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Tuning Pressure Drop in Isoporous Membranes: Tuning Pressure Drop in Isoporous Membranes: Design with Fabrication Variability (Adv. Theory Simul. 8/2021)
Author(s) -
Ong Shi Ke,
Birgersson Erik,
Low Hong Yee
Publication year - 2021
Publication title -
advanced theory and simulations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.068
H-Index - 17
ISSN - 2513-0390
DOI - 10.1002/adts.202170016
Subject(s) - membrane , fabrication , pressure drop , monte carlo method , drop (telecommunication) , range (aeronautics) , drop out , nanotechnology , materials science , computer science , statistical physics , mechanics , physics , engineering , chemistry , mechanical engineering , mathematics , statistics , composite material , medicine , biochemistry , alternative medicine , pathology , economics , demographic economics
In article number 2100088, Shi Ke Ong, Erik Birgersson, and Hong Yee Low develop a physics‐based machine learning methodology: the inherent fabrication variabilities (probability distributions) in the pore architecture of isoporous membranes and a trained neural network that aids in the performance range prediction through Monte Carlo simulations. Input and output are scaled [−1 1], hence the background has the digits ‘−1’, ‘0’ and ‘1’.