Membrane Science Meets Machine Learning: Future and Potential Use in Assisting Membrane Material Design and Fabrication

Machine learning aided high-throughput prediction of ionic liquid@MOF composites for membrane-based CO2 capture

(2022) Zhengqing Zhang et al.   JOURNAL OF MEMBRANE SCIENCE

Evaluation of machine learning algorithms to predict internal concentration polarization in forward osmosis

(2022) Ibrar Ibrar et al.   JOURNAL OF MEMBRANE SCIENCE

Deep learning meets quantitative structure–activity relationship (QSAR) for leveraging structure-based prediction of solute rejection in organic solvent nanofiltration

(2022) Gergo Ignacz et al.   JOURNAL OF MEMBRANE SCIENCE

High-throughput predictions of metal–organic framework electronic properties: theoretical challenges, graph neural networks, and data exploration

(2022) Andrew S. Rosen et al.   npj Computational Materials

Combining Machine Learning and Molecular Simulations to Unlock Gas Separation Potentials of MOF Membranes and MOF/Polymer MMMs

(2022) Hilal Daglar et al.   ACS Applied Materials & Interfaces

Agglomeration tendency and activated carbon concentration effects on activated carbon‐polysulfone mixed matrix membrane performance: A design of experiment formulation study

(2022) Jeremy Lewis et al.   JOURNAL OF APPLIED POLYMER SCIENCE

Interpretable machine learning for accelerating the discovery of metal-organic frameworks for ethane/ethylene separation

(2022) Zihao Wang et al.   CHEMICAL ENGINEERING JOURNAL

Membrane fouling prediction and uncertainty analysis using machine learning: A wastewater treatment plant case study

(2022) David J. Kovacs et al.   JOURNAL OF MEMBRANE SCIENCE

Machine learning improves metal–organic frameworks design and discovery

(2022) Senam Tamakloe   MRS BULLETIN

Combining Computational Screening and Machine Learning to Predict Metal–Organic Framework Adsorbents and Membranes for Removing CH4 or H2 from Air

(2022) Huilin Li et al.   Membranes

Machine learning for designing of thin-film nanocomposite membrane

(2021) Masoud Fetanat et al.   SEPARATION AND PURIFICATION TECHNOLOGY

Machine Learning for Advanced Design of Nanocomposite Ultrafiltration Membranes

(2021) Masoud Fetanat et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Machine Learning Meets with Metal Organic Frameworks for Gas Storage and Separation

(2021) Cigdem Altintas et al.   Journal of Chemical Information and Modeling

Imputation of missing gas permeability data for polymer membranes using machine learning

(2021) Qi Yuan et al.   JOURNAL OF MEMBRANE SCIENCE

Predicting Polymers’ Glass Transition Temperature by a Chemical Language Processing Model

(2021) Guang Chen et al.   Polymers

From Black Box to Machine Learning: A Journey through Membrane Process Modelling

(2021) Claudia F. Galinha et al.   Membranes

Automating water quality analysis using ML and auto ML techniques

(2021) D. Venkata Vara Prasad et al.   ENVIRONMENTAL RESEARCH

Revolutionizing Membrane Design Using Machine Learning-Bayesian Optimization

(2021) Haiping Gao et al.   ENVIRONMENTAL SCIENCE & TECHNOLOGY

Benchmarking Machine Learning Models for Polymer Informatics: An Example of Glass Transition Temperature

(2021) Lei Tao et al.   Journal of Chemical Information and Modeling

Bayesian optimization for chemical products and functional materials

(2021) Ke Wang et al.   Current Opinion in Chemical Engineering

Transport analysis of material gap membrane distillation desalination processes

(2020) Jingcheng Cai et al.   DESALINATION

Safety and serviceability of membrane buildings: A critical review on architectural, material and structural performance

(2020) Jianhui Hu et al.   ENGINEERING STRUCTURES

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

Understanding and optimization of thin film nanocomposite membranes for reverse osmosis with machine learning

(2020) Chester Su Hern Yeo et al.   JOURNAL OF MEMBRANE SCIENCE

Multi-scale membrane process optimization with high-fidelity ion transport models through machine learning

(2020) Deniz Rall et al.   JOURNAL OF MEMBRANE SCIENCE

Gas Transport in a Polymer of Intrinsic Microporosity (PIM-1) Substituted with Pseudo-Ionic Liquid Tetrazole-Type Structures

(2020) Michael D. Guiver et al.   MACROMOLECULES

Separation of noble gases through nano porous material membranes

(2020) B. Assfour et al.   ANNALS OF NUCLEAR ENERGY

Molecular image-convolutional neural network (CNN) assisted QSAR models for predicting contaminant reactivity toward OH radicals: Transfer learning, data augmentation and model interpretation

(2020) Shifa Zhong et al.   CHEMICAL ENGINEERING JOURNAL

A comparison of t-SNE, SOM and SPADE for identifying material type domains in geological data

