Publications

Books: (1)

1. Krishnan, N. M. A., Kodamana, H., Bhattoo., R., 2024, Machine Learning for Materials Discovery: Numerical Recipes and Practical Applications, Springer Nature (link).

Peer-reviewed Publications: (120)

2024 (13)

2. Chakraborty, S., Ganisetti, S., Balaji, S., Khan, S., Mohapatra, S. K., Patra, P.,  Sen, P., Ghosh, M., Dey, K. K., Krishnan, N. M. A., Biswas, K., Allu, A. R., & Annapurna, K., 2024. Enhancing glass-forming ability and mechanical properties of barium-calcium-aluminate glasses through ZnO inclusion. Journal of Non-Crystalline Solids, 636, 123005. (link)

3. Bishnoi, S., Jayadeva, J., Ranu, S., & Krishnan, N. M. A., 2024. BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics. In The Twelfth International Conference on Learning Representations (ICLR 2024). (link)

4. Mandal, I., Gangareddy, J., Sethurajaperumal, A., Nk, M., Majji, M., Bera, S., Rudra, P., Ravichandran, V., Bysakh, S., Jacob, N., Rao, K. D. M., Singh, R. K., Krishnan, N. M. A., Chirumamilla, M., Palanisamy, T., Motapothula, M., Varrla, E., Ghosh S., & Allu, A. R., 2024. H‐Glass Supported Hybrid Gold Nano‐Islands for Visible‐Light‐Driven Hydrogen Evolution. Small, 2401131. (link)

5. Miret, S., Krishnan, N. M. A., Sanchez-Lengeling, B., Skreta, M., Venugopal, V., & Wei, J. N., 2024. Perspective on AI for accelerated materials design at the AI4Mat-2023 workshop at NeurIPS 2023. Digital Discovery. (link)

6. Hira, K., Zaki, M., Sheth, D., Mausam & Krishnan, N. M. A., 2024. Reconstructing the materials tetrahedron: challenges in materials information extraction. Digital Discovery, 3(5), 1021-1037. (link)

7. Burark, P., Tiwari, K., Rashid, M. M., Prathosh, A. P., & Krishnan, N. M. A., 2024. CoDBench: a critical evaluation of data-driven models for continuous dynamical systems. Digital Discovery, 3(6), 1172-1181. (link)

8. Bihani, V., Mannan, S., Pratiush, U., Du, T., Chen, Z., Miret, S., Micoulaut, M., Smedskjaer, M., Ranu, S., & Krishnan, N. M. A., 2024. EGraFFBench: evaluation of equivariant graph neural network force fields for atomistic simulations. Digital Discovery, 3(4), 759-768. (link)

9. Mannan, S., Bihani, V., Krishnan, N. M. A., and Mauro, J.C., 2024. Navigating energy landscapes for materials discovery: Integrating modeling, simulation, and machine learning. Materials Genome Engineering Advances, p.e25. (link)

10. Bedi, S., Katiyar, A., Krishnan, N. M. A. and Kota, S.H., 2024. Utilizing LSTM models to predict PM2. 5 levels during critical episodes in Delhi, the world's most polluted capital city. Urban Climate, 53, p.101835. (link)

11. Chen, Z., Du, T., Krishnan, N. M. A., and Smedskjaer, M.M., 2024. Enhanced bond switching at complexion layer facilitates high fracture energy of LATP solid-state electrolytes. Journal of Materials Chemistry A. (link)

12. Zaki, M., Jayadeva, J., Mausam, M. and Krishnan, N. M. A., 2024. MaScQA: Investigating Materials Science Knowledge of Large Language Models. Digital Discovery. (link)

13. Pittie, T., Ahmad, S., Singh, H., Rashid, M.M., Adhikari, S., Shetty, S. and Krishnan, N. M. A., 2023. A combined experimental and numerical analysis framework for the design of aluminum windows. Journal of Building Engineering, p.108259. (link)

14. Acharya, A., Chanda, B., Saminathan, M., Perumal, S., Jayanthi, K., Annapurna, K., Krishnan, N. M. A., Gahtori, B., Naskar, M.K., Ghosh, S. and Allu, A.R., 2024. Influence of metal organic framework glasses on thermoelectric properties of AgSb0.96Zn0.04Te2 alloy. Journal of Non-Crystalline Solids, 627, p.122816. (link)

2023 (19)

1. Zaki, M., Jan, A., Krishnan, N. M. A. and Mauro, J.C., 2023. Glassomics: An omics approach toward understanding glasses through modeling, simulations, and artificial intelligence. MRS Bulletin, pp.1-14. (link)

2. Sahoo, S., Khan, Z., Mannan, S., Tiwari, U., Ye, Z., Krishnan, N. M. A., and Gosvami, N.N., 2023. Superlubricity and Stress-Shielding of Graphene Enables Ultra Scratch-Resistant Glasses. ACS Applied Materials & Interfaces. (link)

3. Rashid, M.M., Chakraborty, S. and Krishnan, N. M. A., 2023. Revealing the predictive power of neural operators for strain evolution in digital composites. Journal of the Mechanics and Physics of Solids, 181, p.105444 (link)

4. Gangareddy, J., Rudra, P., Chirumamilla, M., Ganisetti, S., Kasimuthumaniyan, S., Sahoo, S., Jayanthi, K., Rathod, J., Soma, V.R., Das, S., Gosvami, N.N., Krishnan, N. M. A., Pedersen K., Mondal S., Ghosh S., and Allu A. R., 2023. Multi-Functional Applications of H-Glass Embedded with Stable Plasmonic Gold Nanoislands. Small (Weinheim an der Bergstrasse, Germany), pp.e2303688-e2303688. (link)

5. Patra, P., Kumar, J., Margit, F., Keshri, S.R., Bysakh, S., Biswas, K., Gosvami, N.N., Krishnan, N. M. A., Allu, A.R. and Kalyandurg, A., 2023. Effect of Rare Earth (RE3+) Ionic Radii on Transparent Lanthanide-Tellurite Glass-Ceramics: Correlation between ‘Hole-Formalism’and Crystallization. Materials Advances. (link)

6. Oladipo, B., Matos, H., Krishnan, N. M. A., and Das, S., 2023. Integrating Experiments, Finite Element Analysis, and Interpretable Machine Learning to Evaluate the Auxetic Response of 3D Printed Re-entrant Metamaterials. Journal of Materials Research and Technology. (link)

7. Mandal, I., Mannan, S., Wondraczek, L., Gosvami, N.N., Allu, A.R. and Krishnan, N. M. A., 2023. Machine Learning-Assisted Design of Na-Ion-Conducting Glasses. The Journal of Physical Chemistry C. (link)

8. Bishnoi, S., Badge, S. and Krishnan, N. M. A., 2023. Predicting oxide glass properties with low complexity neural network and physical and chemical descriptors. Journal of Non-Crystalline Solids, 616, p.122488. (link)

