Physics- and image-based prediction of fluid flow and transport in complex porous membranes and materials by deep learning
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Physics- and image-based prediction of fluid flow and transport in complex porous membranes and materials by deep learning
Authors
Keywords
Machine learning, Porous membrane, Fluid flow
Journal
JOURNAL OF MEMBRANE SCIENCE
Volume 622, Issue -, Pages 119050
Publisher
Elsevier BV
Online
2021-01-12
DOI
10.1016/j.memsci.2021.119050
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Simultaneous rational design of ion separation membranes and processes
- (2020) Deniz Rall et al. JOURNAL OF MEMBRANE SCIENCE
- Neural networks for estimating physical parameters in membrane distillation
- (2020) Alexander V. Dudchenko et al. JOURNAL OF MEMBRANE SCIENCE
- Designing exceptional gas-separation polymer membranes using machine learning
- (2020) J. Wesley Barnett et al. Science Advances
- A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems
- (2020) Meng Tang et al. JOURNAL OF COMPUTATIONAL PHYSICS
- Multi-scale membrane process optimization with high-fidelity ion transport models through machine learning
- (2020) Deniz Rall et al. JOURNAL OF MEMBRANE SCIENCE
- Backwash sequence optimization of a pilot-scale ultrafiltration membrane system using data-driven modeling for parameter forecasting
- (2020) Bopeng Zhang et al. JOURNAL OF MEMBRANE SCIENCE
- Advanced control of membrane fouling in filtration systems using artificial intelligence and machine learning techniques: A critical review
- (2019) Majid Bagheri et al. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
- Remaining useful life estimation for proton exchange membrane fuel cells using a hybrid method
- (2019) Hao Liu et al. APPLIED ENERGY
- Simulation and characterization of novel reverse osmosis membrane prepared by blending polypyrrole coated multiwalled carbon nanotubes for brackish water desalination and antifouling properties using artificial neural networks
- (2019) Javad Farahbakhsh et al. JOURNAL OF MEMBRANE SCIENCE
- A novel process monitoring approach based on variational recurrent autoencoder
- (2019) Feifan Cheng et al. COMPUTERS & CHEMICAL ENGINEERING
- Deep neural networks for modeling fouling growth and flux decline during NF/RO membrane filtration
- (2019) Sanghun Park et al. JOURNAL OF MEMBRANE SCIENCE
- Toward the inverse design of MOF membranes for efficient D2/H2 separation by combination of physics-based and data-driven modeling
- (2019) Musen Zhou et al. JOURNAL OF MEMBRANE SCIENCE
- Linking Morphology of Porous Media to Their Macroscopic Permeability by Deep Learning
- (2019) Serveh Kamrava et al. TRANSPORT IN POROUS MEDIA
- Machine learning-enabled discovery and design of membrane-active peptides
- (2018) Ernest Y. Lee et al. BIOORGANIC & MEDICINAL CHEMISTRY
- Modeling fouling in a large RO system with artificial neural networks
- (2018) Edwin A. Roehl et al. JOURNAL OF MEMBRANE SCIENCE
- Prediction of Membrane Permeation of Drug Molecules by Combining an Implicit Membrane Model with Machine Learning
- (2018) Stephanie A. Brocke et al. Journal of Chemical Information and Modeling
- Rational design of ion separation membranes
- (2018) Deniz Rall et al. JOURNAL OF MEMBRANE SCIENCE
- U-Net: deep learning for cell counting, detection, and morphometry
- (2018) Thorsten Falk et al. NATURE METHODS
- Preparation of open-cell polymer foams by CO 2 assisted foaming of polymer blends
- (2016) Wei-long Kong et al. POLYMER
- Mapping membrane activity in undiscovered peptide sequence space using machine learning
- (2016) Ernest Y. Lee et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- The application of 3D imaging techniques, simulation and diffusion experiments to explore transport properties in porous oxygen transport membrane support materials
- (2016) Bernhard Tjaden et al. SOLID STATE IONICS
- Quantitative analysis of mitochondrial morphology and membrane potential in living cells using high-content imaging, machine learning, and morphological binning
- (2015) Anthony P. Leonard et al. BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR CELL RESEARCH
- Prediction of plasticization pressure of polymeric membranes for CO2 removal from natural gas
- (2015) A.L. Ahmad et al. JOURNAL OF MEMBRANE SCIENCE
- Functional discrimination of membrane proteins using machine learning techniques
- (2008) M Michael Gromiha et al. BMC BIOINFORMATICS
- Neural network approach for modeling the performance of reverse osmosis membrane desalting
- (2008) Dan Libotean et al. JOURNAL OF MEMBRANE SCIENCE
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now