5 papers
Evaluating LLM-generated code for domain-specific languages: molecular dynamics with LAMMPS
Ethan Holbrook, Juan C. Verduzco, Alejandro Strachan
Large language models (LLMs) are changing the way researchers interact with code and data in scientific computing. While their ability to generate general-purpose code is well esta…
A Data-Driven Parametric Reduced-Order Chemical Kinetics Model Derived from Atomistic Simulations
Michael N. Sakano, Alejandro Strachan
Coarse-grained modeling in molecular simulations serves not only to extend accessible time and length scales beyond atomistic limits, but also to reduce high-dimensional chemical d…
Nuclear Quantum Effects in Multi-Step Condensed Matter Chemistry: A Path Integral Molecular Dynamics Study of Thermal Decomposition
Jalen Macatangay, Alejandro Strachan
Nuclear quantum effects (NQEs) are often central to a predictive understanding of chemical reactions and rates. While their incorporation in gas-phase reactions is well established…
A collaborative digital twin built on FAIR data and compute infrastructure
Thomas M. Deucher, Juan C. Verduzco, Michael Titus +1
The integration of machine learning with automated experimentation in self-driving laboratories (SDL) offers a powerful approach to accelerate discovery and optimization tasks in s…
Thermodynamic Fidelity of Generative Models for Ising System
Brian H. Lee, Kat Nykiel, Ava E. Hallberg +2
Machine learning has become a central technique for modeling in science and engineering, either complementing or as surrogates to physics-based models. Significant efforts have rec…