9. Zaki, M., Sharma, S., Gurjar, S.K., Goyal, R. and Krishnan, N. M. A., 2023. Cementron: Machine learning the alite and belite phases in cement clinker from optical images. Construction and Building Materials, 397, p.132425. (link)

10. Gupta, T., Zaki, M., Krishnan, N. M. A., Mausam., 2023. DiSCoMaT: Distantly Supervised Composition Extraction from Tables in Materials Science Articles. Association of Computational Linguistics. (link)

11. Mannan, S., Zaki, M., Bishnoi, S., Cassar, D.R., Jiusti, J., Faria, J.C.F., Christensen, J.F., Gosvami, N.N., Smedskjaer, M.M., Zanotto, E.D. and Krishnan, N. M. A., 2023. Glass Hardness: Predicting Composition and Load Effects via Symbolic Reasoning-Informed Machine Learning. Acta Materialia. (link)

12. Bihani, V., Manchanda, S., Sastry, S., Ranu, S. and Krishnan, N. M. A., 2023. StriderNET: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes. International Conference on Machine Learning (ICML). (link)

13. Lyngdoh, G., Krishnan, N. M. A., and Das, S., 2023. Machine learning guided design of microencapsulated phase change materials-incorporated concretes for enhanced freeze-thaw durability. Cement and Concrete Composites, 140, p.105090. (link)

14. Bishnoi, S., Bhattoo, R., Jayadeva, J., Ranu, S. and Krishnan, N. M. A., 2023. Enhancing the inductive biases of graph neural ode for modeling physical systems. In The Eleventh International Conference on Learning Representations (ICLR). (link)

15. Singla, S., Mannan, S., Zaki, M. and Krishnan, N. M. A., 2023. Accelerated design of chalcogenide glasses through interpretable machine learning for composition–property relationships. Journal of Physics: Materials, 6(2), p.024003. (link)

16. Pittie, T., Kartikeya, K., Bhatnagar, N., Krishnan, N. M. A., Senthil, T. and Rajan, S.D., 2023. Building a predictive soft armor finite element model combining experiments, simulations, and machine learning. Journal of Composite Materials, 57(9), pp.1599-1615. (link)

17. Bhattoo, R., Ranu, S. and Krishnan, N. M. A., 2023. Learning the dynamics of particle-based systems with Lagrangian graph neural networks. Machine Learning: Science and Technology. (link)

18. Bhattoo, R., Bishnoi, S., Zaki, M. and Krishnan, N.M.A., 2023. Understanding the Compositional Control on Electrical, Mechanical, Optical, and Physical Properties of Inorganic Glasses with Interpretable Machine Learning. Acta Materialia, p.118439. (link)

19. Christensen, J.F., Krishnan, N.M.A., Bauchy, M. and Smedskjaer, M.M., 2023. Indenting glasses with indenters of varying stiffness and sharpness. Journal of Non-Crystalline Solids, 603, p.122111. (link)

2022 (17)

1. Rashid, M.M., Pittie, T., Chakraborty, S. and Krishnan, N.M.A., 2022. Learning the stress-strain fields in digital composites using fourier neural operator. iScience, p.105452. (link)

2. Bhattoo, R., Ranu, S. and Krishnan, N.M.A., 2022. Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network. Proceedings of Neural Information Processing Systems. (Spotlight) (link)

3. Thangamuthu, A., Kumar, G., Bishnoi, S., Bhattoo, R., Krishnan, N.M.A., and Ranu, S., 2022. Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems. In Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track. (link)

4. Zaki, M., Kasimuthumaniyan, S., Sahoo, S., Gosvami, N.N. and Krishnan, N.M.A., 2022. Interpretable Machine Learning Approach for Identifying the Tip Sharpness in Atomic Force Microscopy. Scripta Materialia, 221, p.114965. (link)

5. Kasimuthumaniyan, S., Sahoo, S., Smedskjaer, M.M., Krishnan, N.M.A., and Gosvami, N.N., 2022. Quantifying the densification and shear flow under indentation deformation in borosilicate glasses. International Journal of Applied Glass Science, 13(4), pp.526-538. (link)

6. Pittie, T., Kunwar, G., Das, S., Jain, J. and Krishnan, N.M.A., 2022. Determining the threshold displacement energy of magnesium using molecular dynamics simulations. Bulletin of Materials Science, 45(3), pp.1-7. (link)

7. Zaki, M., Namireddy, S.R., Pittie, T., Bihani, V., Keshri, S.R., Venugopal, V., Gosvami, N.N. and Krishnan, N.M.A., 2022. Natural language processing-guided meta-analysis and structure factor database extraction from glass literature. Journal of Non-Crystalline Solids: X, 15, p.100103. (link)

8. La Plante, E.C., Hsiao, Y.H., Pignatelli, I., Kumar, A., Krishnan, N.M.A., Oey, T., Dobbs, H., Yu, Y., Wang, B., Neithalath, N. and Field, K.G., 2022. Distinct Effects of Irradiation on the Structure and Chemical Reactivity of Silicates and Carbonates. Nuclear Science and Engineering. (link)

9. Jan, A. and Krishnan, N.M.A, 2022. Diminished Diffusion in the Aged Hydrated Gels of Irradiated Borosilicate Glasses. The Journal of Physical Chemistry C, 126(35), pp.15037-15045. (link)

10. Bihani, V., Yadav, A. and Krishnan, N.M.A., 2022. Reactive molecular simulation of shockwave propagation in calcium–silicate–hydrate gels. Journal of Non-Crystalline Solids, 590, p.121677. (link)

11. Gupta, T., Zaki, M. and Krishnan, N.M.A., 2022. MatSciBERT: A materials domain language model for text mining and information extraction. npj Computational Materials, 8(1), pp.1-11. (link)

12. Hu, Y., Liu, H., Yang, K., Zhou, Q., Hoover, C.G., Krishnan, N.M.A., Smedskjaer, M.M., Micoulaut, M., Guo, L. and Bauchy, M., 2022. Topological Constraint Theory of Glass: Counting Constraints by Molecular Dynamics Simulations. Atomistic Simulations of Glasses: Fundamentals and Applications, pp.123-148. (link)

13. Sahoo, S., Khatri, O.P., Krishnan, N.M.A., and Gosvami, N.N., 2022. Graphene Oxide Tribofilms Enhance the Scratch Resistance of Silica Glasses. ACS Applied Nano Materials. (link)

14. Lyngdoh, G.A., Zaki, M., Krishnan, N. M. A., and Das, S., 2022. Prediction of concrete strengths enabled by missing data imputation and interpretable machine learning. Cement and Concrete Composites, p.104414. (link)

15. Keshri, S.R., Mandal, I., Ganisetti, S., Kasimuthumaniyan, S., Kumar, R., Gaddam, A., Shelke, A., Ajithkumar, T.G., Gosvami, N.N., Krishnan, N. M. A., and Allu, A.R., 2022. Elucidating the Influence of Structure and Ag+-Na+ Ion-Exchange on Crack-Resistance and Ionic conductivity of Na3Al1. 8Si1. 65P1. 8O12 Glass Electrolyte. Acta Materialia, p.117745. (link)

16. Zaki, M., Venugopal, V., Bhattoo, R., Bishnoi, S., Singh, S.K., Allu, A.R. and Krishnan, N.A., 2022. Interpreting the optical properties of oxide glasses with machine learning and Shapely additive explanations. Journal of the American Ceramic Society, 105(6), pp.4046-4057. (link).

