Raghavendra Meena

Postdoctoral researcher and computational materials scientist with expertise in DFT, AIMD, machine-learning interatomic potentials, microkinetic modelling, and LLM-driven workflow automation for sustainable catalysis and materials design.

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Education

2020 – 2025

Ph.D., Theoretical and Computational Chemistry

Wageningen University & Research, the Netherlands

Defense scheduled: June 22, 2026

Advisors: Prof. Guanna Li, Prof. Harry Bitter, Prof. Han Zuilhof

Thesis: Multiscale Modeling of Molybdenum and Tungsten Carbide Catalysts for Sustainable Biomass Conversion

2019 – 2020

M2, Computational Materials Science

Sorbonne Université, Paris, France

Advisors: Prof. Michele Casula, Prof. Prasenjit Ghosh

Thesis: Magnetic properties of narrow zig-zag graphene nanoribbons from ab initio calculations

2015 – 2020

BS-MS, Chemistry and Physics

Indian Institute of Science Education and Research (IISER) Pune, India

Research Experience

Oct 2025 – Present

Postdoctoral Researcher

Biobased Chemistry & Technology group, Wageningen University & Research

  • Training and validating machine-learning interatomic potentials for CO2 conversion and polymer-degradation systems, generating DFT reference data with VASP and CP2K and refining models through active-learning loops.
  • Developed agent-materials-science, an open-source LLM-driven agent that exposes ASE and DFT tooling through a natural-language interface to lower the barrier to atomistic simulation workflows.
  • Collaborating with the experimental group of Dr. Ina Vollmer (Utrecht University) on the mechanistic understanding of plastic polymer degradation, bridging atomistic simulation and physical experiment.
Oct 2020 – Sep 2025

Doctoral Researcher

Biobased Chemistry & Technology group, Wageningen University & Research

  • Performed high-throughput plane-wave DFT (VASP, CP2K) across large transition-metal-carbide composition and surface-termination spaces to derive activity descriptors for biomass hydrodeoxygenation catalysis.
  • Designed and maintained modular, reproducible HPC pipelines (Python/Bash on SLURM) automating structure generation, DFT input preparation, job submission, and post-processing across thousands of calculations.
  • Carried out ab initio molecular dynamics and metadynamics simulations (PLUMED) to characterise reaction free-energy landscapes on catalyst surfaces.
  • Derived interpretable structure-property descriptors using SISSO (symbolic regression) and SHAP-based explainable AI, enabling data-efficient screening from limited DFT datasets.
  • Translated computational insights directly into experimental design in collaboration with synthetic chemists and analytical scientists at WUR, UU, and TU/e.
  • Co-authored 10 publications; contributed to NWO grant applications and international peer review.
May 2019 – May 2020

Master's Thesis Researcher

Theoretical of Quantum Materials group, Sorbonne Université

  • Computed ground-state electronic and magnetic properties of the narrowest zigzag graphene nanoribbon using Quantum ESPRESSO for plane-wave DFT and TurboRVB for quantum Monte Carlo (QMC), establishing many-body QMC reference data for a strongly correlated, low-dimensional carbon system.
  • Benchmarked a hierarchy of DFT exchange-correlation approximations, including DFT+U, against the QMC reference to assess their accuracy for the antiferromagnetic ground state and spin-resolved electronic structure.
  • Developed Python and Bash workflows for plane-wave DFT input generation, k-point and cutoff convergence, and structural relaxation on HPC clusters, directly relevant to building DFT reference datasets for downstream MLIP training.

Publications

Ten peer-reviewed publications in computational chemistry, catalysis, and materials science. Full list on Google Scholar. One first-author manuscript and two collaboration manuscripts in preparation.

First-author publications

  1. Meena, R.; Purcell, J. M.; Kluijtmans, W.; Zuilhof, H.; Bitter, J. H.; Ouyang, R.; Li, G. (2025). Activity descriptors of Mo2C-based catalysts for C–OH bond activation. ChemRxiv (under review at ACS Catalysis). doi:10.26434/chemrxiv-2025-pg52l
  2. Meena, R.; Draijer, K. M.; van Dam, B.; Zuilhof, H.; Bitter, J. H.; Li, G. (2025). Rationalizing catalytic performances of Mo/W-(oxy)carbides for hydrodeoxygenation reaction. ChemCatChem. Front cover. doi:10.1002/cctc.202500659
  3. Meena, R.; Bitter, J. H.; Zuilhof, H.; Li, G. (2023). Toward the rational design of more efficient Mo2C catalysts for hydrodeoxygenation. ACS Catalysis. doi:10.1021/acscatal.3c03728
  4. Meena, R.; Li, G.; Casula, M. (2022). Ground-state properties of the narrowest zigzag graphene nanoribbon from quantum Monte Carlo. Journal of Chemical Physics. doi:10.1063/5.0078234

