Sandeep Kumar Email & Phone Number

Berlin, De

Berlin, Germany

The computation of X-ray absorption (XAS) and resonant inelastic X-ray scattering (RIXS) spectra plays a critical role in elucidating the electronic structure and dynamic properties of inorganic solids. This study leverages the Density Functional Theory (DFT) combined with the Restricted Open-Shell Configuration Interaction Singles (ROCIS) method to accurately simulate XAS and RIXS spectra for a range of inorganic materials, including transition metal oxides, rare earth compounds, and complex oxides.Our computational approach integrates ML/DFT/ROCIS to account for the detailed electronic interactions and core-hole effects crucial for X-ray spectroscopy. The ROCIS method, known for its robust treatment of excited states and core-level spectroscopy, is particularly suited for capturing the intricate nature of core-electron excitations and subsequent inelastic scattering processes in RIXS. The study includes a thorough examination of computational parameters such as the choice of exchange-correlation functional, basis sets, and the treatment of core-hole effects, ensuring comprehensive and accurate spectral simulations.Finally, we will validate our methodology against experimental XAS and RIXS spectra of various prototypical inorganic solids.

Ghent, Flemish Region, Belgium

We have worked on the screening of electrolytes for solid-state Li-ion batteries in experimental collaboration with a large industrial company (Umicore, Belgium). The tool of choice is high-throughput (HT) screening using density-functional theory (DFT), supported by machine learning. Furthermore, solid-state batteries are considered the next generation of batteries, but they still suffer from high interfacial resistance. Challenges include continuous interfacial side reactions, limited electrochemical windows, contact issues, side reactions in moisture, and cracks or pulverization issues. In this direction, structure optimization, energy above the hull, phase stability, average cathode voltage, interface stability, and (electro)-chemical stability have been investigated to discover the new electrolytes for the better performance of solid-state Li-ion batteries.

Department Of Physics And Materials Science, Limpertsberg Campus, Luxembourg

We have worked on high-throughput density functional theory (DFT) methodology and Machine learning to calculate thousands of semiconductor materials' electronic and optical properties and provide detailed information on the strength of the various light-matter interaction mechanisms present in the Infrared (IR) spectral range. The project was an experimental collaboration with an industrial company ( IEE SA Luxembourg)This project aimed to explore new materials that might be suitable to produce cheaper and more efficient cameras for night vision and automatic driving. To handle the big database, we have used numerical methods as well as analytical calculations. Utilizing data Handling and visualization tools such as Python, Machine Learning, Monte Carlo algorithm, Shell Scripting, Matlab, Scilab, FORTRAN, Pandas, Seaborn, Matplotlib, and High-performance computing were important tools to accomplish the projects.

Ramat Gan, Tel Aviv, Israel

We have worked intensely on the theoretical and computational study of Li-ion battery properties using high-level quantum mechanical calculations. This work has been done in collaboration with the experimental group at the Weizmann Institute of Science (WIS), Israel.

Mumbai

In my doctoral work, we have studied the ground state properties of ordered and disordered alloys. In particular, we have focused on how chemical doping affects the electronic, magnetic, and superconducting properties of iron-based superconductors and their substitutional alloys. We have used state-of-the-art DFT calculations by employing the Green's function-based Korringa–Kohn–Rostoker method formulated within atomic sphere approximation (KKR-ASA) to study these superconducting alloys. The coherent potential approximation (CPA), virtual crystal approximation (VCA), and special quasirandom structures (SQS) have been used to account for the disordered on each lattice site. However, one can also study this type of disorder by using supercell calculations, which are generally more time-consuming and computationally expensive calculations. In addition, chemical doping has become an indispensable tool and it can facilitate one in characterization, control, and design of the different properties of materials.

Mumbai, Maharashtra, India

@PM Dimensions Pvt.Ltd.

Doctor Of Philosophy - Phd, Theoretical And Computational Condensed Matter Physics, A

Master Of Technology - Mtech, A