17. Lyngdoh, G.A., Kelter, N.K., Doner, S., Krishnan, N. M. A., and Das, S., 2022. Elucidating the auxetic behavior of cementitious cellular composites using finite element analysis and interpretable machine learning. Materials & Design, 213, p.110341. (link)

2021 (16)

1. Chhibber-Goel, J., Malhotra, S., Krishnan, N. M. A. and Sharma, A., 2021. The profiles of first and second SARS-CoV-2 waves in the top ten COVID-19 affected countries. Journal of Global Health Reports, 5, p.e2021082. (link)

2. Kumar, R., Jan, A., Bauchy, M. and Krishnan, N. M. A., 2021. Effect of irradiation on the atomic structure of borosilicate glasses. Journal of the American Ceramic Society, 104(12), pp.6194-6206. (link)

3. Yadav, A. and Krishnan, N. M. A., 2021. Role of steric repulsions on the precipitation kinetics and structure of calcium–silicate–hydrate gels. Soft Matter, 17 (39), 8902-8914. (link)

4. Ranjith, P., Sreevalsa, S., Patra, P., Som, S., Menon, A., Jayanthi, K., Annapurna, K., Krishnan, N. M. A., Allu, A.R. and Das, S., 2021. Realizing cool and warm white-LEDs based on color controllable (Sr,Ba)2Al3O6F: Eu2+ phosphors obtained via a microwave-assisted diffusion method. Physical Chemistry Chemical Physics, 23(28), pp.15245-15256. (link)

5. Keshri, S.R., Ganisetti, S., Kumar, R., Gaddam, A., Illath, K., Ajithkumar, T.G., Balaji, S., Annapurna, K., Nasani, N., Krishnan, N. M. A. and Allu, A.R., 2021. Ionic Conductivity of Na3Al2P3O12 Glass Electrolytes—Role of Charge Compensators. Inorganic Chemistry. (link)

6. Zaki, M., Jayadeva, and Krishnan, N. M. A., 2021. Extracting Processing and Testing Parameters from Materials Science Literature for Improved Property Prediction of Glasses. Chemical Engineering and Processing-Process Intensification, p.108607. (link)

7. Venugopal, V., Sahoo, S., Zaki, M., Agarwal, M., Gosvami, N.N. and Krishnan, N. M. A., 2021. Looking Through Glass: Knowledge Discovery from Materials Science Literature using Natural Language Processing. Patterns, 2(7), 100290. (link) 

8. La Plante, E.C., Hsiao, Y.H., Pignatelli, I., Kumar, A., Krishnan, N. M. A., Oey, T., Dobbs, H., Yu, Y., Wang, B., Neithalath, N. and Field, K.G., 2021. Distinct Effects of Irradiation on the Structure and Chemical Reactivity of Silicates and Carbonates. Nuclear Science and Engineering. (link)

9. Krishnan, N. M. A., Le Pape, Y., Sant, G. and Bauchy, M., 2021. Disorder-induced expansion of silicate minerals arises from the breakage of weak topological constraints. Journal of Non-Crystalline Solids, 564, p.120846. (link)

10. Sharma, V., Zaki, M., Jha, K.N. and Krishnan, N. M. A., 2021. Machine learning-aided cost prediction and optimization in construction operations. Engineering, Construction and Architectural Management. (link)

11. Kasimuthumaniyan, S., Gosvami, N.N. and Krishnan, N. M. A., 2021. Towards understanding the scratchability in functional glasses. Ceramics International. (link)

12. Yang, K., Hu, Y., Li, Z., Krishnan, N. M. A., Smedskjaer, M.M., Hoover, C.G., Mauro, J.C., Sant, G. and Bauchy, M., Analytical Model of the Network Topology and Rigidity of Calcium Aluminosilicate Glasses. Journal of the American Ceramic Society. (link)

13. Cao, Y., Kazembeyki, M., Tang, L., Krishnan, N. M. A., Smedskjaer, M.M., Hoover, C.G. and Bauchy, M., Modeling the Nanoindentation Response of Silicate Glasses by Peridynamic Simulations. Journal of the American Ceramic Society, 2021. (link)

14. Ravinder, R., Venugopal, V., Bishnoi, S., Singh, S., Zaki, M., Grover, H.S., Bauchy, M., Agarwal, M. and Krishnan, N. M. A., Artificial Intelligence and Machine Learning in Glass Science and Technology: 21 Challenges for the 21st Century. International Journal of Applied Glass Science, 2021. (link)

15. Hu, Y., Liu, Z., Yang, K., Krishnan, N. M. A., Smedskjaer, M.M., Sant, G. and Bauchy, M., 2021. Rigidity theory of glass: Determining the onset temperature of topological constraints by molecular dynamics. Journal of Non-Crystalline Solids, 554, p.120614. (link)

16. Bishnoi, S., Ravinder, R., Grover, H. S., Kodamana, H., and Krishnan, N. M. A., Scalable Gaussian processes for predicting the optical, physical, thermal, and mechanical properties of inorganic glasses with large datasets, Materials Advances, 2021. (link) 

2020 (13)

1. Ravinder, R., Singh, S., Bishnoi, S., Jan, A., Sharma, A., Kodamana, H., and Krishnan, N. M. A., An Adaptive, Interacting, Cluster-Based Model For Predicting the Transmission Dynamics of COVID-19, Heliyon, p.e05722, 2020. (link)

2. Lyngdoh, G.A., Li, H., Zaki, M., Krishnan, N. M. A., and Das, S., Elucidating the Constitutive Relationship of Calcium–Silicate–Hydrate Gel using High Throughput Reactive Molecular Simulations and Machine Learning, Scientific Reports, 10, 21336, 2020. (link)

3. Lyngdoh, G.A., Nayak, S., Krishnan, N. M. A., and Das, S. Fracture toughness of fly ash-based geopolymer gels: Evaluations using nanoindentation experiment and molecular dynamics simulation. Construction and Building Materials, 262, p.120797, 2020. (link)

