science, Universität Bremen, Bremen, Germany, September 25, 2014.
24. Ab initio modeling of anode materials for Li, Na, and Mg ion batteries: post-Li issues, role of different phases, and computational matters. At the Ruhr-Universität Bochum, Bochum, Germany, September 22, 2014.
23. Search for insertion type anodes for Na and Mg ion batteries based on group IV semiconductors: amorphization, doping, and computational errors. At the 26th Canadian Symposium on Theoretical and Computational Chemistry (CSTCC), Montreal QC, Canada, July 5-11, 2014.
22. Computational modeling and design of materials for electrochemical energy conversion and storage. At the Department of Chemistry, Queen’s University, Kingston ON, Canada, July 4, 2014.
21. Computational modeling and design of materials for electrochemical energy conversion and storage. At the Department of Chemistry and Chemical Biology, McMaster University, Hamilton ON, Canada, July 2, 2014
20. Studies of silicon and tin as insertion type anodes for post-Li batteries. At the 3rd Changsha International Workshop on Computational and Theoretical Chemistry with Materials, Hunan Normal University, Changsha, Hunan, China, June 8-10, 2014.
Session chair.
19. Modelling of Anode Materials for Post-Li Electrochemical Batteries (and more). At the Institute of Materials Research and Enginnering (IMRE), A*STAR, Singapore, December 4, 2013
18. Modeling of Anode Materials for post-Li Electrochemical Batteries. At the University of Tokyo, November 22, 2013, Tokyo, Japan.
17. Comparative computational studies of Li, Na, and Mg storage in crystalline and amorphous phases of Si and TiO2, At the 7th Asian Conference on Electrochemical Power Sources (ACEPS-7), November 24-27, 2013, Senri Life Sciences Center, Osaka, Japan (Sergei Manzhos, Fleur Legrain, and Oleksandr Malyi).
16. Mechanical and temperature effects on the performance of anodes in electrochemical batteries. At the 50th Annual Technical Meeting of Society of Engineering Science & ASME-AD Summer Meeting, Brown University, Providence RI, USA, July 28-31, 2013. (Sergei Manzhos, Oleksandr Malyi, Yang Wei Koh)
15. Capturing quantum effects in molecular dynamics: temperature and isotope effects on the energetics of organic solar cells. At the 2nd Changsha International Workshop on Computational and Theoretical Chemistry with Materials, Hunan Normal University, Changsha, Hunan, China, June 14-16, 2013.
14. Enabling quantum dynamics with or without potential energy surfaces by removing extra fitting. At the Workshop on Mathematical Methods in Quantum Molecular Dynamics, Banff AB, Canada, April 28 – May 3, 2013
13. How molecular and quantum dynamics help design solar cells: Anharmonic vibrations of adsorbed molecules and effects of nuclear motions on the operation of dye-sensitized solar cells. At the Freie Universitat Berlin, March 18, 2013
12. Computational approaches to the dynamics at surfaces and applications to graphene-like materials. At the Graphene Research Centre, National University of Singapore, October 17, 2012
11. Computational Modeling of Reactions at Surfaces Beyond Potential Energy Diagrams and the Harmonic Approximation. At the 2nd International Conference on Molecular and Functional Catalysis (ICMFC-2), Biopolis, Singapore, July 30-31, 2012
10. Effects of electron-phonon coupling on the performance of photoelectrochemical cells: influence of dye structural changes and of isotopic substitution. At the 1st Changsha International Workshop on Theoretical and Computational Chemistry with Materials, Hunan Normal University , Changsha, Hunan, China, June 8-9, 2012.
9. Computational modeling of molecule-surface interactions for sustainable energy schemes. At the National University of Singapore, Singapore, November 22, 2011
8. Relating dye structure to electron injection and recombination dynamics in dye-sensitized solar cells with the help of derivative coupling constants. At Queen's University, Kingston ON, Canada, June 15, 2011
7. Reconstruction of three-dimensional distributions from two-dimensional projections in photofragment imaging. At A*star, Biopolis, Singapore, October 22, 2010
6. Dynamics on ab initio potential energy surfaces for prediction of reactivity: a general method. At Asia-Pacific Interfinish 2010, Biopolis, Singapore, October 19-22, 2010
5. Perspectives for constructing ab initio potential energy surfaces in dozens of dimensions. At The 90th Annual Meeting of the Chemical Society of Japan, Osaka, Japan, March 26-29, 2010
4. Extracting functional dependence from sparse data and dimensionality reduction for potential energy surfaces. At Coping with Complexity: Model Reduction and Data Analysis, Research Workshop in conjunction with A4A6, the 6th Conference on “Algorithms for Approximation”, Ambleside, Lake District, UK, August 31 – September 4, 2009
3. Molecule-independent and dynamics-friendly methodology to build high-dimensional potential energy surfaces: towards applications in heterogeneous catalysis. At the Leiden Institute of Chemistry, the University of Leiden, June 16, 2008
2. Reconstructing potential energy surfaces and reaction pathways. At the National Research Council of Canada, Ottawa, ON, February 19, 2008
1. Molecule-independent and dynamics-friendly methods to build high-dimensional potential energy surfaces. At the National Research Council of Canada, Ottawa, ON, November 30, 2006.
