2 citations · 3 across the 4 of their papers we have counts for
6 papers
FlashCart: Fast Cartesian Tensor Products for Equivariant Interatomic Potentials
Viktor Zaverkin, Payman Goodarzi, Sergey V. Sukhomlinov +4
Machine-learned interatomic potentials extend atomistic simulations beyond the length- and timescales accessible to electronic-structure methods. However, the computational cost of…
Molecular Déjà Vu: Digit-Level Retrieval of Molecular Properties in Frontier Language Models
Matthias Busch, Marius Tacke, Sviatlana V. Lamaka +4
Large language models (LLMs) are increasingly employed to predict molecular properties. However, prediction error alone cannot distinguish prediction from retrieval of published va…
LLM-driven design of physics-constrained constitutive models: two agents are better than one
Marius Tacke, Matthias Busch, Kian Abdolazizi +4
Developing constitutive models that capture how materials deform under load traditionally requires years of specialized expertise in continuum mechanics, machine learning, and scie…
In-Context Molecular Property Prediction with LLMs: A Blinding Study on Memorization and Knowledge Conflicts
Matthias Busch, Marius Tacke, Sviatlana V. Lamaka +4
The capabilities of large language models (LLMs) have expanded beyond natural language processing to scientific prediction tasks, including molecular property prediction. However,…
GENIUS: An Agentic AI Framework for Autonomous Design and Execution of Simulation Protocols
Mohammad Soleymanibrojeni, Roland Aydin, Diego Guedes-Sobrinho +4
Predictive atomistic simulations have propelled materials discovery, yet routine setup and debugging still demand computer specialists. This know-how gap limits Integrated Computat…
Teaching a Transformer to Think Like a Chemist: Predicting Nanocluster Stability
João Marcos T. Palheta, Octavio Rodrigues Filho, Mohammad Soleymanibrojeni +6
Atomically precise metal nanoclusters bridge the molecular and bulk regimes, but designing bimetallic motifs with targeted stability and reactivity remains challenging. Here we com…