430 citations · 955 across the 13 of their papers we have counts for
13 papers
Hydrogen in Disordered Titania: Connecting Local Chemistry, Structure, and Stoichiometry through Accelerated Exploration
James Chapman, Kyoung E. Kweon, Yakun Zhu +8
Hydrogen incorporation in native surface oxides of metal alloys often controls the onset of metal hydriding, with implications for materials corrosion and hydrogen storage. A key r…
Quantifying Disorder One Atom at a Time Using an Interpretable Graph Neural Network Paradigm
James Chapman, Tim Hsu, Xiao Chen +2
Quantifying the level of atomic disorder within materials is critical to understanding how evolving local structural environments dictate performance and durability. Here, we lever…
Efficient, Interpretable Graph Neural Network Representation for Angle-dependent Properties and its Application to Optical Spectroscopy
Tim Hsu, Tuan Anh Pham, Nathan Keilbart +6
Graph neural networks are attractive for learning properties of atomic structures thanks to their intuitive graph encoding of atoms and bonds. However, conventional encoding does n…
A Physically-informed Graph-based Order Parameter for the Universal Characterization of Atomic Structures
James Chapman, Nir Goldman, Brandon Wood
A new graph-based order parameter is introduced for the characterization of atomistic structures. The order parameter is universal to any material/chemical system, and is transfera…
Semi-Automated Creation of Density Functional Tight Binding Models Through Leveraging Chebyshev Polynomial-based Force Fields
Nir Goldman, Kyoung Eun Kweon, Babak Sadigh +8
Density Functional Tight Binding (DFTB) is an attractive method for accelerated quantum simulations of condensed matter due to its enhanced computational efficiency over standard D…
Neural Networks Potential from the Bispectrum Component: A Case Study on Crystalline Silicon
Howard Yanxon, David Zagaceta, Brandon C. Wood +1
In this article, we present a systematic study in developing machine learning force fields (MLFF) for crystalline silicon. While the main-stream approach of fitting a MLFF is to us…