Research

We are developing innovative nanomaterials with efficient light absorption, light-emitting properties, high ionic and electronic conductivity and biocompatibility, based on polymer chemistry, supramolecular chemistry, theoretical chemistry, and organic chemistry. We strategically consider the electronic and steric structures of molecules to maximize the potential of materials. In addition to experimental studies, we will also approach novel materials from the perspective of data science, which predicts optimal solutions based on existing data. Through these efforts, we aim to develop next-generation energy materials that can be implemented in society while pursuing the academic principles of each field. The following is a list of major research projects currently underway in the Fujigaya Laboratory.

Project 1 : Development of next-generation battery materials

In today's electronics-driven society, it is no exaggeration to say that energy means electricity, and therefore electrodes are essential for energy devices. CNTs are an ideal material for electrodes because of their high electrochemical stability, electrical conductivity, mechanical strength, and mesh structure that favors material diffusion. To be able to use these CNTs freely, a certain amount of know-how is required. This is where the essence of our technology lies.

Reference

[1] D. Wu, N. Kayo, S. M. Jayawickrama, Y. K. Phua, N. Tanaka, T. Fujigaya, “Effect of Alcohol Content on the Ionomer Adsorption of Polymer Electrolyte Membrane Fuel Cell Catalysts”, Int. J. Hydrogen. Energy 48, 5915-5928 (2023).

[2] Y. Motoishi, N. Tanaka, T. Fujigaya, "Postmodification of highly delocalized cations in an azide-based polymer via copper-catalyzed cycloaddition for anion exchange membranes", Polymer J. 55, 171-180 (2023).

[3] Y. K. Phua, D. Weerathunga, D. Wu, C. Kim, S. M. Jayawickrama, N. Tanaka, T. Fujigaya, "Effect of Surface Roughness of Carbon Nanotube-based Catalyst Layer for Polymer Electrolyte Membrane Fuel Cell Performance", Sustainable Energy & Fuels 6, 4636-4644 (2022).

[4] D. Wu, S. M. Jayawickrama, N. Tanaka, T. Fujigaya, "Effect of Polymer-coating on Acetylene Black for Durability of Polymer Electrolyte Membrane Fuel Cell", J. Power Sources 549, 232079 (2022).

[5] S. M. Jayawickrama, D. Wu, R. Nakayama, S. Ishikawa, X. Liu, G. Inoue, T. Fujigaya, "Effect of a Polybenzimidazole Coating on Carbon Supports for Ionomer Content Optimization in Polymer Electrolyte Membrane Fuel Cells", J. Power Source 496, 229855 (2021).

Project 2 : Toward the Nanobiotechnology

There is a widespread perception that CNTs are toxic because they resemble asbestos, but any substance can be poisonous depending on how it is ingested; CNTs are a rare material that can absorb near-infrared light, which has excellent bio-permeability, and research is underway to utilize this property for biological applications.

Reference

[1] R. Hamano, N. Tanaka, T. Fujigaya, “Size exclusion chromatography-based length sorting of single-walled carbon nanotubes stably coated with cross-linked polymer”, Mater. Adv. 5, 2482-2490 (2024).

[2] S. S. Y. Law, G. Liou, Y. Nagai, J. Giménez-Dejoz, A. Tateishi, K. Tsuchiya, Y. Kodama, T. Fujigaya, K. Numata, "Polymer-coated carbon nanotube hybrids with functional peptides for gene delivery into plant mitochondria",  Nature Commun. 13, 2417 (2022).

[3] Y. Nagai, K. Nakamura, J. Ohno, M. Kawauchi, T. Fujigaya, "Antibody-Conjugated Gel-Coated Single-Walled Carbon Nanotubes as Photothermal Agents" ACS Appl. Bio Mater. 4, 5049 (2021).

[4] Y. Nagai, K. Nakamura, M. Yudasaka, T. Shiraki, T. Fujigaya, "Radical Polymer Grafting on the Surface of Single-walled Carbon Nanotubes Enhances Photoluminescence in the Near Infrared: Implications for Bioimaging and Biosensing" ACS Appl. Nano Mater. 3, 8840 (2021).

[5] Y. Nagai, M. Yudasaka, H. Kataura, T. Fujigaya, "Brightening of Near-IR Emission from Single-walled Carbon Nanotubes by Modifying the Chemical Structure of Cross-linked Polymer Coating", Chem. Commun. 55, 6854 (2019).

Project 3 : Development of Flexible Thermoelectric Generation Sheets

Our goal is to develop thermoelectric conversion sheets made of single-walled carbon nanotubes (SWNTs) with the world's highest conversion efficiency and durability. We aim to achieve a high Seebeck coefficient by selecting the diameter and electrical properties of the CNTs used, and to achieve high durability by identifying the mechanism of stable doping. We also focus on understanding and controlling the contact points of SWNTs, and aim to achieve high efficiency by building a giant modeling system in conjunction with actual measurement data.

Reference

[1] N. Tanaka, M. Yamamoto, I. Yamaguchi, A. Hamasuna, E. Honjo, T. Fujigaya “Photolithographic p–n patterning of single-walled carbon nanotube sheets using photobase generators”, J. Mater. Chem. A 11, 23278 (2023).

[2] N. Tanaka, T. Ishii, I. Yamaguchi, A. Hamasuna, T. Fujigaya, “Photoinduced electron doping of single-walled carbon nanotubes based on carboxamide photochemical reactions”, J. Mater. Chem. A 11, 6909-6917 (2023).

[3] B. Angana, W. Huang, T. Ishii, R. Yamaguchi, E. Honjo, N. Tanaka, T. Fujigaya, "Comparison of thermoelectric properties of sorted and unsorted semiconducting single-walled carbon nanotube free-standing sheets", Jpn. J. Appl. Phys. 61,121004 (2022).

