3 papers
physics.chem-ph2026
TSAgent: An Agentic Workflow for Autonomous Transition State Search
Varun Madhavan, Ankit Mathanker, Dean M. Sweeney +3
Identifying transition states (TSs) on potential energy surfaces is a central computational bottleneck in mechanistic studies of catalytic materials. A TS search is not a single ca…
cond-mat.mtrl-sci2026
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…
physics.chem-ph2026
Benchmarking short-range machine learning potentials for atomistic simulations of metal/electrolyte interfaces
Lucas B. T. de Kam, Jia-Xin Zhu, Ankit Mathanker +2
Atomistic simulations of electrochemical interfaces remain challenging due to the long time scales required to adequately sample the structure of the electric double layer. The eme…