Soumyakanti Das

Löbdergraben 32 | Room 139
07743 Jena
tel: +49 3641 9-47773

Curriculum Vitae

Education

  • 08/2022-07/2024
    Indian Institute of Technology Mandi | Master of Science (M.Sc.) in Physics | Supervisor: Prof. Arti Kashyap, CGPA: 8.79 (in scale 10)
  • 07/2019–07/2022
    Midnapore College (Autonomous) | B.Sc. (UG) in Physics, minor subject Chemistry | CGPA: 9.07 (in scale 10)

Research Experience

  • 01/2024-06/2024
    High-throughput DFT Calculations of Rare Earth Pnictides | Supervisor: Prof. Arti Kashyap (IIT Mandi, India)      
  • 08/2023-12/2023
    A Simple Machine Learning Model to Predict Electronic Dielectric Constant | Supervisor: Prof. Arti Kashyap  
  • 05/2023–07/2023
    A First-principles Study of Bond Breaking in Thin Films and Bulk PbTe. | Supervisor: Prof. Umesh V. Waghmare (JNCASR, India)   

Research Interests 

  • Density Functional Theory (DFT), Density Functional Embedding Theory, Subsystem DFT, Machine Learning, Condensed Matter Physics, Computational Chemistry, Molecular Dynamics

Digital Skills

  • Python
  • C
  • Quantum Espresso
  • Turbomole
  • Serenity
  • Abinit
  • C++
  • VASP
  • LAMMPS
  • Matlab

Language

  • English
  • Bengali
  • Hindi

PhD project

Modeling and simulations of light-driven processes at inorganic surfaces

This project aims to develop advanced quantum chemical (QC) methodologies using subsystem DFT (sDFT) and DFT-based embedding to investigate light-induced phenomena at inorganic interfaces and membranes. Conventional electronic structure methods face challenges in simulating macroscopic polarization due to high computational demands and limitations in treating low-dimensional systems. These issues arise from the reliance on plane wave-based methods, which require large supercells to avoid artificial interactions between periodic images, making simulations computationally intensive. Traditional slab models also fail to capture essential long-range electrostatic interactions critical for understanding polarization-driven processes. sDFT addresses these limitations by fragmenting complex systems into subsystems, enabling efficient, localized electronic structure calculations while preserving key interactions. By employing Gaussian-type orbitals (GTO) instead of plane waves, this approach provides a more adaptable and computationally efficient framework for studying photoinduced polarization, charge transfer dynamics, and molecular interactions in complex systems.

The key developments of this project are:

  • Develop Non-Additive Kinetic Energy (NAKE)-based sDFT for molecular and periodic systems, ensuring accurate simulations without artificial 3D simulation cells.
  • Implement projector-based sDFT to extend its applicability to strongly correlated systems, such as carbon-based and MOF membranes.
  • Apply sDFT to investigate photoinduced polarization and light-driven processes, including second harmonic generation (SHG) and high harmonic generation (HHG) spectra.
  • Integrate machine learning models to establish robust correlations between molecular photoactive units and macroscopic material properties.

This project will actively collaborate with RP3-RP8 to explore light-responsive phenomena in molecular membranes and inorganic-organic interfaces. Additionally, it will contribute to RP9 and RP11 by providing an advanced computational framework to analyze photoactive materials and correlate molecular interactions with macroscopic functionalities. The project will also engage with RP12 to develop innovative educational resources for theoretical material science.