DOE OSTI · 2438146
Capturing molecular interactions in graph neural networks: a case study in multi-component phase equilibrium
Abstract
We propose a graph neural network architecture that captures molecular interactions in an explicit manner by combining atomic-level (local) graph convolution and molecular-level (global) message passing through a molecular interaction network.
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Qin, Shiyi, Jiang, Shengli, Li, Jianping, Balaprakash, Prasanna, Van Lehn, Reid C., Zavala, Victor M.. 2023-02-13. Capturing molecular interactions in graph neural networks: a case study in multi-component phase equilibrium. https://doi.org/10.1039/d2dd00045h
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