7. OTHER CONFERENCE PRESENTATIONS (latest ~2 years and other than invited talks, click here for a fuller list; main presenter in bold)
7. OTHER CONFERENCE PRESENTATIONS (latest ~2 years and other than invited talks, click here for a fuller list; main presenter in bold)
The role of bonding vs. nonbonding interactions and minute geometry changes on the optical spectra of charge transfer nanoaggregates computed with TD-DFTB. At The 73rd JSAP Spring Meeting, Tokyo, Japan, March 15-18, 2026 (T. Li, R. Li. K. Kameda, S. Manzhos, M. Ihara). Talk.
Hybrid Density Functional Tight Binding (DFTB) - force field method to facilitate large scale electronic structure calculations: application to CO adsorption on nano-sized zirconia. At The 73rd JSAP Spring Meeting, Tokyo, Japan, March 15-18, 2026 (K. Chen, A. S. Hutama. K. Kameda, M. Ihara, S. Manzhos). Talk.
Near-natural generation of microstructures of functional ceramics with molecular dynamics. At The 12th Project Report Meeting of the HPCI System Including Fugaku, Tokyo, Japan, October 23-24, 2025 (S. Manzhos, M. Ihara, R. Li, T. Motori, T. Okamoto, K. Kameda). Poster.
High-accuracy building electricity demand forecasting using group encoding for high-dimensional binary data. At SCEJ 56th Autumn Meeting, Tokyo, Japan, September 16-18, 2025. (T. Kagawa, H. Lee, K. Kameda, S. Manzhos, M. Ihara). Talk.
Evaluation of surface adsorption reaction species coverage on SrZr0.95Y0.05O3-δ-added Ni/YSZ fuel electrodes in hydrogen power generation. At SCEJ 56th Autumn Meeting, Tokyo, Japan, September 16-18, 2025. (K. Kameda, K. Nakagawa, S. Manzhos, M. Ihara). Talk.
Sensitivity analysis of integration costs through coupling the building façade photovoltaic potential with a techno-economic model. At SCEJ 56th Autumn Meeting, Tokyo, Japan, September 16-18, 2025. (S. Wang, H. Lee, M. Oya, H. Hamasaki, K. Kameda, S. Manzhos, M. Ihara). Talk.
Comparison of polycrystalline ZrO2 models produced by computational heat treatment using molecular dynamics and Voronoi tessellation. At The 86th JSAP Autumn Meeting, Nagoya, Japan, September 7-10, 2025. (Y. Yoinara, K. Kameda, M. Ihara, S. Manzhos). Talk.
Neural network - Gaussian process regression hybrid for insightful machine learning: from materials informatics to DFT functional development. At New Generation Nuclear Density Functionals 2025, Beijing, China, June 26-29, 2025. (S. Manzhos, Y. Liu, K. Kameda, M. Ihara). Poster.
物理科学における非常に高精度な機械学習を必要とするアプリケーション：機械学習の手法開発への影響とニューロモルフィックコンピューティングの可能性の検討. At the 39th Annual Conference of JSAI, Osaka, Japan, May 27-30, 2025 (S. Manzhos, M. Ihara, J. Lüder, C.-C. Chueh, W.-Y. Lee, Q. G. Chen). Talk. (High vs Low Accuracy Machine Learning Applications in Physical Sciences: Implications for Methods and Possibilities of Neuromorphic Computing)
Application of hybrid Density Functional Tight Binding (DFTB)-Molecular Mechanics approach to computing optical properties of dyes on nanoparticles, At The 72nd JSAP Spring Meeting, Tokyo, Japan, March 14-17, 2025 (T. Li, R. Li, K. Kameda, S. Manzhos, M. Ihara). Poster.