Co-authored publications

  1. Simi, S.; Mathew, T.; Meena, R.; Li, G.; Shiju, N. R.; et al. (2025). Towards improved activity and stability in RWGS reaction: dispersed copper in mesoporous alumina matrix. Chemical Engineering Journal. doi:10.1016/j.cej.2025.169863
  2. Hergesell, A. H.; Popp, S.; Meena, R.; Guarin, V. M. O.; Seitzinger, C. L.; Sievers, C.; Li, G.; Vollmer, I. (2025). Homolytic fracture of inorganic crystalline materials enhances the mechano-chemical degradation of polypropylene. Chemical Science. doi:10.1039/d5sc03348a
  3. Pirgach, D. A.; Meena, R.; Li, G.; Miloserdov, F. M.; van Es, D. S.; Bruijnincx, P. C. A.; Bitter, J. H. (2025). Medium-dependent regioselectivity of electrochemical bromination of methyl levulinate. RSC Sustainability. doi:10.1039/d5su00037h
  4. Hergesell, A. H.; Baarslag, R. J.; Seitzinger, C. L.; Meena, R.; Schara, P.; Tomović, Ž.; Li, G.; Weckhuysen, B. M.; Vollmer, I. (2024). Surface-activated mechano-catalysis for ambient conversion of plastic waste. Journal of the American Chemical Society. doi:10.1021/jacs.4c07157
  5. Zhang, H.; Bolshakov, A.; Meena, R.; Garcia, G. A.; Dugulan, A. I.; Parastaev, A.; Li, G.; Hensen, E. J. M.; Kosinov, N. (2023). Revealing active sites and reaction pathways in methane non-oxidative coupling over iron-containing zeolites. Angewandte Chemie International Edition. doi:10.1002/anie.202306196
  6. Ghorai, S.; Meena, R.; Joseph, A. P.; Jemmis, E. D. (2021). Comparison of RNC coupling and CO coupling mediated by Cr–Cr quintuple bond and B–B multiple bonds. Journal of Physical Chemistry A. doi:10.1021/acs.jpca.1c05185

Technical Skills

DFT codes Quantum ESPRESSO, VASP, CP2K, GAUSSIAN
Beyond DFT Ab initio molecular dynamics, metadynamics (CP2K + PLUMED), Quantum Monte Carlo (TurboRVB), microkinetic modelling
ML potentials Training and validation of MLIPs (MACE, fair-chem/UMA); active-learning loops with DFT reference data
HPC & workflows SLURM, modular Python/Bash pipelines for high-throughput DFT and AIMD, Materials Project + ASE-based automation
Programming Python (NumPy, ASE, scikit-learn, seaborn, pandas, matplotlib), Bash, Git, Linux
ML / data science SISSO (symbolic regression), SHAP-based explainable AI, feature engineering, LLM-driven workflow automation (API, tool calling, agents)

Funding and Awards

2021 – 2025

NWO HPC grants, Snellius supercomputer

12.5M CPU and 50k GPU hours (€200k equivalent)

2019

Erasmus+ Fellowship, Sorbonne Université

€10k — awarded for M2 studies in France

2015 – 2020

INSPIRE Scholarship, Government of India

Nationally competitive science scholarship; 1,000 awards per year

2013 – 2015

NTSE Scholarship, Government of India

Nationally competitive talent-search scholarship; 1,000 awards per year

Teaching and Supervision

  • Co-taught advanced computational chemistry to graduate students at Wageningen University, 2020–2025.
  • Supervised 6 thesis projects: 3 MSc major, 2 MSc minor, 1 BSc.
  • Supervised undergraduate organic chemistry practicals.

Professional Development

  • Python for Data Science and Machine Learning Bootcamp, Udemy, 2025.
  • CECAM "Understanding Molecular Simulation" school, University of Amsterdam, 2023.
  • Scientific Writing, Wageningen in'to Languages, 2023.
  • Project and Time Management, Wageningen Graduate School, 2023.
  • Paris International School on Advanced Computational Materials Science, Sorbonne University, 2021.
  • Han-sur-Lesse winter school for theoretical and computational chemistry, Ardennes, 2021.

Languages

EnglishFluent
HindiNative
DutchA2

References

Available on request from the PhD advisors listed in this CV.