4. Pandikkadavath, M.S., Mangalathu, S., Oinam, R.M., Kumar, P.A., Sahoo, D.R. and Krishnan, N. M. A. Drift Response Evaluation of Buckling-Restrained Braced Frames (BRBFs) under Sequential Seismic Disturbances. In IOP Conference Series: Materials Science and Engineering (Vol. 936, No. 1, p. 012040). IOP Publishing, 2020. (link)

5. Lyngdoh, G.A., Kumar, R., Krishnan, N. M. A., and Das, S. Dynamics of confined water and its interplay with alkali cations in sodium aluminosilicate hydrate gel: insights from reactive force field molecular dynamics. Physical Chemistry Chemical Physics, 22(41), pp.23707-23724, 2020. (link)

6. Ravinder, R., Sridhara, K.H., Bishnoi, S., Grover, H.S., Bauchy, M., Kodamana, H. and Krishnan, N. M. A., Deep learning aided rational design of oxide glasses. Materials Horizons, 2020. (link)

7. Lyngdoh, G.A., Nayak, S., Kumar, R., Krishnan, N. M. A., and Das, S., Fracture toughness of sodium aluminosilicate hydrate (NASH) gels: Insights from molecular dynamics simulations. Journal of Applied Physics, 127(16), p.165107, 2020. (link)

8. Wang, Z., Du, T., Krishnan, N. M. A., Smedskjaer, M.M. and Bauchy, M., On the equivalence of vapor-deposited and melt-quenched glasses. The Journal of Chemical Physics, 152(16), p.164504, 2020. (link)

9. Nayak, S., Ravinder, R., Krishnan, N. M. A., and Das, S., A Peridynamics-Based Micromechanical Modeling Approach for Random Heterogeneous Structural Materials. Materials, 13, 1298, 2020. (link)

10. Kasimuthumaniyan, S., Reddy, A.A., Krishnan, N. M. A. and Gosvami, N.N., Understanding the role of post-indentation recovery on the hardness of glasses: Case of silica, borate, and borosilicate glasses. Journal of Non-Crystalline Solids, 534, p.119955, 2020. (link)

11. Bhaskar, P., Kumar, R., Maurya, Y., Ravinder, R.,Reddy, A.A., Das, S., Gosvami, N.N., Youngman, R.E., Bødker, M.S., Mascaraque, N., Smedskjaer, M.M., Bauchy, M., Krishnan, N. M. A., Cooling rate effects on the structure of 45S5 bioglass: Insights from experiments and simulations. Journal of Non-Crystalline Solids, 534, p.119952, 2020. (link)

12. Ravinder, R., Kumar, A., Kumar, R., Vangla, P. and Krishnan, N. M. A., Irradiation‐induced brittle‐to‐ductile transition in α‐quartz. Journal of the American Ceramic Society, 2020. (link)

13. Ravinder, R., Garg, P. and Krishnan, N. M. A., Glass Transition and Crystallization in Hexagonal Boron Nitride: Crucial Role of Orientational Order. Advanced Theory and Simulations, 2020. (link)

2019 (17)

1. Hsiao, Y.H., Wang, B., La Plante, E.C., Pignatelli, I., Krishnan, N. M. A., Le Pape, Y., Neithalath, N., Bauchy, M. and Sant, G., The effect of irradiation on the atomic structure and chemical durability of calcite and dolomite. npj Materials Degradation, 3(1), pp.1-9, 2019. (link)

2. Ganisetti, S., Gaddam, A., Kumar, R., Balaji, S., Mather, G.C., Pascual, M.J., Fabian, M., Siegel, R., Senker, J., Kharton, V., Guénolé, J., Krishnan, N. M. A., Ferreira, J. M. F., Allu, A. R., Elucidating the formation of Al-NBO bonds, Al-O-Al linkages and clusters in alkaline-earth aluminosilicate glasses based on molecular dynamics simulations. Physical Chemistry Chemical Physics, 2019. (link)

3. Rivera, J., Berjikian, J., Ravinder, R., Kodamana, H., Das, S., Bhatnagar, N., Bauchy, M. and Krishnan, N. M. A., 2019. Glass Fracture upon Ballistic Impact: New Insights from Peridynamics Simulations. Frontiers in Materials, 6, p.239, 2019. (link)

4. Bishnoi, S., Singh, S., Ravinder, R., Bauchy, M., Gosvami, N. N., Kodamana, H. and Krishnan, N. M. A., Predicting Young's modulus of oxide glasses with sparse datasets using machine learning. Journal of Non-Crystalline Solids, 524, p.119643, 2019. (link)

5. Liu, H., Zhang, T., Krishnan, N. M. A., Smedskjaer, M.M., Ryan, J.V., Gin, S. and Bauchy, M., Predicting the dissolution kinetics of silicate glasses by topology-informed machine learning. npj Materials Degradation, 3(1), pp.1-12, 2019. (link)

6. Doner, S., Nayak, S., Senol, K., Shukla, A., Krishnan, N. M. A., Yilmazcoban, I.K. and Das, S., Dynamic compressive behavior of metallic particulate-reinforced cementitious composites: SHPB experiments and numerical simulations. Construction and Building Materials, 227, p.116668, 2019. (link)

7. Dhawan, S., Ghosh, S., Ravinder, R., Bais, S.S., Basak, S., Krishnan, N. M. A., Agarwal, M., Banerjee, M. and Haridas, V., Redox Sensitive Self-Assembling Dipeptide for Sustained Intracellular Drug Delivery. Bioconjugate Chemistry, 2019. (link)

8. Lyngdoh, G.A., Kumar, R., Krishnan, N. M. A. and Das, S., Realistic atomic structure of fly ash-based geopolymer gels: Insights from molecular dynamics simulations. The Journal of Chemical Physics, 151(6), p.064307, 2019. (link) This article was chosen as Editor's pick!

