29 citations · 60 across the 9 of their papers we have counts for
4 papers · 1 filter
Inverse design of bespoke interatomic potentials via active learning by information-matching
Yonatan Kurniawan, Logan D. Williams, Amit Samanta +6
Interatomic potentials (IPs) enable large-scale atomistic simulations beyond the reach of first-principles methods, but their predictive reliability depends critically on the selec…
Information Entropy is a General-Purpose Collective Variable for Enhanced Sampling
Xiangrui Li, Daniel Schwalbe-Koda
Enhanced sampling methods typically require predefined collective variables (CVs) that presuppose knowledge of reaction coordinates, restricting the discovery of unanticipated tran…
Generative Inversion of Spectroscopic Data for Amorphous Structure Elucidation
Jiawei Guo, Daniel Schwalbe-Koda
Determining atomistic structures from characterization data is one of the most common yet intricate problems in materials science. Particularly in amorphous materials, proposing st…
Automatic Identification of Compounds in Molecular Mixtures from Liquid-Phase Infrared Spectra
Yannah J. U. Melle, Thanh Nguyen, Jeffrey Lopez +1
Interpreting spectroscopy data is a critical bottleneck in automating chemical research and industrial characterization. Particularly within infrared (IR) spectroscopy, identifying…