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  • Dr. Anoop Ayyappan, Department of Chemistry, Indian Institute of Technology Kharagpur
  • Kharagpur, West Bangal, India

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anooplab/README.md

AnoopLab

AnoopLab is a computational chemistry research group led by Prof. Anoop Ayyappan. The group is currently based at Digital University Kerala, continuing a computational chemistry research programme developed across Digital University Kerala and IIT Kharagpur.

We develop and apply computational methods to explore chemical space, molecular structure, reactivity, and materials. Machine learning is used judiciously alongside quantum chemistry, with emphasis on chemical interpretation, validation, and reproducible workflows.

Research themes

  • Scientific software and reproducible computational discovery — reusable tools and workflows for chemical structure, reaction, and property exploration.
  • Explainable AI and machine learning for molecular science — interpretable structure–property relationships and ML-assisted quantum chemistry.
  • Automated exploration of chemical space, reactions, and structures — systematic generation and exploration of molecules, reaction networks, aggregates, and nanoclusters.
  • Computational molecular and materials discovery — quantum-chemical and data-driven approaches to molecules, nanoclusters, and materials.

Software and data

  • PyAR — software for automated exploration of aggregates, reaction pathways, solvation structures, and atomic clusters.
  • HydroMol — a searchable dataset and chemical-space explorer for hydrocarbons.
  • SSA — an implementation of Gillespie's stochastic simulation algorithm.

PyAR is the group's principal software-development programme and a continuing focus for methodological research.

Recent work

  • S. Giri, M. Banerjee, A. Subhash, S. Rajesh, S. E. Padinjarethil, and A. Anoop, “Chemical Space Exploration and Molecular Design of Organic Donor–Acceptor TADF Emitters,” Journal of Materials Chemistry C (2026). DOI: 10.1039/D6TC00707D
  • S. Giri, S. Ghosal, and A. Anoop, “Data-Driven Exploration of Synthesizable Strained Hydrocarbons as High-Energy-Density Candidates for Sustainable Aviation Fuels,” Sustainable Energy & Fuels 10 (2026), 3240–3251. DOI: 10.1039/D6SE00364H

Links

Contact

Prof. Anoop Ayyappan
School of Digital Sciences, Digital University Kerala
anoop.a@duk.ac.in

Popular repositories Loading

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    Python program for aggregation and reaction

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  2. ssa ssa Public

    Our implementation of Gillespie's Stochastic Simulation Algorithm (SSA)

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  4. eSIgen4qc eSIgen4qc Public

    eSIgen4qc is a tool that generates electronic supporting information (ESI) for quantum chemistry, focusing on ORCA output files. It extracts properties like energy, free energy, zero-point energy (…

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    Config files for my GitHub profile.