9. Song, W., Li, X., Wang, B., Krishnan, N. M. A., Goyal, S., Smedskjaer, M. M., Mauro, J. C., Hoover, C. G., and Bauchy, M., Atomic picture of structural relaxation in silicate glasses. Applied Physics Letters, 114(23), p.233703, 2019. (link)

10. Yang, K., Xu, X., Yang, B., Cook, B., Ramos, H., Krishnan, N. M. A., Smedskjaer, M. M., Hoover, C. and Bauchy, M., Predicting the Young's Modulus of Silicate Glasses using High-Throughput Molecular Dynamics Simulations and Machine Learning. Scientific reports, 9(1), p.8739, 2019. (link)

11. Liu, H., Tang, L., Krishnan, N. M. A., Sant, G. and Bauchy, M., Structural percolation controls the precipitation kinetics of colloidal calcium–silicate–hydrate gels. Journal of Physics D: Applied Physics, 2019. (link)

12. Ravinder, R., Kumar, R., Agarwal, M. and Krishnan, N. M. A., Evidence of a two-dimensional glass transition in graphene: Insights from molecular simulations. Scientific Reports, 9(1), 4517, 2019. (link)

13. Liu, H., Dong, S., Tang, L., Krishnan, N. M. A., Masoero, E., Sant, G. and Bauchy, M., Long-Term Creep Deformations in Colloidal Calcium–Silicate–Hydrate Gels by Accelerated Aging Simulations. Journal of Colloid and Interface Science, 2019. (link)

14. Krishnan, N. M. A., Ravinder, R., Kumar, R., Le Pape, Y., Sant, G. and Bauchy, M., Density–Stiffness Scaling in Minerals upon Disordering: Irradiation vs. Vitrification. Acta Materialia, 166, 611-617, 2019. (link)

15. Nayak S., Krishnan, N. M. A., Das, S., Fracture response of metallic particulate-reinforced cementitious composites: Insights from experiments and multiscale numerical simulations. Cement and Concrete Composites, 97, 154-165, 2019. (link)

16. Nayak S., Krishnan, N. M. A., Das, S., Microstructure-guided numerical simulation to evaluate the influence of phase change materials (PCMs) on the freeze-thaw response of concrete pavements. Construction and Building Materials, 201, 246-256, 2019. (link)

17. Liu, H., Dong, S., Tang, L., Krishnan, N. M. A., Sant, G., Bauchy, M., Effects of polydispersity and disorder on the mechanical properties of hydrated silicate gels. The Journal of Mechanics and Physics of Solids, 122, 555-565, 2019. (link)

2018 (9)

1. Tang, L., Krishnan, N. M. A., Berjikian, J., Rivera, J., Smedskjaer, M. M., Mauro, J. C., Zhou, W., and Bauchy., Effect of nanoscale phase separation on the fracture behavior of glasses: Toward tough, yet transparent glasses. Physical Review Materials, 2, 113602, 2018. (link)

2. Krishnan, N. M. A., Le Pape, Y., Sant, G. and Bauchy, M., Effect of irradiation on silicate aggregates’ density and stiffness. Journal of Nuclear Materials, 512, 126-136, 2018. (link)

3. Yang, K., Kachmar, A., Wang, B., Krishnan, N. M. A., Balonis, M., Sant, G., Bauchy, M., New Insights into the Atomic Structure of Amorphous TiO2 using Tight-binding Molecular Dynamics. The Journal of Chemical Physics, 149, 094501, 2018. (link)

4. Liu, H., Du, T., Krishnan, N. M. A., Li, H., & Bauchy, M., Topological Optimization of Cementitious Binders: Advances and Challenges. Cement and Concrete Composites, 2018. (link) 

5. Hsiao, Y.H., La Plante, E.C., Krishnan, N. M. A., Dobbs, H.A., Le Pape, Y., Neithalath, N., Bauchy, M., Israelachvili, J.N. & Sant, G.N. Role of Electrochemical Surface Potential and Irradiation on Garnet-type Almandine’s Dissolution Kinetics. The Journal of Physical Chemistry C, 122 (30), 17268–17277, 2018. (link)

6. Wang, M., Krishnan, N. M. A., Wang, B., Smedskjaer, M. M., Mauro, J. C., & Bauchy, M. A New Transferable Interatomic Potential for Molecular Dynamics Simulations of Borosilicate Glasses. Journal of Non-Crystalline Solids, 498, 294–304, 2018. (link) 

7. Yu, Y., Wang, M., Krishnan, N. M. A., Smedskjaer, M. M., Vargheese, K. D., Mauro, J. C., Balonis, M., & Bauchy, M. Hardness of silica glasses: Atomic scale origin of mixed modifier effect. Journal of Non-Crystalline Solids, 489, 16–21, 2018. (link)

8. Krishnan, N.M. A., Mangalathu, S., Smedskjaer, M. M., Tandia, A., Burton, H., & Bauchy, M. Predicting the dissolution kinetics of silicate glasses using machine learning. Journal of Non-Crystalline Solids, 487, 37–45, 2018. (link)

9. Yu, Y., Krishnan, N. M. A., Smedskjaer, M. M., Sant, G., & Bauchy, M. The hydrophilic-to-hydrophobic transition in glassy silica is driven by the atomic topology of its surface. The Journal of Chemical Physics, 148 (7), 074503, 2018. (link)

2017 (12)

1. Krishnan, N. M. A., Wang, B., Le Pape, Y., Sant, G., & Bauchy, M. Irradiation-driven amorphous-to-glassy transition in quartz: The crucial role of the medium-range order in crystallization. Physical Review Materials, 1(5), 053405, 2017. (link)

2. Hsiao, Y. H., La Plante, E. C., Krishnan, N. M. A., Le Pape, Y., Neithalath, N., Bauchy, M., & Sant, G. Effects of irradiation on albite’s chemical durability. The Journal of Physical Chemistry A, 121(41), 7835-7845, 2017. (link)

3. Krishnan, N. M. A., & Ghosh, D. Mechanics of Metal-Nanocomposites at Multiple Length Scales: Case of Al-BNNT. Journal of Nanomechanics and Micromechanics, 7(4), 04017014, 2017. (link)

4. Krishnan, N. M. A., Wang, B., Sant, G., Phillips, J. C., & Bauchy, M. Revealing the Effect of Irradiation on Cement Hydrates: Evidence of a Topological Self- Organization. ACS Applied Materials & Interfaces, 9(37), 32377-32385, 2017. (link)

5. Li, X., Song, W., Yang, K., Krishnan, N. M. A., Wang, B., Smedskjaer, M. M., Mauro, J. C., Sant, G., Balonis, M., & Bauchy, M. Cooling rate effects in sodium silicate glasses: Bridging the gap between molecular dynamics simulations and experiments. The Journal of Chemical Physics, 147(7), 074501, 2017. (link)

6. Chandra, A., Krishnan, N. M. A., Patra, P. K., & Ghosh, D. Coaxial Boron-Nitride/Carbon Nanotubes as a Potential Replacement for Double-Walled Carbon Nanotubes for High Strain Applications. Journal of Nanoscience and Nanotechnology, 17(8), 5252-5260, 2017. (link)

7. Krishnan, N. M. A., Wang, B., Yu, Y., Le Pape, Y., Sant, G., & Bauchy, M. Enthalpy landscape dictates the irradiation-induced disordering of quartz. Physical Review X, 7(3), 031019, 2017. (link)

8. Bauchy, M., Wang, M., Yu, Y., Wang, B., Krishnan, N. M. A., Masoero, E., Ulm, F-J., & Pellenq, R. Topological Control on the Structural Relaxation of Atomic Networks under Stress. Physical Review Letters, 119(3), 035502, 2017. (link)

