Raghavendra Meena

Computational materials scientist with expertise in DFT, AIMD, microkinetic modeling, and machine learning for sustainable catalysis and materials design.

Education

PhD Computational Chemistry

Wageningen University & Research, Netherlands

MSc Computational Materials Science

Sorbonne Université, France

BS-MS Chemistry & Physics

IISER Pune, India

Research Experience

Postdoctoral Researcher

Wageningen University & Research

  • Identified strategies to improve CO2 hydrogenation over Ce6O12/Cu-based catalysts
  • Used machine-learned potentials (MLPs) in designing catalysts for CO2 hydrogenation to methanol
  • Created an NLP/LLM-based workflow to automate the slab generation from bulk

Doctoral Researcher

Wageningen University & Research

  • Applied multiscale modeling methodology (DFT, microkinetic modeling, AIMD) to optimize catalytic activity of transition metal carbides (TMCs) for biomass conversion under operando conditions
  • Identified interpretable descriptors of catalytic activity in TMCs using machine learning
  • Fine-tuned MACE and fairchem MLPs for accelerating AIMD simulations of Mo2C-based catalysts
  • Collaborated on experimental projects: mechano-catalytic plastic degradation, RWGS catalysis over a single Cu atom, methane coupling using porous materials (ZSM-5/MFI), electrochemical bromination of methyl levulinate

Master's Thesis Intern

Sorbonne Université, France

  • Established state-of-the-art QMC methodology to quantify magnetic properties of carbon-based materials. Further showed that these results could be reproduced using a low-level DFT+U calculations
  • Demonstrated the narrowest zigzag graphene nanoribbons (zGNRs) as correlated quasi-1D systems with AFM spin ordering (possibly at room temperature). Useful for spintronic device applications
  • Quantified bandgaps and magnetic properties of zGNRs via DFT methods (GGA, mGGA, hybrids)

Research Intern

Indian Institute of Science, India

  • Demonstrated isonitrile coupling mediated by allenic diborenes as an alternative to transition metals (DFT)

Skills

DFT VASP, Quantum ESPRESSO, ASE, GAUSSIAN
QMC VMC, DMC, LRDMC
AIMD VASP, CP2K, PLUMED
Code Python, bash, MATLAB, LaTeX
ML scikit-learn, MACE, fair-chem, SISSO
Tools Git, HPC, Linux, Blender, VMD

Grants & Scholarships

Dutch Research Council HPC grants (12.5mil CPU/50k GPU hrs) - equiv. 200k Euros

Erasmus+ Fellowship (M2), France - 10k Euros

Innovation in Science Pursuit for Inspired Research (INSPIRE) Scholarship, India - 400k INRs

National Talent Search Examination (NTSE) Scholarship, India - 30k INRs

Languages

EnglishProfessional
HindiNative
DutchA2
FrenchA1