1 citations · 2 across the 2 of their papers we have counts for
3 papers
physics.chem-ph2024★ 1 cited
Multiscale modeling framework of a constrained fluid with complex boundaries using twin neural networks
Peiyuan Gao, George Em Karniadakis, Panos Stinis
The properties of constrained fluids have increasingly gained relevance for applications ranging from materials to biology. In this work, we propose a multiscale model using twin n…
physics.chem-ph2023
Physics-Guided Continual Learning for Predicting Emerging Aqueous Organic Redox Flow Battery Material Performance
Yucheng Fu, Amanda Howard, Chao Zeng +3
Aqueous organic redox flow batteries (AORFBs) have gained popularity in renewable energy storage due to their low cost, environmental friendliness and scalability. The rapid discov…
physics.comp-ph2023★ 1 cited
Physics-informed machine learning of the correlation functions in bulk fluids
Wenqian Chen, Peiyuan Gao, Panos Stinis
The Ornstein-Zernike (OZ) equation is the fundamental equation for pair correlation function computations in the modern integral equation theory for liquids. In this work, machine…