5 papers
Harnessing AtomisticSkills for Agentic Atomistic Research
Bowen Deng, Bohan Li, Matthew Cox +20
Computational materials science and chemistry span vast knowledge domains and fractured software ecosystems. Although large language models (LLMs) have demonstrated research capabi…
Reweighting free energy profiles between universal machine learning interatomic potentials for fast consensus building
Sauradeep Majumdar, Miguel Steiner, Johannes C. B. Dietschreit +4
Free energy profiles serve as a fundamental bridge between microscopic atomic fluctuations and macroscopic thermodynamic observables. Estimating the free energy profile along a rea…
A Priori Sampling of Transition States with Guided Diffusion
Hyukjun Lim, Soojung Yang, Lucas Pinède +3
Transition states, the first-order saddle points on the potential energy surfaces, govern the kinetics and mechanisms of chemical reactions and conformational changes. Locating the…
Transferable Learning of Reaction Pathways from Geometric Priors
Juno Nam, Miguel Steiner, Max Misterka +3
Identifying minimum-energy paths (MEPs) is crucial for understanding chemical reaction mechanisms but remains computationally demanding. We introduce MEPIN, a scalable machine-lear…
Heron: Visualizing and Controlling Chemical Reaction Explorations and Networks
Charlotte H. Müller, Miguel Steiner, Jan P. Unsleber +6
Automated and high-throughput quantum chemical investigations into chemical processes have become feasible in great detail and broad scope. This results in an increase in complexit…