Significantly improved stability of carbon/air secondary battery system by separating carbon deposition area, At PRiME 2024, Honolulu, HI, USA, October 6-11, 2024 ( K. Kameda, T. Wakamiya, R. Takagi, S. Manzhos, M. Ihara). Poster.
Concept and advantages of carbon/air secondary battery system as a fixed compact power storage with large capacity, At PRiME 2024, Honolulu, HI, USA, October 6-11, 2024 (M. Ihara, K, Kameda, T. Wakamiya, R. Takagi, C. Kexin, S. Manzhos). Oral.
Investigation of carbon-based materials for perovskite solar cells using first-principles calculations and materials informatics (in Japanese). At the 85th JSAP Autumn Meeting, Niigata, Japan, September 16-20, 2024. (Keisuke Maeda, Ruicheng Li, Keisuke Kameda, Sergei Manzhos, Manabu Manabu1) Talk.
A comprehensive materials database for orbital-free density functional theory developments. At Towards Routine Orbital-free Large-Scale Quantum-Mechanical Modelling of Materials, Institute for Advanced Studies in Mathematics (IASM), Zhejiang University, Hangzhou, China, September 8-13, 2024. (Johann Luder, Sergei Manzhos) Talk.
カーボン空気二次電池システムの充放電特性に対する温度依存性. At SCEJ 55th Autumn Meeting, Sapporo, Japan, September 11-13, 2024. (高木 伶海、加藤 航太、遠藤 明日香、Chen Kexin、若宮 大志郎、亀田 恵佑、Manzhos Sergei、伊原 学) Talk.
高効率と耐久性向上を両立させるカーボン空気二次電池システムのニッケルベース燃料極の開発. AAt SCEJ 55th Autumn Meeting, Sapporo, Japan, September 11-13, 2024. (亀田 恵佑、若宮 大志郎、吉田 紗良、チェン カシン、Manzhos Sergei、伊原 学) Talk.
カーボン空気二次電池システムにおける充放電特性のサーメット電極依存性. At SCEJ 55th Autumn Meeting, Sapporo, Japan, September 11-13, 2024. (若宮 大志郎、Chen Kexin、亀田 恵佑、Manzhos Sergei、伊原 学) Talk.
2050年のエネルギーシステム最適化に向けた全国建物壁面の太陽電池ポテンシャル算出. At SCEJ 55th Autumn Meeting, Sapporo, Japan, September 11-13, 2024. (Wang Shuai、大屋 昌士、大歳 夏生、亀田 恵佑、濱崎 博、大久保 辰哉、Manzhos Sergei、伊原 学) Talk.
日射成分とモジュール構造に基づく影計算による太陽電池リアルタイム発電量予測モデル. At SCEJ 55th Autumn Meeting, Sapporo, Japan, September 11-13, 2024. (大歳 夏生、葛西 祐也、亀田 恵佑、Manzhos Sergei、伊原 学) Talk.
クラスタリングを利用したSHAP値の解析手法によるエネルギー消費行動の可視化. At SCEJ 55th Autumn Meeting, Sapporo, Japan, September 11-13, 2024. (香川 達哉、飯嶌 大樹、Lee Hyojae、Wang Shuai、亀田 恵佑、Manzhos Sergei、伊原 学) Talk.
変動型再エネの発電量変動に追従する水素製造方法としての水Pulse-jet固体酸化物電解セルの提案. At SCEJ 55th Autumn Meeting, Sapporo, Japan, September 11-13, 2024. (岡崎 成美、亀田 恵佑、Manzhos Sergei、伊原 学) Talk.
Bandstructure modulation and molecular adsorption properties of zirconia nanoparticles: a large-scale electronic structure study. At 14th International Conference on Ceramic Materials and Components for Energy and Environmental Systems, Budapest, Hungary, August 18-22, 2024 (Kexin Chen, William Dawson, Takahito Nakajima, Aulia Sukma Hutama, Keisuke Kameda, Sergei Manzhos, Manabu Ihara). Poster.
Computational models of grain structures of titania with nature-like grain distributions. At 14th International Conference on Ceramic Materials and Components for Energy and Environmental Systems, Budapest, Hungary, August 18-22, 2024 (Takuma Okamoto, Anastassia Sorkin, Keisuke Kameda, Manabu Ihara, Hao Wang, Sergei Manzhos). Poster.
Machine learning of properties of perovskites with an NN with additive kernel GPR-based neuron activation functions. At Chemical Compound Space Conference 2024 (CCSC 2024), Heidelberg, Germany, May 21-24, 2024 (M. Nukunudompanich, H. Yoon, L. Hyojae, K. Kameda, M. Ihara, S. Manzhos). Poster.
