Physics-Informed Neural Networks with Group Contribution Methods

Thermophysical properties of organic compounds are used in countless scientific, engineering, and industrial settings in developing theories, designing new systems and devices, analyzing costs and risks, and improving existing infrastructure. Often, due to costs, safety, prior interest, or procedura...

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Veröffentlicht in:	Journal of chemical theory and computation 2023-07, Vol.19 (13), p.4163-4171
Hauptverfasser:	Babaei, Mohammad Reza, Stone, Ryan, IV, Thomas Allen Knotts, Hedengren, John
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Boiling points Cost analysis Deep learning Distillation Environmental impact Machine learning Neural networks Nuclear safety Organic compounds Physics Predictions Surface tension Test sets Thermodynamics Thermophysical properties Training
Online-Zugang:	Volltext
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