4 papers
Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic Refinement
Zuriel Y. Yescas-Ramos, Andrés Ãlvarez-GarcÃa, Huziel E. Sauceda
We present \textsc{dm-PhiSNet}, a physically constrained \textsc{PhiSNet}-based equivariant model that predicts one-electron reduced density matrices (1-RDMs) directly from molecul…
Characterizing High-Capacity Janus Aminobenzene-Graphene Anode for Sodium-Ion Batteries with Machine Learning
Claudia Islas-Vargas, L. Ricardo Montoya, Carlos A. Vital-José +3
Sodium-ion batteries require anodes that combine high capacity, low operating voltage, fast Na-ion transport, and mechanical stability, which conventional anodes struggle to delive…
Delta-learned force fields for nonbonded interactions: Addressing the strength mismatch between covalent-nonbonded interaction for global models
Leonardo Cázares-Trejo, Marco Loreto-Silva, Huziel E. Sauceda
Noncovalent interactions--vdW dispersion, hydrogen/halogen bonding, ion-, and -stacking--govern structure, dynamics, and emergent phenomena in materials and molecular syste…
Machine Learned Force Fields: Fundamentals, its reach, and challenges
Carlos A. Vital, Román J. Armenta-Rico, Huziel E. Sauceda
Highly accurate force fields are a mandatory requirement to generate predictive simulations. In this regard, Machine Learning Force Fields (MLFFs) have emerged as a revolutionary a…