Exploring the application of hybrid DFTB-Molecular Mechanics approach to computing optical properties. At the 2024 MRS Spring Meeting & Exhibit, Seattle WA, USA & virtual, May 7-9, 2024 (Ruicheng Li, Gekko Budiutama, Keisuke Kameda, Sergei Manzhos and Manabu Ihara). Talk.
Exploring carbon nanoflake based materials for charge transport layers of perovskite solar cells: a combined DFT-DFTB study including effects of solid-state packing. At the 2024 MRS Spring Meeting & Exhibit, Seattle WA, USA & virtual, May 7-9, 2024 (Ruicheng Li, Keisuke Maeda, Man-Fai Ng, Keisuke Kameda, Sergei Manzhos and Manabu Ihara1). Talk.
Modelling of natural-like grain generation of TiO2 and its effect on band structure. At the 2024 MRS Spring Meeting & Exhibit, Seattle WA, USA & virtual, May 7-9, 2024 (Takuma Okamoto, Anastassia Sorkin, Keisuke Kameda, Wang Hao, Manabu Ihara and Sergei Manzhos). Talk.
Effects of nanosizing of zirconia and bandstructure modulation on catalytic activity: insights from a combined Density Functional Tight Binding – Order(N) Density Functional Theory study. At the 2024 MRS Spring Meeting & Exhibit, Seattle WA, USA & virtual, May 7-9, 2024 (Kexin Chen, William Dawson, Takahito Nakajima, Aulia S. Hutama, Keisuke Kameda, Sergei Manzhos and Manabu Ihara). Talk.
Modulation of molecular adsorption properties of zirconia nanoparticles: a Density Functional Tight Binding Theory study. At the 71st JSAP Spring Meeting, Tokyo, Japan, March 22-25, 2024 (Kexin Chen, Aulia Sukma Hutama, Keisuke Kameda, Sergei Manzhos, Manabu Ihara). Talk.
Natural-like generation of grain structure of rutile-TiO2. At the 71st JSAP Spring Meeting, Tokyo, Japan, March 22-25, 2024 (Takuma Okamoto, Anastassia Sorkin, Keisuke Kameda, Wang Hao, Sergei Manzhos, Manabu Ihara). Talk.
Exploring electronic properties of carbon nanoflake-based materials for charge transport layers in perovskite solar cells: insight from solid-state modelling. At the 71st JSAP Spring Meeting, Tokyo, Japan, March 22-25, 2024 (Ruicheng Li, Keisuke Maeda, Man-Fai Ng, Keisuke Kameda, Sergei Manzhos, Manabu Ihara). Talk
熱・電力需要の変動が建物規模分散型水素蓄エネルギーシステムの経済性に与える影響. At the SCEJ 89th Annual Meeting, Osaka, Japan, March 18 - 20, 2024 (吉岡 大雄、白倉 沙也加、亀田 恵佑、Manzhos Sergei、伊原 学)
リアルタイム雲画像データに基づく日射成分を用いた影を含む太陽電池発電量予測モデル. At the SCEJ 89th Annual Meeting, Osaka, Japan, March 18 - 20, 2024 (大歳 夏生、Lee Hyojae、亀田 恵佑、Manzhos Sergei、伊原 学)
電極反応モデルに基づく水素発電におけるBaZr0.9Y0.1O3-δ添加Ni/YSZ燃料極の反応種被覆率の推定. At the SCEJ 89th Annual Meeting, Osaka, Japan, March 18 - 20, 2024 (亀田 恵佑、中川 慶、古賀 康友、Chen Kexin、高木 伶海、若宮 大志郎、岡崎 成美、Lee Hyojae、大歳 夏生、Manzhos Sergei、伊原 学)
炭素析出制御可能なカーボン空気二次電池システムの電極開発. At the SCEJ 89th Annual Meeting, Osaka, Japan, March 18 - 20, 2024 (亀田 恵佑、若宮 大志郎、Chen Kexin、Manzhos Sergei、伊原 学)
Modelling of CO/CO2 Electrode Reactions in Carbon/Air Secondary Battery System. At the SCEJ 89th Annual Meeting, Osaka, Japan, March 18 - 20, 2024 (Chen Kexin、Kameda Keisuke、Koga Yasutomo、Manzhos Sergei、Ihara Manab)
Neural networks with optimized neuron activation functions and without nonlinear optimization or how to prevent overfitting, cut CPU cost and get physical insight all at once. At 2023 MRS Fall Meeting & Exhibit, Boston MA, USA, November 27 - December 1 & December 5-7, 2023 (Sergei Manzhos, Manabu Ihara). Talk
Carbon nanoflake based materials for charge transport layers of perovskite solar cells: insight from atomistic modeling into nanosizing and functionalizations suitable for electron and hole transport. At 2023 MRS Fall Meeting & Exhibit, Boston MA, USA, November 27 - December 1 & December 5-7, 2023 (Ruicheng Li, Keisuke Kameda, Sergei Manzhos, Manabu Ihara). Poster
Effect of naturally generated microstructure of a ceramic on ion transport: lithiation of titania. At 2023 MRS Fall Meeting & Exhibit, Boston MA, USA, November 27 - December 1 & December 5-7, 2023 (Sergei Manzhos, Takuma Okamoto, Anastasia Sorkin, Keisuke Kameda, Manabu Ihara, Hao Wang). Talk.
