Assist. Prof. Dr. Shivam Tripathi | Indian Institute of Technology Kanpur | India
Dr. Shivam Tripathi is a materials engineering researcher and faculty member specializing in atomistic simulations, machine learning–driven materials discovery, and the design of next-generation functional materials. With training from globally recognized institutions in materials science and computational engineering, he integrates advanced molecular dynamics, density functional theory, and data-driven modeling to address challenges in catalysis, shape memory alloys, energy storage, electronic materials, and space-relevant systems. His academic foundation combines rigorous theoretical knowledge with extensive hands-on experience in computational methods, including large-scale molecular dynamics, enhanced sampling, and ab-initio simulations. During his postdoctoral research, he worked on dynamic mechanisms of ammonia synthesis on iron surfaces under operando conditions, unveiling fundamental insights into nitrogen adsorption, dissociation, and poisoning pathways using machine-learning-accelerated simulation frameworks. His doctoral research provided breakthroughs in understanding nanoscale precipitate effects on martensitic transformations, enabling guidelines for designing low-fatigue, ultra-fine-grain shape memory alloys and uncovering mechanisms governing superelasticity and phase transformation behavior. Dr. Tripathi’s research portfolio extends to designing tunable transformations in lightweight alloys, modeling environment-dependent atomic-level properties in complex-concentrated alloys, and unraveling phonon transport mechanisms in nanoscale copper hybrids for nanoelectronics. He has contributed to multiple high-impact publications across catalysis, materials physics, and computational materials science, and his work has been recognized through awards, research honors, and competitive travel grants. His technical expertise includes Python, C, VASP, LAMMPS, PLUMED, Quantum Espresso, TensorFlow, and advanced materials characterization methods. Beyond research, he has contributed significantly to academic service and outreach through leadership roles, mentoring, teaching computational and experimental materials science courses, and developing open-access scientific software tools used by the broader materials community. His contributions reflect a commitment to innovation, academic excellence, and advancing computational materials engineering.
Featured Publications
Perego, S., Bonati, L., Tripathi, S., & Parrinello, M. (2024). How dynamics changes ammonia cracking on iron surfaces. ACS Catalysis, 14(19), 14652–14664.
Tripathi, S., Bonati, L., Perego, S., & Parrinello, M. (2024). How poisoning is avoided in a step of relevance to the Haber–Bosch catalysis. ACS Catalysis, 14, 4944–4950.
Tripathi, S., Vishnu, K. G., Titus, M. S., & Strachan, A. (2020). Tunability of martensitic transformation in Mg–Sc shape memory alloys: A DFT study. Acta Materialia, 189, 1–9.
Tripathi, S., Verma, V., Brown, T. W., & Kulkarni, K. N. (2017). Effect of small amount of manganese on the interdiffusivities in Fe–Al alloys. Journal of Phase Equilibria and Diffusion, 38(2), 135–142.
Tripathi, S., Vishnu, K. G., Titus, M. S., & Strachan, A. (2022). Uncovering the role of nanoscale precipitates on martensitic transformation and superelasticity. Acta Materialia, 229, 117790.
Farnell, M. S., McClure, Z. D., Tripathi, S., & Strachan, A. (2022). Modeling environment-dependent atomic-level properties in complex-concentrated alloys. The Journal of Chemical Physics, 156(11).