9. Krishnan, N. M. A., Wang, B., Le Pape, Y., Sant, G., & Bauchy, M. Irradiation-vs. vitrification-induced disordering: The case of 𝜶-quartz and glassy silica. The Journal of Chemical Physics, 146(20), 204502, 2017. (link)

10. Wang, B., Krishnan, N. M. A., Yu, Y., Wang, M., Le Pape, Y., Sant, G., & Bauchy, M. Irradiation-induced topological transition in SiO 2: Structural signature of networks' rigidity. Journal of Non-Crystalline Solids, 463, 25-30, 2017. (link)

11. Krishnan, N. M. A., & Ghosh, D. Buckling analysis of cylindrical thin-shells using strain gradient elasticity theory. Meccanica, 52(6), 1369-1379, 2017. (link)

12. Wang, M., Wang, B., Krishnan, N. M. A., Yu, Y., Smedskjaer, M. M., Mauro, J. C., Sant, G., & Bauchy, M. Ion exchange strengthening and thermal expansion of glasses: Common origin and critical role of network connectivity. Journal of Non-Crystalline Solids, 455, 70-74, 2017. (link)

2016 and before (4)

1. Krishnan, N. M. A., Wang, B., Falzone, G., Le Pape, Y., Neithalath, N., Pilon, L., Bauchy, M., & Sant, G. Confined Water in Layered Silicates: The Origin of Anomalous Thermal Expansion Behavior in Calcium-Silicate-Hydrates. ACS Applied Materials & Interfaces, 8(51), 35621-35627, 2016. (link)

2. Krishnan, N. M. A., & Ghosh, D. A novel method for studying the buckling of nanotubes considering geometrical imperfections. Applied Physics A, 117(2), 945-953, 2014. (link)

3. Krishnan, N. M. A., & Ghosh, D. Defect induced plasticity and failure mechanism of boron nitride nanotubes under tension. Journal of Applied Physics, 116(4), 044313, 2014. (link)

4. Krishnan, N. M. A., & Ghosh, D. Chirality dependent elastic properties of single-walled boron nitride nanotubes under uniaxial and torsional loading. Journal of Applied Physics, 115(6), 064303, 2014. (link)

Conference Presentations: (71)

1. Kasimuthumaniyan, S., Sahoo, S., Amarnath Reddy, A., Krishnan, N. M. A., & Gosvami, N. N. Scratch Damage Evolution and Wear Behavior of Ion-exchanged Sodium Aluminophosphosilicate Glasses. IndiaTrib-2022, New Delhi, 2022

2. Kasimuthumaniyan, S., Sahoo, S., Smedskjaer, M. M., Gosvami, N. N., & Krishnan, N. M. A. Study of the Indentation Deformation Mechanisms in Borosilicate Glasses. 26th International Congress on Glass, Berlin, Germany, 2022 

3. Jan, A., Krishnan, N. M. A. Diminished Diffusion in the Aged Hydrated Gels of Irradiated Borosilicate Glasses. 2022 MRS Fall Meeting & Exhibit, Boston, USA. 2022 

4. Jan, A., Krishnan, N. M. A. Diminished Diffusion in the Aged Hydrated Gels of Irradiated Borosilicate Glasses. Materials Science and Technology (MS&T) 2022, Pittsburgh, USA, 2022 

5. Jan, A., Krishnan, N. M. A. Molecular dynamics simulation of tellurite glasses. Materials Science and Technology (MS&T) 2022, Pittsburgh, USA, 2022 

6. Jan, A., Krishnan, N. M. A. Diminished Diffusion in the Aged Hydrated Gels of Irradiated Borosilicate Glasses. Glass and Optical Materials Division Annual Meeting (GOMD), Baltimore, MD, USA. 2022 

7. Ravinder, R. & Krishnan, N. M. A. Lagrangian and Hamiltonian Graph Neural Networks for Robust Molecular Simulations. XXX International Materials Research Congress (IMRC2022) and International Conference on Advanced Materials (ICAM2021), Cancun, Mexico, 2022 

8. Ravinder, R. & Krishnan, N. M. A. Understanding the Compositional Control on Electrical, Mechanical, Optical, And Physical Properties of Inorganic Glasses with Interpretable Machine Learning. XXX International Materials Research Congress (IMRC2022) and International Conference on Advanced Materials (ICAM2021), Cancun, Mexico, 2022 

9. Ravinder, R. & Krishnan, N. M. A. PeriDyn: A Peridynamics Package Written in Julia Programming Language. 11th European Solid Mechanics Conference, NUI, Galway, Ireland, 2022.

10. Ravinder, R. & Krishnan, N. M. A. Learning Quantum-accuracy Interatomic Potential for Silica Using Lagrangian Graph Neural Networks. Glass and Optical Materials Division Annual Meeting (GOMD), Baltimore, MD, USA. 2022 

11. Zaki, M., Krishnan, N. M. A., & Jayadeva, J. Predicting electrical properties of Glasses as a function of composition and wavelengths. Glass and Optical Materials Division Annual Meeting (GOMD), Baltimore, MD, USA. 2022.

12. Zaki, M., Krishnan, N. M. A, & Jayadeva, J. Predicting Vickers Hardness of Glasses as a function of processing parameters. 26th International Congress on Glass, Berlin, Germany, 2022.

13. Zaki, M., Krishnan, N. M. A, & Jayadeva, J. Predicting Optical properties of Glasses as a function of testing parameters . 26th International Congress on Glass, Berlin, Germany, 2022.

14. Zaki, M., Krishnan, N. M. A, & Jayadeva, J. Machine Learning Based Predictions and Explanations of Glasses Properties as a Function of Composition, Testing, and Processing Parameters (Poster). Şişecam 37th International Glass Conference, Istanbul, Turkey, 2022.

15. Zaki, M., Jayadeva, J., & Krishnan, N. M. A. Cementron: Cement clinker microstructure segmentation using machine learning. 2022 MRS Fall Meeting & Exhibit, Boston, USA. 2022.

16. Zaki, M. & Krishnan, N. M. A. Accelerated materials discovery using artificial intelligence and machine learning. 2nd Global Road Construction and Safety Conference, New Delhi, 2022.

17. Sahoo, S., Tiwari, U., Kaware, R. R., Mannan, S., Gosvami, N. N., & Krishnan, N. M. A. A Molecular Dynamics Study of the Scratch-Induced Damage in Graphene-Coated Silica Glass. 11th International Conference on Industrial Tribology (IndiaTrib-2022), New Delhi, 2022.

18. Sahoo, S., Khatri, O. P., Krishnan, N. M. A., & Gosvami, N. N. Minimizing the Scratch Damage of Silica Glasses via In Situ Deposition of Graphene Oxide Tribofilms. 11th International Conference on Industrial Tribology (IndiaTrib-2022), New Delhi, 2022.