Machine learning beyond plain neural networks and kernel methods: from getting rid of non-linear optimization and overfitting to building many-body representations. At Hierarchical Structure and Machine Learning (HISML) 2023, Tokyo, Japan, October 2-13, 2023 (Sergei Manzhos and Manabu Ihara). Talk.
Novel encoding method for high dimensional power consumption data in distributed energy system for short-term electricity demand forecasting. At the SCEJ 54th Autumn Meeting, Fukuoka, Japan, September 11-13, 2023 (Hyojae Lee, Shunsaku Tsuda, Taiki Iijima, Keisuke Kameda, Sergei Manzhos, Manabu Ihara). Talk.
Calculation of Tokyo's photovoltaic potential and study of the effects of reducing daily power fluctuations from facade installations. At the SCEJ 54th Autumn Meeting, Fukuoka, Japan, September 11-13, 2023 (Shuai Wang, Masashi Oya, Keisuke Kameda, Sergei Manzhos, Manabu Ihara). Talk.
Neural networks without nonlinear optimization and with optimized neuron activation functions built with Gaussian processes. At The 33rd Annual Meeting of the Japanese Neural Network Society (JNNS2023), Tokyo, Japan, September 4-6, 2023 (Sergei Manzhos, Manabu Ihara). Poster.
Building robust orders-of-coupling representations with machine learning. At the 34th IUPAP Conference on Computational Physics (CCP2023), Kobe, Japan, August 4-8, 2023 (Sergei Manzhos, Manabu Ihara). Talk.
Combining Density Functional Tight Binding (DFTB) with empiric potentials for large-scale semiempirical materials modeling. At the 34th IUPAP Conference on Computational Physics (CCP2023), Kobe, Japan, August 4-8, 2023 (Gekko Budiutama, Ruicheng Li, Sergei Manzhos, Manabu Ihara). Poster.
Enhancement of the bond valence method for rapid screening of solid state ionic conductors with machine learning. At ICMAT 2023, Singapore, June 26-30, 2023 (Takaaki Ariga, Sergei Manzhos, Manabu Ihara). Talk.
Generation of microstructure of perovskite solar cell materials from molecular dynamics. At ICMAT 2023, Singapore, June 26-30, 2023 (Anastassia Sorkin, Jiei Yasumoto, Takuma Okamoto, Sergei Manzhos, Hao Wang, Manabu Ihara). Talk.
Hybrid models combining neural networks (NN), Gaussian process regressions (GPR), and high-dimensional model representations (HDMR) for more powerful machine learning. At the 37th Annual Conference of the Japanese Society for Artificial Intelligence (2023年度 人工知能学会全国大会（第37回）, JSAI2023), Kumamoto, Japan, June 6-9, 2023 (Sergei Manzhos, Shunsaku Tsuda, Hyojae Lee, Manabu Ihara). Talk.
Clarifying the effects of nanostructured porosity of silicon on the band gap and band alignment: a computational study. At the 70th JSAP Spring Meeting, Tokyo, Japan, March 15-18, 2023 (Panus Sundarapura, Manabu Ihara, Sergei Manzhos). Talk.
8. CONFERENCE ORGANIZING COMMITTEES, SESSION CHAIRING etc
Conference organizing committees
23rd International Workshop on Computational Mechanics of Materials, Singapore, October 2-5, 2013
3rd International Freiberg Conference on Electrochemical Storage Materials (ESTORM), Freiberg, Germany, June 12-14, 2017, member of the conference advisory board
12th International Conference on Ceramic Materials and Components for Energy and Environmental Applications (CMCEE-12), July 23-27, 2018, Singapore.
