L-MAU-Cahn-Hilliard: MPI Solver and Low-Dimensional Prediction Pipeline
Published:
In-progress academic project for Cahn-Hilliard microstructure evolution: MPI spectral solver + low-dimensional ML prediction with L-MAU.
Published:
In-progress academic project for Cahn-Hilliard microstructure evolution: MPI spectral solver + low-dimensional ML prediction with L-MAU.
Published in Journal of the Taiwan Institute of Chemical Engineers, 2021
Process simulation and techno-economic analysis of hybrid membrane/cryogenic distillation for air separation.
Recommended citation: Chen SJ, Yu BY. Rigorous simulation and techno-economic evaluation on the hybrid membrane/cryogenic distillation processes for air separation. Journal of the Taiwan Institute of Chemical Engineers. 2021 Oct 1;127:56-68.
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Published in Polymers, 2023
Phase-field modeling and physics-informed neural networks for connecting morphology and properties in phase-separating polymer solutions.
Recommended citation: Lin LC, Chen SJ, Yu HY. Connecting structural characteristics and material properties in phase-separating polymer solutions: phase-field modeling and physics-informed neural networks. Polymers. 2023 Dec 14;15(24):4711.
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Published in Computer Physics Communications, 2024
A multivariate time-series network approach for predicting Cahn-Hilliard microstructure evolution in low-dimensional latent space.
Recommended citation: Chen SJ, Yu HY. L-MAU: A multivariate time-series network for predicting the Cahn-Hilliard microstructure evolutions via low-dimensional approaches. Computer Physics Communications. 2024 Dec 1;305:109342.
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Published:
Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.