Théo Jaffrelot Inizan
- Atomate2: modular workflows for materials science
2025/01/01 by Alex M. Ganose, Hrushikesh Sahasrabuddhe, Mark Asta +53 · 2 voices · 8 citations
Chemical Engineering · Decision Sciences · Materials Science · #Catalysis and Oxidation Reactions #Machine Learning in Materials Science #Scientific Computing and Data Management
- Scalable Hybrid Deep Neural Networks/Polarizable Potentials Biomolecular Simulations including long-range effects
2022/07/28 by Théo Jaffrelot Inizan, Thomas Plé, Inizan, Théo Jaffrelot +13 · 3 citations
Biochemistry, Genetics and Molecular Biology · #Chemical Physics (physics.chem-ph) #FOS: Physical sciences #Genetics, Bioinformatics, and Biomedical Research #Machine Learning in Bioinformatics #Protein Structure and Dynamics
- Machine Learned Potential for High-Throughput Phonon Calculations of Metal-Organic Frameworks
2024/12/03 by Alin Marin Elena, Alin M. Elena, Prathami Divakar Kamath +12 · 1 voice · 4 citations
Chemistry · Materials Science · Physics and Astronomy · #Chemical Physics (physics.chem-ph) #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Metal-Organic Frameworks: Synthesis and Applications #X-ray Diffraction in Crystallography #cond-mat.mtrl-sci #physics.chem-ph
- Advancing Force Fields Parameterization: A Directed Graph Attention Networks Approach
2024/06/14 by Gong Chen, Théo Jaffrelot Inizan, Thomas Plé +3 · 1 voice · 2 citations
Computer Science · Materials Science · #Advanced Graph Neural Networks #Graph Theory and Algorithms #Machine Learning in Materials Science
- Data-driven Design of Metal-Organic Frameworks with Tunable Negative Thermal Expansion
2026/07/21 by Prathami Divakar Kamath, Francesco Tavani, Alin Marin Elena +6 · 1 voice
#cond-mat.mtrl-sci