[4] N. Tanaka, A. Hamasuna, T. Uchida, R. Yamaguchi, T. Ishii, A. Staylkov, T. Fujigaya, "Electron doping of single-walled carbon nanotubes using pyridine-boryl radicals" Chem. Commun. 57, 6019-6022 (2021).

[5] R. Yamaguchi, T. Ishii, M. Matsumoto, B. Angana, N. Tanaka, K. Oda, M. Tomita, T. Watanabe, T. Fujigaya, "Thermal Deposition Method for p-n Patterning of Carbon Nanotube Sheets for Planar-type Thermoelectric Generator", J. Mater. Chem. 9, 12188 (2021).

Project 4 :   Control of Near-Infrared Emission by Supramolecular Chemistry

Semiconducting single-walled carbon nanotubes (SWCNTs) emit near-infrared light, which is useful for bio-imaging and communications applications. However, the quantum yield of SWCNTs is low (<1%), and the emission wavelength is fixed depending on the winding of the graphene sheet (chirality). In contrast, there is a technique called "local chemical modification" that can significantly improve the luminescence properties by chemically modifying the SWCNT surface with a very small amount of molecules. We have focused on the fact that the luminescence of locally chemically modified SWCNTs (lf-SWCNTs) is greatly affected by the structure and function of the molecule to be modified, and are aiming to create new near-infrared luminescence functions of lf-SWCNTs and develop exciton engineering technology based on molecular chemistry by making full use of synthetic organic chemistry and supramolecular chemistry. We are also working on the development of exciton engineering technology.

Reference

[1] T. Shiraki, R. Saito, H. Saeki, N. Tanaka, K. Harano, T. Fujigaya, “Defect Photoluminescence from Alkylated Boron Nitride Nanotubes”, Chem. Lett. 52, 44-47 (2023).

[2] B. Yu, S. Naka, H. Aoki, K. Kato, D. Yamashita, S. Fujii, Y. Kato, T. Fujigaya, T. Shiraki, “ortho-Substituted Aryldiazonium Design for the Defect Configuration-Controlled Photoluminescent Functionalization of Chiral Single-Walled Carbon Nanotubes”, ACS. Nano 16, 21452-21461 (2022).

[3] K. Hayashi, Y. Niidome, T. Shiga, B. Yu, Y. Nakagawa, D. Janas, T. Fujigaya, T. Shiraki, "Azide modification of single-walled carbon nanotubes for near-infrared defect photoluminescence by luminescent sp2 defect formation", Chem. Commun. 58, 11422-11425 (2022).

[4] Y. Niidome, R. Wakabayashi, M. Goto, T. Fujigaya, T. Shiraki, "Protein-structure-dependent spectral shifts of near-infrared photoluminescence from locally functionalized single-walled carbon nanotubes based on avidin–biotin interactions",  Nanoscale 14, 13090-13097 (2022).

[5] Y. Nakagawa, B. Yu, Y. Niidome, K. Hayashi, A. Staykov, M. Yamada, T. Nakashima, T. Kawai, T. Fujigaya, T. Shiraki  "Photoisomerization of Covalently-attached Diarylethene on Locally Functionalized Single-walled Carbon Nanotubes for Photoinduced Wavelength Switching of Near Infrared Photoluminescence",  J. Phys. Chem. C 126, 10478 (2022).

Project 5 :  Materials Informatics

Data science and machine learning have made remarkable progress in recent years, and they are now making their mark in the world of chemistry and materials. The fusion of chemistry/materials and data science is called "materials informatics," and it is one of the hottest research fields today. In our group, we are searching for new materials and developing new methods by extracting data from literature and using simulation data from "Fugaku" and ITO (Kyushu University supercomputer). We are working on research in various fields such as polymer materials, drug discovery, and interface chemistry.

Reference

[1] Y. K. Phua, K. Kato, T. Fujigaya, “Predicting the anion conductivities and alkaline stabilities of anion conducting membrane polymeric materials: development of explainable machine learning models”, STAM 24, 2261833 (2023).

[2] K. Fukuzawa, K. Kato, C. Watanabe, Y. Kawashima, Y. Handa, A. Yamamoto, K. Watanabe, T. Ohyama, K. Kamisaka, D. Takaya, and T. Honma, "Special Features of COVID-19 in the FMODB: Fragment Molecular Orbital Calculations and Interaction Energy Analysis of SARS-CoV-2-Related Proteins", J. Chem. Inf. Model. 61, 4594-4612 (2021).

[3] K. Kato, Y. Maekawa, N. Watanabe, K. Sasaoka, T. Yamamoto, "Discovery of new microscopic structures in surface water on graphene using data science", Jpn. J. Appl. Phys. 59, 025001 (2020).

[4] K. Kato, T. Masuda, C. Watanabe, N. Miyagawa, H. Mizouchi, S. Nagase, K. Kamisaka, K. Oshima, S. Ono, H. Ueda, A. Tokuhisa, R. Kanada, M. Ohta, M. Ikeguchi, Y. Okuno, K. Fukuzawa, T. Honma, "High-Precision Atomic Charge Prediction for Protein Systems Using Fragment Molecular Orbital Calculation and Machine Learning", J. Chem. Inf. Model. 60, 3361–3368 (2020).

[5] K. Kato, T. Honma, K. Fukuzawa, “Intermolecular interaction among Remdesivir, RNA and RNA-dependent RNA polymerase of SARS-CoV-2 analyzed by fragment molecular orbital calculation", J. Mol. Graph. Model. 100, 107695 (2020).