Efficient, Interpretable Graph Neural Network Representation for Angle-dependent Properties and its Application to Optical Spectroscopy

no code implementations • 23 Sep 2021 • Tim Hsu, Tuan Anh Pham, Nathan Keilbart, Stephen Weitzner, James Chapman, Penghao Xiao, S. Roger Qiu, Xiao Chen, Brandon C. Wood

In this work, we extend the recently proposed ALIGNN encoding, which incorporates bond angles, to also include dihedral angles (ALIGNN-d).

Semi-Automated Creation of Density Functional Tight Binding Models Through Leveraging Chebyshev Polynomial-based Force Fields

1 code implementation • 6 Feb 2021 • Nir Goldman, Kyoung Eun Kweon, Babak Sadigh, Tae Wook Heo, Rebecca K. Lindsey, C. Huy Pham, Laurence E. Fried, Bálint Aradi, Kiel Holliday, Jason R. Jeffries, Brandon C. Wood

Our approach is easy to implement and can yield accurate DFTB models over a broad range of thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.

Materials Science