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cond-mat.mtrl-sci2022★ 1 cited
Deep-learning-based prediction of nanoparticle phase transitions during in situ transmission electron microscopy
Wenkai Fu, Steven R. Spurgeon, Chongmin Wang +3
We develop the machine learning capability to predict a time sequence of in-situ transmission electron microscopy (TEM) video frames based on the combined long-short-term-memory (L…
cond-mat.mtrl-sci2021★ 83 cited
Predicting Aqueous Solubility of Organic Molecules Using Deep Learning Models with Varied Molecular Representations
Gihan Panapitiya, Michael Girard, Aaron Hollas +3
Determining the aqueous solubility of molecules is a vital step in many pharmaceutical, environmental, and energy storage applications. Despite efforts made over decades, there are…