19. Sahoo, S., Khatri, O. P., Krishnan, N. M. A., & Gosvami, N. N. Enhancing Scratch Resistance of Silica Glass via Self-Generated Tribofilms from Graphene Oxide Aqueous Dispersions. 26th International Congress on Glass (ICG), Berlin, 2022.

20. Sahoo, S., Tiwari, U., Kaware, R. R., Mannan, S., & Gosvami, N. N., Krishnan, N. M. A. Studying the Scratch-Induced Damage of Silica Glass by Molecular Dynamics Simulations. 26th International Congress on Glass (ICG), Berlin, 2022.

21. Rashid, M.M., Pittie, T., Chakraborty, S., & Krishnan, N. M. A. Learning Stress-Strain fields in digital composites using Fourier Neural Operator. 2022 MRS Fall Meeting & Exhibit, Boston, USA. 2022

22. Mannan, S., Gosvami, N. N., & Krishnan, N. M. A. Understanding the load dependency of Vickers hardness of glass using machine learning. 11th International Conference on Industrial Tribology (IndiaTrib-2022), New Delhi, 2022.

23. Mannan, S., Gosvami, N. N., & Krishnan, N. M. A. , Study of Scratch Mechanism in Oxide Glasses Using PeriDynamics. 11th International Conference on Industrial Tribology (IndiaTrib-2022), New Delhi, 2022.

24. Kasimuthumaniyan, S., Sahoo, S., Smedskjaer, M. M., Gosvami, N. N., & Krishnan, N. M. A. Composition-dependent Indentation Deformation in Borosilicate Glasses. 14th Pacific Rim Conference on Ceramic and Glass Technology (PACRIM) with 2021 Glass & Optical Materials Division Annual Meeting (GOMD), Vancouver, 2021

25. Kasimuthumaniyan, S., Gosvami, N. N., & Krishnan, N. M. A. Influence of Post-indentation Recovery on the Hardness of Oxide Glasses. 14th Pacific Rim Conference on Ceramic and Glass Technology (PACRIM) with 2021 Glass & Optical Materials Division Annual Meeting (GOMD), Vancouver, 2021. 

26. Ravinder, R., Bishnoi, S., Zaki, M. & Krishnan, N. M. A. Decoding the Genome of Inorganic Glasses using Interpretable Machine Learning. 14th Pacific Rim Conference on Ceramic and Glass Technology (PACRIM) with 2021 Glass & Optical Materials Division Annual Meeting (GOMD), Vancouver, 2021. 

27. Ravinder, R. & Krishnan, N. M. A. Molecular Dynamics Simulation Using Graph Neural Networks. MRS Fall Meeting 2021, USA.

28. Ravinder, R., Bishnoi, S., Zaki, M. & Krishnan, N. M. A. Understanding the Composition-property Relationship of Glasses Using Interpretable Machine Learning. Materials Science and Technology (MS&T) 2021, Columbus, Ohio, USA, 2021

29. Zaki, M., Jayadeva, J. & Krishnan, N. M. A. Extracting the Synthesis and Processing Protocols from Materials Science Literature for Improved Property Prediction. 14th Pacific Rim Conference on Ceramic and Glass Technology (PACRIM) with 2021 Glass & Optical Materials Division Annual Meeting (GOMD), Vancouver, 2021.

30. Zaki, M., Jayadeva, J. & Krishnan, N. M. A. Understanding the optical properties of glasses using interpretable machine learning. 14th Pacific Rim Conference on Ceramic and Glass Technology (PACRIM) with 2021 Glass & Optical Materials Division Annual Meeting (GOMD), Vancouver, 2021.

31. Zaki, M., Agarwal, A., Ravinder, R. & Krishnan, N. M. A. Predicting normal and anomalous glasses directly from the indent images using machine learning. 14th Pacific Rim Conference on Ceramic and Glass Technology (PACRIM) with 2021 Glass & Optical Materials Division Annual Meeting (GOMD), Vancouver, 2021. 

32. Zaki, M., Agarwal, A., Ravinder, R. & Krishnan, N. M. A. Predicting Glass Behaviour from Optical Microscopy Images Using Interpretable Machine Learning. Materials Science and Technology (MS&T) 2021, Columbus, Ohio, USA, 2021

33. Zaki, M., Venugopal, V., Ravinder, R., Bishnoi, S., Singh, S. K., Reddy, A. A., Jayadeva, J. & Krishnan, N. M. A. Elucidating Compositional Governance of Optical Properties Oxide Glasses Using Interpretable Machine Learning. Materials Science and Technology (MS&T) 2021, Columbus, Ohio, USA, 2021 

34.  Yadav, A. & Krishnan, N. M. A. Effect of polydispersity on the fracture properties of calcium–silicate–hydrate gel. Materials Science and Technology (MS&T) 2021, Columbus, Ohio, USA, 2021 

35.  Yadav, A., Bihani, V., Krishan, N. M. A. Study of Silica Glass Structural Properties under Compression Shockwave Using Reactive Force Field. Materials Science & Technology, Ohio, 2021. 

36.  Yadav, A., Bihani, V., & Krishnan, N. M. A. Study of silica glass structural properties under compression shockwave using reactive force field: molecular dynamics simulation. 14th Pacific Rim Conference on Ceramic and Glass Technology (PACRIM) with 2021 Glass & Optical Materials Division Annual Meeting (GOMD), Vancouver, 2021. 

37.  Bihani, V., Yadav, A., & Krishnan, N. M. A. Sodium silicate glass structural properties under compression shockwave14th Pacific Rim Conference on Ceramic and Glass Technology (PACRIM) with 2021 Glass & Optical Materials Division Annual Meeting (GOMD), Vancouver, 2021. 

38.  Bishnoi, S., Ravinder, R., & Krishnan, N. M. A. Developing physics-based descriptors for property prediction in oxide glasses. Materials Science and Technology (MS&T) 2021, Columbus, Ohio, USA, 2021 

39.  Bishnoi, S., Ravinder, R., Kodamana, H. & Krishnan, N. M. A. Scalable Gaussian processes for predicting the optical, physical, thermal, and mechanical properties of inorganic glasses using compositions for large datasets. Materials Science and Technology (MS&T) 2021, Columbus, Ohio, USA, 2021 

40.  Sahoo, S., Khatri, O. P., Krishnan, N. M. A., Gosvami, N. N. Dispersion-Derived Tribological Coatings to Enhance Scratch Resistance of Glasses. 14th Pacific Rim Conference on Ceramic and Glass Technology (PACRIM) with 2021 Glass & Optical Materials Division Annual Meeting (GOMD), Vancouver, 2021. 