Quantum International Frontiers 2018, October 17-21, 2018, Changsha, Hunan, China
International Conference on Advanced Ceramics and Composites (2019 ICACC), January 27 - February 1, 2019, Daytona Beach FL,USA
International Conference on High-Performance Ceramics (CICC-11), May 25-29, 2019, Kunming, China.
2nd Global Forum on Advanced Materials and Technologies for Sustainable Development (GFMAT-2) Toronto Marriott Downtown Eaton Centre Hotel, Toronto, Canada, July 21-26, 2019
CMMSE – 2019, 19th International Conference on Computational and Mathematical Methods in Science and Engineering (date & location TBA)
44th International Conference and Exposition on Advanced Ceramics and Composites (ICACC2020), January 26-31, 2020, Daytona Beach FL, USA (co-organizer of Symposium S10: Modeling, genome, informatics, and machine learning)
45th International Conference and Exposition on Advanced Ceramics and Composites (ICACC2021), February 9-11, 2021, virtual (co-organizer of Symposium S10: Modeling, genome, informatics, and machine learning)
46th International Conference and Exposition on Advanced Ceramics and Composites (ICACC2022), January 24-28, 2022, virtual (co-organizer of Symposium S10: Modeling and Design of Ceramics and Composites)
47th International Conference and Exposition on Advanced Ceramics and Composites (ICACC2023), January 22-27, 2022, Daytona Beach FL, USA (co-organizer of Symposium S10: Modeling and Design of Ceramics and Composites)
Session chairing and judge roles at conferences
Session chairing and judge roles at conferences
29th Canadian Symposium on Theoretical and Computational Chemistry (CSTCC), Kelowna BC, Canada, June 27 - July 1, 2022
Judge at the poster sessionQuantum International Frontiers 2018, October 17-21, 2018, Changsha, Hunan, China. Session chair.
International Symposium on Molecular Spectroscopy, 73rd meeting (ISMS), Champaign-Urbana IL, USA, June 18-22, 2018.
Judge of student presentations for Rao Prize.
27th International Photovoltaic Science and Engineering Conference (PVSEC-27), Shiga, Japan, November 12-17, 2017.
Session chair of “Organic and Dye-Sensitized Solar Cells”
Session chair of “High Performance (Efficiency)”
Pacifichem 2015, Honolulu, Hawaii, USA, December 15-20, 2015 ( http://www.pacifichem.org/ ). Session chair of “PHYS: New Insights from Quantum Dynamics and ab initio Potentials in High Dimensional Systems (#84)”.
26th Canadian Symposium on Theoretical and Computational Chemistry, July 6-11, 2014, Montreal QC, Canada. Judge at the poster session.
3rd Changsha International Workshop on Computational and Theoretical Chemistry with Materials, Hunan Normal University, Changsha, Hunan, China, June 8-10, 2014. Session chair.
23rd International Workshop on Computational Mechanics of Materials, October 2-5, 2013, Singapore. Session chair.
94th Canadian Society for Chemistry Meeting and Exhibition, June 5-9, 2011, Montreal QC, Canada. Judge at the Physical and Theoretical Division poster session.
Judge roles at science fairs
Judge roles at science fairs
Singapore Science and Engineering Fair 2019, judge
Singapore Science and Engineering Fair 2017, judge
Singapore Science and Engineering Fair 2016, judge
Singapore Science and Engineering Fair 2015, judge
Singapore International Mathematics Challenge (SIMC) 2014, judge
Singapore Science and Engineering Fair 2014, judge
9. SCHOLARSHIPS, AWARDS, AND GRANTS
2025 – 2026 KMITL Research Funding: Academic Melting Pot Inbound Program (invitee PI)
2024 – 2027 内閣府SIP「マテリアル事業化イノベーション・育成エコシステムの構築」のうち、サブ課題C「マテリアルユニコーン予備軍の創出」個別テーマ(1)「マテリアルユニコーン予備軍創出支援」” 世界初の炭素/CO2変換による大容量コンパクト蓄電システムの実用化 —材料インフォマティクスによる開発加速、経済活性化と地球温暖化抑制を実現する”アンビエントエネルギー社会”の実現へ—” (co-PI)
2024 – 2025 WRH Program Overseas Researcher Invitation “Investigation of microstructure-driven properties of functional ceramics: from large-scale atomistic calculations to experimental validation” (host PI)
2024 – 2025 WRH Program Faculty Research Abroad “Understanding and control of microstructure-driven properties of functional ceramics” (PI)
