Dr. Alin Marin Elena | Data Driven Materials and Molecular Science

Biography

Alin leads the Data Driven Materials and Molecular Science research group.

Current work focuses on physics-informed machine learning (machine-learnt interatomic potentials), transport properties in complex liquids and molten salts, porous materials, and explaining experimental results via atomistic modelling.

Alin is the scientific secretary of CCP5 since 2018, co-organiser of the CCP5 Summer School since 2017, co-organiser and founding member of CaMML school, and founding member of the IOP Machine Learning and Neuromorphic Computing Group.

You can see a list of UKRI grants where Alin was/is Co-I or PI here.

Highlighted Work

📄 Publication @batatia20257006

A foundation model for atomistic materials chemistry

Ilyes Batatia et al.

The Journal of Chemical Physics 2025 DOI: 10.1063/5.0297006

🔗 View Publication 📚 Group Catalogue

💻 Software Python / ASE / CLI

janus-core

Tools for materials modeling with machine-learned interatomic potentials (MACE, SevenNet, CHGNet, M3GNet). Provides a simple, robust CLI and Python API with full ASE calculator support.

pip install janus-core

🔗 GitHub Repository 🔗 Documentation 🔗 PyPI

💻 Software Python / Packing / CLI

pack-mm

A Python package and CLI for building realistic atomistic and molecular systems for materials modeling, utilizing machine-learned interatomic potentials (via janus-core) with Monte Carlo and Molecular Dynamics routines.

pip install pack-mm

🔗 GitHub Repository 🔗 Documentation 🔗 PyPI

Research Interests & Focus

Machine-learned interatomic potentials (MLIPs) and MACE foundation models
Rare event sampling, enhanced sampling, and free energy methods
Molecular dynamics algorithms and scalable parallel simulation software (DL_POLY)
Transport properties and thermodynamics in complex liquids and molten salts
Porous frameworks, metal-organic frameworks, and guest-host adsorption
Bridging experimental synchrotron/neutron observations with atomistic modelling

ML Interatomic Potentials MACE Foundation Models Rare Event Sampling Molecular Dynamics Molten Salts Porous Materials Experiment vs Modelling High Performance Computing Agentic AI

Appointments & Roles

Group Leader, Data Driven Materials and Molecular Science — STFC Scientific Computing Department, UKRI
Computational Scientist(Principal) — STFC Scientific Computing Department, UKRI
Scientific Secretary — CCP5 (Collaborative Computational Project on Condensed Phase Simulation)

Recent Publications

A budget-dependent crossover between coverage-and response-based training-set selection for machine-learned interatomic potentials

Jia Bi, Alin-Marin Elena arXiv preprint arXiv:2609.05877 • 2026 DOI: 10.48550/arXiv.2609.05877

A strategic roadmap for an atomistic machine-learning ecosystem

Jörg Behler, Michele Ceriotti, Cecilia Clementi, Gábor Csányi, Alin-Marin Elena, Aditi Krishnapriyan, Joseph W. Abbott, Fabio Affinito, Albert P. Bartók, Ilyes Batatia, Filippo Bigi, Florian N. Brünig, Yannick Calvino Alonso, Giuseppe Carleo, Aurélie Champagne, Stefan Chmiela, Marc L. Descoteaux, Ralf Drautz, Alexandra Farcas, Meng Gao, Rohit Goswami, Michael F. Herbst, Christian Holm, James R. Kermode, Alexander L. M. Knoll, Tobias Kreiman, Marcel F. Langer, Hoang-Thien Luu, Yury Lysogorskiy, Mihai-Cosmin Marinica, Rocco Meli, Klaus-Robert Müller, Frank Noé, Mohamadhosein Nosratjoo, Simon Olsson, Christoph Ortner, Aldo S. Pasos-Trejo, Anyang Peng, Eric Qu, Andrea Rizzi, Mariana Rossi, Bassem Sboui, Gregor N. C. Simm, Alexandre Tkatchenko, Jacopo Venturin, O. Anatole von Lilienfeld, William C. Witt, Brandon M. Wood, Tigany Zarrouk, Fabian Zills arXiv preprint arxiv: 2609.39090 • 2026 DOI: 10.48550/arXiv.2609.39090

Automatic generation of input files with optimised k-point meshes for Quantum ESPRESSO self-consistent field single-point total energy calculations

Elena Patyukova, Junwen Yin, Susmita Basak, Samuel Pinilla, Alin M. Elena, Gilberto Teobaldi Digital Discovery • 2026 DOI: 10.1039/d5dd00565e

Bond, orbital and spin order in d4/d6/d7 perovskite oxides: successes and limitations of foundation interatomic potentials

Swagata Acharya, Dimitar Pashov, Mark van Schilfgaarde, Alin M. Elena arxiv.org/abs/2607.08351 • 2026 DOI: 10.48550/arXiv.2607.08351

Data-driven Design of Metal-Organic Frameworks with Tunable Negative Thermal Expansion

Prathami Divakar Kamath, Francesco Tavani, Alin Marin Elena, Théo Jaffrelot Inizan, Yen-hsu Lin, Jian Yin, Wenqian Xu, Omar M. Yaghi, Kristin A. Persson arXiv preprint arXiv:2607.18594 • 2026 DOI: 10.48550/arXiv.2607.18594

View All Publications by Dr. Alin Marin Elena (43) →