41.  Sahoo, S., Khatri, O. P., Krishnan, N. M. A., Gosvami, N. N. Self-Generated Tribo-Coatings on Glass from Nano-Dispersions in Aqueous Medium. Materials Science and Technology (MS&T) 2021, Columbus, Ohio, USA, 2021 

42. Krishnan, N. M. A. Python for Glass Genomics (PyGGi): A Machine Learning Package to Predict the Properties of Glasses. Materials Science & Technology (MS&T), Portland, 2019.

43. Singh, S., Bishnoi, S., Ravinder, R., Kodamana, H., & Krishnan, N. M. A. Machine learning to predict Elastic properties of glasses. Materials Science & Technology (MS&T), Portland, 2019.

44. Bhaskar, P., Maurya, Y., Kumar, R., Ravinder, R., & Krishnan, N. M. A. Cooling rate effects on the structure of 45S5 bioglass. Materials Science & Technology (MS&T), Portland, 2019.

45. Rivera, J., Berjikian, J., Bauchy, M., & Krishnan, N. M. A. Peridynamics modeling of impact-induced crack in glass. Materials Science & Technology (MS&T), Portland, 2019.

46. Krishnan, N. M. A. Designing materials for nuclear applications: Insights from atomistic modeling and deep learning. MRSI Colloquium, IGCAR Kalpakkam, 2019.

47. Goyal, N., Saxena, D., Ravinder, R., Kodamana, H., & Krishnan, N. M. A. Deep learning based prediction of elastic properties of glasses. EMI International Conference, Lyon, 2019.

48. Bishnoi, S., Singh, S., Ravinder, R., Kodamana, H., & Krishnan, N. M. A. Predicting Young’s modulus of glasses using Gaussian process regression. EMI International Conference, Lyon, 2019.

49. Krishnan, N. M. A. Role of Weak Constraints in the Disorder-induced Swelling of Silicate Minerals, National Seminar on Crystallography, BARC, 2019.

50. Rathod, P., Ravinder, R., Kumar, R., & Krishnan, N. M. A. Reactive simulation of shock propagation in sodium silicate glasses. International Congress on Glass, Boston, 2019.

51. Kumar, A., Ravinder, R., Kumar, R., & Krishnan, N. M. A. Irradiation induced brittle-to-ductile transition in α-quartz. International Congress on Glass, Boston, 2019.

52. Singh, S., Bishnoi, S., Ravinder, R., Kodamana, H., & Krishnan, N. M. A. Machine learning based prediction of Young’s modulus for glasses with sparse data. International Congress on Glass, Boston, 2019.

53. Bhaskar, P., Maurya, Y., Kumar, R., Ravinder, R., & Krishnan, N. M. A. Cooling rate effects on the structure of 45S5 bioglass. International Congress on Glass, Boston, 2019.

54. Krishnan, N. M. A., Pape Y.L., Sant G., & Bauchy, M. Role of weak constraints in the disorder-induced swelling of silicates. International Congress on Glass, Boston, 2019.

55. Krishnan, N. M. A. Precipitation kinetics and mechanics of calcium-silicate-hydrates gel. International Conference on Multiscale Simulation & Mathematical Modelling of Complex Biological Systems, JNU, 2019

56. Ravinder, R., & Krishnan, N. M. A. Evidence of two-dimensional glass transition in graphene. CompFlu 2018, IIT Roorkee, 2018.

57. Krishnan, N. M. A., & Bauchy, M. Mesoscale mechanics of polydisperse gels. CompFlu 2018, IIT Roorkee, 2018.

58. Rivera, J., Berjikian, J., Bauchy, M., & Krishnan, N. M. A. Impact induced crack patterns in brittle materials: Evidence of a power-law dependence with fracture energy. European Solid Mechanics Conference, Bologna, 2018.

59. Krishnan, N. M. A., Mangalathu, M., Tandia, A., Smedskjaer, M., Burton, H., Bauchy, M., Machine learning based prediction of dissolution kinetics in silicate glasses. Glass and Optimal Materials Division Meeting, San Antonio, 2018.

60. Krishnan, N. M. A., Wang, B., Bauchy, M., Topological nanoengineering of cement hydrates. Glass and Optimal Materials Division Meeting, San Antonio, 2018. 

61. Rivera, J., Berjikian, J., Bauchy, M., & Krishnan, N. M. A. Impact induced crack patterns in brittle materials: A peridynamics based investigation. Glass and Optimal Materials Division Meeting, San Antonio, 2018. 

62. Krishnan, N. M. A., Wang,  B., Le Pape, Y., Sant, G., & Bauchy, M. Irradiation-Induced Damage is Driven by Weak Topological Constraints. Glass and Optimal Materials Division Meeting, Hawaii, 2017.  

63. Krishnan, N. M. A., Wang, M., Wang, B., Mauro, J. C., Sant, G., & Bauchy, M. Influence of Irradiation on the Structure and Corrosion of Borosilicate Glasses. Glass and Optimal Materials Division  Meeting, Hawaii, 2017. 

64. Krishnan, N. M. A., Wang, B., Le Pape, Y., Sant, G., & Bauchy, M. Irradiation-Induced Damage in Quartz: The Critical Role of the Enthalpy Landscape. Glass and Optimal Materials Division Meeting, Hawaii, 2017. 

65. Krishnan, N. M. A., Wang, B., Sant, G., & Bauchy, M. Nano-Engineering of Cementitious Materials towards Improved Nuclear Wasteforms, 12th Pacific Rim Conference on Ceramic and Glass Technology, Hawaii, 2017. 

66. Yu, Y., Krishnan, N. M. A., Smedskjaer, M. M., Mauro, J. C., & Bauchy, M. Origin of the Mixed Alkaline Earth Effect on the Hardness of Silicate Glasses, 12th Pacific Rim Conference on Ceramic and Glass Technology, Hawaii 2017.

67. Krishnan, N. M. A.,  Wang, B., Falzone, G., Neithalath, N., Le Pape, Y., Bauchy, M., & Sant, G. The origin of anomalous thermal expansion behavior in calcium-silicate- hydrates. Internation Conference on  Advances in Construction Materials and Systems, Chennai, 2017.

68. Krishnan, N. M. A., & Ghosh, D. Effect of temperature, strain-rate and prestress on single-walled carbon nanotubes under axial loading, Seventh M.I.T. Conference on Computational Fluid and Solid Mechanics, Boston, 2013. 

69. Krishnan, N. M. A., & Ghosh, D. Stochastic buckling analysis of carbon nanotubes. International Conference on Structural Safety and Reliability, New York, 2013. 

70. Krishnan, N. M. A., & Ghosh, D. Variation of stress-strain ratio for single-walled carbon nanotubes under compression. Asian Conference on Mechanics of Functional Materials and Structures, Delhi, 2012.  

71. Krishnan, N. M. A., & Ghosh, D. A probabilistic study of carbon nanotube buckling. International Congress on Computational Mechanics and Simulation, Hyderabad, 2012.