Areas of specialization: 

I. Computational modelling (Density Functional Theory, Molecular Dynamics) 

II. First‑Principles Transport and Light–Matter Dynamics in Functional Materials

III. Energy storage (Rechargeable Batteries, Hydrogen Fuel)

IV. Damping (Internal Friction) in Nanoresonators 

Current areas of research:

A. Mechanics of 2D and other nanomaterials using atomistic simulations and machine learning

B. Computational screening of electrode materials for alkali-ion, Li-S, and Li-air batteries 

C. Design and discovery of solid-state electrolytes 

D. Materials for hydrogen storage 

E. Energy dissipation in nanoresonators 

Advanced Simulations for Carrier and Thermal Transport Optimization:

Employing advanced many-body perturbation theory and Boltzmann Transport Equation (BTE) formalisms, we evaluate carrier mobility, thermal conductivity, and thermoelectric efficiency in a system-agnostic framework. Using GW-level precision, we compute strain-dependent transport properties to understand how structural perturbations influence performance. We also model non-equilibrium steady-state light–matter interactions to uncover photocarrier dynamics relevant for optoelectronic applications. By integrating strain effects, photon coupling, and thermal transport, our work offers predictive insights into designing materials with optimized charge and heat transport properties. This is currently a major focus area in our group, and we welcome (with a background in Physics) motivated individuals interested in joining these efforts.  

• Singh, Zimmi, Abhishek Kumar, and Sankha Mukherjee. "Unveiling magnetic transition-driven lattice thermal conductivity switching in monolayer VS2." Nanoscale 17.11 (2025): 6550-6561. 

• Kumar, Praveen, et al. "Harnessing Layer-Controlled Two-dimensional Semiconductors for Photoelectrochemical Energy Storage via Quantum Capacitance and Band Nesting." arXiv preprint arXiv:2502.20107 (2025). 

Materials for advanced rechargeable energy storage: 

With the rapid growth in potential material candidates, especially those with complex chemistries and defect landscapes, experimental discovery alone is time-consuming and costly. We address this challenge through atomistic simulations that combine ab initio molecular dynamics and quasi-harmonic analysis to probe ion transport, mechanical, vibrational, and electronic properties at finite temperatures. To overcome length and time scale limitations, we are also developing machine learning interatomic potentials, enabling large-scale modelling of defects such as vacancies, grain boundaries, interfaces, and stacking faults. This integrated, multiscale approach accelerates the discovery and understanding of solid electrolytes critical to the advancement of Li, Na, K, and Mg-based batteries. We are actively looking for motivated individuals interested in joining these efforts.

• Maithani, V., Das, S., & Mukherjee, S. (2024). Cooperative Transport of Lithium in Disordered Li10MP2S12 (M= Sn, Si) Electrolytes for Li-Ion Batteries. Chemistry of Materials, 36(21), 10537-10551. 

• S. Mukherjee, L. Kavalsky, K. Chattopadhyay, and C. V. Singh, “Dramatic improvement in the performance of graphene as Li/Na battery anodes with suitable electrolytic solvents,” Carbon, vol. 161, pp. 570–576, 2020.

• M. Jiang et al., “Materials perspective on new lithium chlorides and bromides: insights into thermo-physical properties,” Physical Chemistry Chemical Physics, vol. 22, no. 39, pp. 22758–22767, 2020.

• S. Mukherjee, L. Kavalsky, and C. V. Singh, “Ultrahigh storage and fast diffusion of Na and K in blue phosphorene anodes,” ACS applied materials & interfaces, vol. 10, no. 10, pp. 8630–8639, 2018.

• S. Mukherjee, L. Kavalsky, K. Chattopadhyay, and C. V. Singh, “Adsorption and diffusion of lithium polysulfides over blue phosphorene for Li–S batteries,” Nanoscale, vol. 10, no. 45, pp. 21335–21352, 2018.

• A. Gao, S. Mukherjee, I. Srivastava, M. Daly, and C. V. Singh, “Atomistic Origins of Ductility Enhancement in Metal Oxide Coated Silicon Nanowires for Li‐Ion Battery Anodes,” Advanced Materials Interfaces, vol. 4, no. 23, p. 1700920, 2017.

Mechanical properties of 2D materials: 

Since the synthesis of graphene, two-dimensional (2D) materials have revolutionized the field of materials science. While graphene is one of the strongest materials known to mankind with a strength of 100 GPa, it suffers from a poor fracture toughness (GIC~ 16 J/m2 ). Moreover, other than graphene, carbon has more than 30 polymorphs for which there exists no structure-property relationships. Finally, in real-life applications graphene-based systems are often subjected to a large cyclic stress. However, we do not know yet if these atomically thin materials are immune from fatigue failure? If not, what is the fatigue life and underlying damage mechanisms? 

• Anuragi, A., Das, A., Baski, A., Maithani, V., & Mukherjee, S. (2024). Machine learning predicted inelasticity in defective two-dimensional transition metal dichalcogenides using SHAP analysis. Physical Chemistry Chemical Physics, 26(21), 15316-15331. 

• Cui, T., Mukherjee, S., Onodera, M., Wang, G., Kumral, B., Islam, A., ... & Filleter, T. (2022). Mechanical reliability of monolayer MoS2 and WSe2. Matter, 5(9), 2975-2989. 

• S. Mukherjee, R. Alicandri, and C. V. Singh, “Strength of graphene with curvilinear grain boundaries,” Carbon, vol. 158, pp. 808–817, 2020.

• T. Cui et al., “Fatigue of graphene,” Nature materials, vol. 19, no. 4, pp. 405–411, 2020.

• C. Cao et al., “Nonlinear fracture toughness measurement and crack propagation resistance of functionalized graphene multilayers,” Science advances, vol. 4, no. 4, p. eaao7202, 2018.

• T. Cui et al., “Mechanical reliability of monolayer MoS2 and WSe2,” Matter, vol. 5, no. 9, pp. 2975–2989, 2022.

Internal friction in Nanoresonators: 

Silicon-based nanoresonators are common, operate at very high frequencies (in the GHz regime) and are ultrasensitive. The performance of these devices can be further improved by reducing materials damping and internal friction. Difficulties in studying internal friction in nanoresonators using experiments arise from their small size and the simultaneous existence of several mechanisms. As a result, despite of a lot of research activity a detailed microscopic understanding of the mechanisms of material damping is still illusive. In this pursuit, MD simulations can be particularly empowering, but it is not clear what are the methods for simulating damping using MD? Furthermore, what are the mechanisms of material damping in single-crystal silicon, amorphous silicon, and amorphous silica nanoresonators? 

• S. Mukherjee, J. Song, and S. Vengallatore, “Atomistic simulations of material damping in amorphous silicon nanoresonators,” Modelling and Simulation in Materials Science and Engineering, vol. 24, no. 5, p. 055015, 2016.

• Z. Nourmohammadi, S. Mukherjee, S. Joshi, J. Song, and S. Vengallatore, “Methods for atomistic simulations of linear and nonlinear damping in nanomechanical resonators,” Journal of Microelectromechanical Systems, vol. 24, no. 5, pp. 1462–1470, 2015.