Computational Chemistry · Molecular Physics · FEA, Magnetostatics & Magnetohydrodynamics
%20Physics-MAHE%20Manipal-8B0000){kind=icon}
I'm a physicist moving into computational chemistry. My work connects quantum-chemical calculations with what you can measure in the lab: vibrational spectra, magnetic susceptibility, and transport.
At the continuum scale I work on finite-element analysis (FEA) of magnetostatic fields and magnetohydrodynamics (MHD): how magnetic fields and field gradients act on conducting fluids and dissolved species. Molecular simulation and continuum simulation are two ends of the same problem.
For my B.Sc. (Hons) Physics thesis at Manipal Institute of Applied Physics (minor in Mathematics) I combined three things:
- DFT (ORCA, r²SCAN-3c / CPCM) on aqueous As(III) and As(V) species
- Langevin–Lorentz transport modelling
- FTIR spectroscopy and VSM magnetometry
The goal was to test whether arsenic speciation produces measurable vibrational and magnetic signatures.
Next: a master's in computational molecular science.
- Electronic structure: DFT and composite methods (r²SCAN-3c, PBE0-D4), implicit/explicit solvation, vibrational analysis, magnetic and NMR response properties
- Molecular simulation: Langevin and Brownian dynamics, classical MD in explicit solvent, diffusion and transport coefficients
- Spectroscopy–theory correlation: calculated against experimental IR, peak deconvolution, speciation fingerprints
- FEA and computational electromagnetics: finite-element magnetostatics, field and field-gradient mapping (|B|, B·∇B), mesh-convergence checks against analytical solutions
- Magnetohydrodynamics (MHD): Lorentz-force-driven flow of electrolytes, Hartmann-type channel flow, coupling between magnetic fields and ion transport
- CFD: transport and mixing in aqueous media, linking continuum models to molecular-scale diffusion coefficients
- Cheminformatics and ML for molecules
| Project | What it does | Stack |
|---|---|---|
| arsenic-speciation-dft-md | DFT Opt/Freq of H₃AsO₃, H₂AsO₃⁻, H₂AsO₄⁻ in CPCM water. Calculated vs. experimental IR. Langevin–Lorentz model showing |q|B/ζ ≤ 10⁻⁶ for solvated ions. FTIR and VSM datasets | ORCA 6 · Python · NumPy · pandas |
| FEMM-Data-Plotter | Deconvolutes FEMM magnetostatic |B| profiles into expanded form for chosen domains | Python · FEMM |
| VSManalyser | Processing of vibrating-sample-magnetometry M–H data | Python |
| Cheminformatics → docking notebooks | MolSSI/IQB crash course: molecular representation, BindingDB mining, structure preparation, CNN-scored docking | RDKit · pandas · gnina |
Studying and building on: gnina (CNN-scored docking) · mols2grid · PyChem-Pro (pure-Python MMFF94 and descriptors) · practical_cheminformatics_tutorials
Quantum chemistry: ORCA (Opt/Freq, CPCM, NMR inputs)
FEA and multiphysics: FEMM (magnetostatics, Lua scripting) · Python post-processing of field data
Simulation and numerics: Python (NumPy, SciPy, pandas, Matplotlib) · Jupyter
Cheminformatics and docking: RDKit · gnina
Data and spectroscopy: OriginPro · FTIR peak fitting · VSM M–H analysis
Currently learning: GROMACS / OpenMM · xTB / CREST · CP2K · Elmer FEM · OpenFOAM (mhdFoam)
Research internships, collaborations and M.Sc./PhD conversations in computational chemistry, molecular simulation, FEA/MHD modelling and theoretical spectroscopy.