2023 JSPS Invitational Fellowships “Development of next generation electron density based mechanistic analyses of functional materials” (host PI)
2022 – 2024 JST Mirai “エネルギービッグデータをコアとするカーボンニュートラルデジタルツイン” (co-PI)
2022 – 2025 JSPS Basic Research (C) “設置角度に着目した農地共用型太陽光発電と、国内への導入ポテンシャルの算出” (co-PI)
2020 - 2025 National Science and Engineering Research Council of Canada Discovery Grant (PI): Computational modeling and design of materials for energy conversion and storage & next generation methods
2020 – 2021 Ministère des Relations Internationales et de la Francophonie du Québec (PI): L'amélioration de la précision et la productivité de l'usinage ultraprécis de matériaux difficiles à usiner
2020 JSPS Invitational Fellowship
2019 – 2021 Mitacs funded joint academic-industrial project “Development of machine learning and artificial intelligence based tools to improve efficiency in financial services”
2019 INRS fonds de démarrage
2017-2020 MOE AcRF Tier 1 grant (co-PI): Enhancing wear resistance of diamond tools for steel machining by ion implantation
2019 Inspiring Research Mentor Award, NUS High School of Mathematics and Science
2017-2019 MOE AcRF Tier 1 grant (PI): Machine Learning to Enable Large-Scale Ab Initio Modelling with Orbital-Free DFT
2016-2019 MOE AcRF Tier 1 grant (PI): Fullerene Derivatives for more Efficient Organic and Perovskite Solar Cells
2016-2019 MOE AcRF Tier 2 grant (PI): Design of vanadium oxide based electrodes for post-lithium batteries
2016 SIG special grant to visit Princeton University
2015 University of Oslo (Norway) Visiting Researcher grant
2015-2018 MOE AcRF Tier 2 grant (PI): Rational design of organic electrodes for Li & Na ion electrochemical batteries
2014-2017 MOE AcRF Tier 1 grant (PI): Phase transitions and amorphization in battery electrodes: computer modelling
2013 Best Poster Award at the 7th Asian Conference on Electrochemical Power Sources (ACEPS-7), November 24-27, 2013, Senri Life Sciences Center, Osaka, Japan
2012-2015 MOE AcRF Tier 1 / startup grant (PI): Theoretical modeling of materials for energy conversion and storage
2009 Global COE “Chemistry Innovation” Grant to Young Researchers of the Japan Society for the Promotion of Science
2006-2007 Natural Sciences and Engineering Research Council of Canada (NSERC) Postdoctoral Fellowship
2004 Din Lal TA Award in Chemistry for Excellence in Teaching
2004 Queen’s Univ. Graduate Award
2003 Queen’s Univ. Graduate Award
2002-2003 Ontario Graduate Scholarship
2002 Queen’s Univ. Graduate Award
2001 Award for the best poster given in the Division of Physical and Theoretical Chemistry at 84th CSC Conference & Exhibition
2001 Queen’s Univ. Graduate Award
2000 – 2001 Queen’s Univ. Graduate Fellowship
1997 – 1999 Kharkov. Univ. Rozhansky Excellence Stipend
1998 First Prize at Conference-Competition of Students and Graduate Students Works in Radio Physics at Kharkov University
10. LEARNED SOCIETY & EDITORIAL BOARD MEMBERSHIPS, SERVICE TO THE ACADEMIC COMMUNITY
10. LEARNED SOCIETY & EDITORIAL BOARD MEMBERSHIPS, SERVICE TO THE ACADEMIC COMMUNITY
Committees
Board of Education (Ookayama campus) Representative for the Department of Applied Chemistry, Energy Course, 2022-
Academy of Energy and Informatics (エネルギー・情報卓越教育院), Tokyo Institute of Technology, representative 2021-
Data Science / AI University Education Implementation Committee (データサイエンス・ＡＩ全学教育機構運営委員会委員), Tokyo Institute of Technology, 2021-
Department Management Committee of the Department of Mechanical Engineering, NUS, elected member, 2013-2019
Department Consultative Committee of the Department of Mechanical Engineering, NUS, internal member, 2013-2019
Queen’s University Faculty of Arts and Science Curriculum Committee, member in 2003-2004
Editorial board member of
Computational and Theoretical Chemistry (Elsevier), Editor (since January 2026)
Engineering and Technology Horizons (King Mongkut's Institute of Technology Ladkrabang), Advisory Board member (since 2025)
Physchem, Editor-in-Chief (http://www.mdpi.com/journal/physchem) (2021-2025)
Molecules (IF=3.098, http://www.mdpi.com/journal/molecules),
