Deep learning-based quasi-continuum theory for structure of confined fluids

Wu, Haiyi; Aluru, Narayana R.

doi:10.1063/5.0096481

Title: Deep learning-based quasi-continuum theory for structure of confined fluids

Journal Article · Tue Aug 30 00:00:00 EDT 2022 · Journal of Chemical Physics

DOI:https://doi.org/10.1063/5.0096481· OSTI ID:1979105

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Univ. of Texas, Austin, TX (United States)

Predicting the structural properties of water and simple fluids confined in nanometer scale pores and channels is essential in, for example, energy storage and biomolecular systems. Classical continuum theories fail to accurately capture the interfacial structure of fluids. In this work, we develop a deep learning-based quasi-continuum theory (DL-QT) to predict the concentration and potential profiles of a Lennard-Jones (LJ) fluid and water confined in a nanochannel. The deep learning model is built based on a convolutional encoder–decoder network (CED) and is applied for high-dimensional surrogate modeling to relate the fluid properties to the fluid–fluid potential. The CED model is then combined with the interatomic potential-based continuum theory to determine the concentration profiles of a confined LJ fluid and confined water. Further, we show that the DL-QT model exhibits robust predictive performance for a confined LJ fluid under various thermodynamic states and for water confined in a nanochannel of different widths. The DL-QT model seamlessly connects molecular physics at the nanoscale with continuum theory by using a deep learning model.

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Research Organization:: Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Energy Frontier Research Centers (EFRC) (United States). Center for Enhanced Nanofluidic Transport (CENT)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES); National Science Foundation (NSF)

Grant/Contract Number:: SC0019112; 2140225; 2137157

OSTI ID:: 1979105

Journal Information:: Journal of Chemical Physics, Vol. 157, Issue 8; ISSN 0021-9606

Publisher:: American Institute of Physics (AIP)Copyright Statement

Country of Publication:: United States

Language:: English

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