(2019) Mehala Balamurali et al.   COMPUTERS & GEOSCIENCES

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

Activated carbon in mixed-matrix membranes

(2019) Jeremy Lewis et al.   SEPARATION AND PURIFICATION REVIEWS

A Machine Learning Approach for Predicting Defluorination of Per- and Polyfluoroalkyl Substances (PFAS) for Their Efficient Treatment and Removal

(2019) Akber Raza et al.   Environmental Science & Technology Letters

Big Data Creates New Opportunities for Materials Research: A Review on Methods and Applications of Machine Learning for Materials Design

(2019) Teng Zhou et al.   Engineering

Advances, Updates, and Analytics for the Computation-Ready, Experimental Metal–Organic Framework Database: CoRE MOF 2019

(2019) Yongchul G. Chung et al.   JOURNAL OF CHEMICAL AND ENGINEERING DATA

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

Machine learning–assisted molecular design and efficiency prediction for high-performance organic photovoltaic materials

(2019) Wenbo Sun et al.   Science Advances

Machine Learning Enabled Tailor-Made Design of Application-Specific Metal–Organic Frameworks

(2019) Xiangyu Zhang et al.   ACS Applied Materials & Interfaces

The roles of particles in enhancing membrane filtration: A review

(2019) Jingwei Wang et al.   JOURNAL OF MEMBRANE SCIENCE

Machine learning-enabled discovery and design of membrane-active peptides

(2018) Ernest Y. Lee et al.   BIOORGANIC & MEDICINAL CHEMISTRY

Evaluating variability with atomistic simulations: the effect of potential and calculation methodology on the modeling of lattice and elastic constants

(2018) Lucas M Hale et al.   MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING

Mordred: a molecular descriptor calculator

(2018) Hirotomo Moriwaki et al.   Journal of Cheminformatics

Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules

(2018) Rafael Gómez-Bombarelli et al.   ACS Central Science

Inverse design in search of materials with target functionalities

(2018) Alex Zunger   Nature Reviews Chemistry

Inverse molecular design using machine learning: Generative models for matter engineering

(2018) Benjamin Sanchez-Lengeling et al.   SCIENCE

Neural networks for the prediction of polymer permeability to gases

(2017) Hanaa Hasnaoui et al.   JOURNAL OF MEMBRANE SCIENCE

Polymer Informatics: Opportunities and Challenges

(2017) Debra J. Audus et al.   ACS Macro Letters

Computational identification of organic porous molecular crystals

(2016) Jack D. Evans et al.   CRYSTENGCOMM

Molecular graph convolutions: moving beyond fingerprints

(2016) Steven Kearnes et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach

(2016) Rafael Gómez-Bombarelli et al.   NATURE MATERIALS

Taking the Human Out of the Loop: A Review of Bayesian Optimization

(2016) Bobak Shahriari et al.   PROCEEDINGS OF THE IEEE

Machine Learning Strategy for Accelerated Design of Polymer Dielectrics

(2016) Arun Mannodi-Kanakkithodi et al.   Scientific Reports

Polymer-matrix nanocomposite membranes for water treatment

(2015) Jun Yin et al.   JOURNAL OF MEMBRANE SCIENCE

The Materials Genome Initiative, the interplay of experiment, theory and computation

(2014) Juan J. de Pablo et al.   CURRENT OPINION IN SOLID STATE & MATERIALS SCIENCE

Considerations for choosing and using force fields and interatomic potentials in materials science and engineering

(2013) Chandler A. Becker et al.   CURRENT OPINION IN SOLID STATE & MATERIALS SCIENCE

A review on membrane fabrication: Structure, properties and performance relationship

(2013) Boor Singh Lalia et al.   DESALINATION

Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)

(2013) James E. Saal et al.   JOM

The high-throughput highway to computational materials design

(2013) Stefano Curtarolo et al.   NATURE MATERIALS

Quantitative Structure–Property Relationship Modeling of Diverse Materials Properties

(2012) Tu Le et al.   CHEMICAL REVIEWS

When is Chemical Similarity Significant? The Statistical Distribution of Chemical Similarity Scores and Its Extreme Values

(2010) Pierre Baldi et al.   Journal of Chemical Information and Modeling

Extended-Connectivity Fingerprints

(2010) David Rogers et al.   Journal of Chemical Information and Modeling

PaDEL-descriptor: An open source software to calculate molecular descriptors and fingerprints

(2010) Chun Wei Yap   JOURNAL OF COMPUTATIONAL CHEMISTRY

Crosslinked poly(vinyl alcohol) membranes

(2009) Brian Bolto et al.   PROGRESS IN POLYMER SCIENCE

The upper bound revisited

(2008) Lloyd M. Robeson   JOURNAL OF MEMBRANE SCIENCE