6 papers
AdsMind: A Physics-Grounded Multi-Agent System for Self-Correcting Discovery of Adsorption Configurations on Heterogeneous Catalyst Surfaces
Zongmin Zhang, Yuyang Lou, Bowen Zhang +6
Identifying the lowest-energy surface-adsorbate configuration is critical for modeling heterogeneous catalysis, yet exhaustive exploration with ab initio calculations is computatio…
On the Covalent Fields of Molecule-Surface Interactions
Edvin Fako, Philippe Schwaller
The ambiguity of the active site, the empirical status of Brønsted-Evans-Polanyi relations, and the unpredictability of linear scaling relation breakdown are three symptoms of a s…
From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Aritra Roy, Kevin Shen, Andrew MacBride +350
Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowledge. This paper analyzes a broa…
LeMat-Bulk: aggregating, and de-duplicating quantum chemistry materials databases
Martin Siron, Inel Djafar, Ali Ramlaoui +10
The rapid expansion of materials science databases has driven machine learning-based discovery while also posing challenges in data integration, duplication, and interoperability.…
Accelerating inverse materials design using generative diffusion models with reinforcement learning
Junwu Chen, Jeff Guo, Edvin Fako +1
Diffusion models promise to accelerate material design by directly generating novel structures with desired properties, but existing approaches typically require expensive and subs…
A foundation model for atomistic materials chemistry
Ilyes Batatia, Philipp Benner, Yuan Chiang +85
Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much…