Editorial board member, section Theoretical Chemistry (since 2018)
Guest editor for Special Issue "Molecular Engineering for Electrochemical Power Sources" (2016)
Computational Materials Science (IF= 2.530, http://www.journals.elsevier.com/computational-materials-science/ ), guest editor (2014)
Frontiers in Energy Research (https://www.frontiersin.org/journals/energy-research), guest editor for Special Topic “Materials design and optimization for next generation solar cell and light-emitting technologies” (2018)
Computation (http://www.mdpi.com/journal/computation), guest editor for the Special Issue "Atomistic Modeling of Materials and Processes in Post-Silicon Solar Cells" (2017)
Mathematics (http://www.mdpi.com/journal/mathematics), guest editor for Special issue "Computational Spectroscopy" (2018)
The Scientific World Journal
International Journal of Chemical Physics (until 2015)
Canadian Young Scientist Journal (until 2015)
Review of manuscripts for ACS Energy Lett., ACS Sustainable Chem. Eng., Acta Marerialia, Adv. Mater. Interfaces, Adv. Quant. Technol., Annalen der Physik, Appl. Energy, Appl. Surf. Sci., Carbon, Catalysts, Chem. Phys. Lett., ChemComm, Chem. Rev., ChemSusChem, Electrochem. Commun., Electrochimica Acta, Energy Environ. Sci., Eur. J. Phys. B., Fullerenes, Nanotubes and Carbon Nanostructures, Ind. J. Phys., Inorganics, Int. J. Mod. Phys. B., Int. J. Quantum Chem., J. Alloys Compounds, J. Am. Chem. Soc., J. Appl. Phys., J. Chem. Phys., J. Chem. Theory Comput., J. Electroanal. Chem., J. Hydrogen Energy, J. Mater. Chem. A/C, J. Mater. Sci., J. Mol. Eng. Mater., J. Mol. Model., J. Photonics Energy, J. Phys. Chem. & J. Phys. Chem. Lett., J. Phys. Commun., J. Power Sources, J. Solid State Chem., J. Theor. Comput. Chem., Jpn. J. Appl. Phys., Langmuir, Mater. Chem. Phys., Materials, Mater. Lett., Mathematics, Mol. Phys., Molecules, Nanoscale Horizons, Nano Lett., Nature, Nature Commun., New J. Chem., Organometallics, Phil. Mag. & Phil. Mag. Lett., Phys. Chem. Chem. Phys., Phys. Lett. A, Phys. Status Solidi, Roy. Soc. Open Sci., RSC Adv., Solid State Ionics, Solid State Sciences, Struct. Chem, Surf. Sci., The Scientific World Journal, Synthetic Metals, Vacuum, WIREs Comput. Molec. Sci., and other journals
Reviewer recognition
Outstanding Reviewer for Physical Chemistry Chemical Physics in 2016, “based on the number, timeliness and quality of the reports completed over the last 12 months”, Phys. Chem. Chem. Phys., 2017, 19, 8140-8140
Outstanding Reviewer for Physical Chemistry Chemical Physics in 2017, “based on the number, timeliness and quality of the reports completed over the last 12 months”, Phys. Chem. Chem. Phys., 2018, 20, 11515-11515
IOP Trusted Reviewer (since 2023) for “high level of peer review competence and the ability to constructively critique scientific literature to an exceptional standard”
Outstanding Reviewer award for Machine Learning: Science and Technology (IOP Publishing) in 2023.
Outstanding Reviewer for Physical Chemistry Chemical Physics in 2025, “based on the number, timeliness and quality of the reports”.
Outstanding Reviewer award for Machine Learning: Science and Technology (IOP Publishing) in 2025.
Review of proposals for major granting agencies, including ACS Petroleum Research Fund, Kentucky Science & Engineering Foundation (KSEF), National Science Centre (Poland), Deutsche Forschungsgemeinschaft (German Research Foundation), Competitive Research Grants (CRG) program at King Abdullah University of Science and Technology (KAUST), Le Fonds de Recherche du Québec– Nature et technologie, KU Leuven C1 grants, Agence National de la Recherche (France) National Research and Development Agency (ANID) of Chile, Canada Research Chair program, US DOE, Swiss National Science Foundation ...
11. LANGUAGES
11. LANGUAGES
English - fluent (spoken and written)
French - fluent (spoken and written)
German – working knowledge
Japanese - working knowledge
Russian and Ukrainian - native
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