Combining crystal graphs and domain knowledge in machine learning to predict metal-organic frameworks performance in methane adsorption
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Combining crystal graphs and domain knowledge in machine learning to predict metal-organic frameworks performance in methane adsorption
Authors
Keywords
Metal-organic frameworks, Methane adsorption, Graph convolution neural network, Domain knowledge, Transfer learning, Virtual screening
Journal
MICROPOROUS AND MESOPOROUS MATERIALS
Volume 331, Issue -, Pages 111666
Publisher
Elsevier BV
Online
2021-12-30
DOI
10.1016/j.micromeso.2021.111666
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Machine Learning Meets with Metal Organic Frameworks for Gas Storage and Separation
- (2021) Cigdem Altintas et al. Journal of Chemical Information and Modeling
- Machine learning and descriptor selection for the computational discovery of metal-organic frameworks
- (2021) Krishnendu Mukherjee et al. MOLECULAR SIMULATION
- A microporous metal–organic framework with triangular channels for C2H6/C2H4 adsorption separation
- (2021) Qiang Gao et al. SEPARATION AND PURIFICATION TECHNOLOGY
- Adsorption Isotherm Predictions for Multiple Molecules in MOFs Using the Same Deep Learning Model
- (2020) Ryther Anderson et al. Journal of Chemical Theory and Computation
- A Universal Machine Learning Algorithm for Large-Scale Screening of Materials
- (2020) George S. Fanourgakis et al. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
- Uncertainty-Quantified Hybrid Machine Learning/Density Functional Theory High Throughput Screening Method for Crystals
- (2020) Juhwan Noh et al. Journal of Chemical Information and Modeling
- Transfer Learning Study of Gas Adsorption in Metal–Organic Frameworks
- (2020) Ruimin Ma et al. ACS Applied Materials & Interfaces
- Big-Data Science in Porous Materials: Materials Genomics and Machine Learning
- (2020) Kevin Maik Jablonka et al. CHEMICAL REVIEWS
- Message Passing Neural Networks for Partial Charge Assignment to Metal-Organic Frameworks
- (2020) Ali Raza et al. Journal of Physical Chemistry C
- Machine-Learning-Based Prediction of Methane Adsorption Isotherms at Varied Temperatures for Experimental Adsorbents
- (2020) Seo-Yul Kim et al. Journal of Physical Chemistry C
- Understanding the diversity of the metal-organic framework ecosystem
- (2020) Seyed Mohamad Moosavi et al. Nature Communications
- Structure–Activity Relationships That Identify Metal–Organic Framework Catalysts for Methane Activation
- (2019) Andrew S. Rosen et al. ACS Catalysis
- Understanding Quantitative Relationship Between Methane Storage Capacities and Characteristic Properties of Metal Organic Frameworks Based on Machine Learning
- (2019) Xuanjun Wu et al. Journal of Physical Chemistry C
- Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals
- (2019) Chi Chen et al. CHEMISTRY OF MATERIALS
- Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm
- (2019) Stephen Wu et al. npj Computational Materials
- Predicting Materials Properties with Little Data Using Shotgun Transfer Learning
- (2019) Hironao Yamada et al. ACS Central Science
- 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
- Artificial Intelligence to Accelerate the Discovery of N2 Electroreduction Catalysts
- (2019) Myungjoon Kim et al. CHEMISTRY OF MATERIALS
- Graph Convolutional Neural Networks as “General-Purpose” Property Predictors: The Universality and Limits of Applicability
- (2019) Vadim Korolev et al. Journal of Chemical Information and Modeling
- New Model for Predicting Adsorption of Polar Molecules in Metal–Organic Frameworks with Unsaturated Metal Sites
- (2018) Christopher Campbell et al. Journal of Physical Chemistry Letters
- Recent advances in gas storage and separation using metal–organic frameworks
- (2018) Hao Li et al. Materials Today
- Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties
- (2018) Tian Xie et al. PHYSICAL REVIEW LETTERS
- First principles Monte Carlo simulations of unary and binary adsorption: CO2, N2, and H2O in Mg-MOF-74
- (2018) Evgenii O. Fetisov et al. CHEMICAL COMMUNICATIONS
- Force-Field Prediction of Materials Properties in Metal-Organic Frameworks
- (2017) Peter G. Boyd et al. Journal of Physical Chemistry Letters
- A Metal-Organic Framework with a Pore Size/Shape Suitable for Strong Binding and Close Packing of Methane
- (2016) Jiao-Min Lin et al. ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
- Computational characterization and prediction of metal–organic framework properties
- (2016) François-Xavier Coudert et al. COORDINATION CHEMISTRY REVIEWS
- Review of Molecular Simulations of Methane Storage in Metal-Organic Frameworks
- (2016) Seung-Joon Lee et al. JOURNAL OF NANOSCIENCE AND NANOTECHNOLOGY
- Force Field Development from Periodic Density Functional Theory Calculations for Gas Separation Applications Using Metal–Organic Frameworks
- (2016) Rocio Mercado et al. Journal of Physical Chemistry C
- Ab Initio Prediction of Adsorption Isotherms for Small Molecules in Metal–Organic Frameworks
- (2016) Arpan Kundu et al. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
- Predicting Methane Storage in Open-Metal-Site Metal–Organic Frameworks
- (2015) Hyun Seung Koh et al. Journal of Physical Chemistry C
- RASPA: molecular simulation software for adsorption and diffusion in flexible nanoporous materials
- (2015) David Dubbeldam et al. MOLECULAR SIMULATION
- Methane storage in metal–organic frameworks
- (2014) Yabing He et al. CHEMICAL SOCIETY REVIEWS
- Can Metal–Organic Frameworks Attain New DOE Targets for On-Board Methane Storage by Increasing Methane Heat of Adsorption?
- (2014) Seung-Joon Lee et al. Journal of Physical Chemistry C
- Multiscale Modeling of Water in Mg-MOF-74: From Electronic Structure Calculations to Adsorption Isotherms
- (2014) A. N. Rudenko et al. Journal of Physical Chemistry C
- Methane Storage in Metal-Substituted Metal–Organic Frameworks: Thermodynamics, Usable Capacity, and the Impact of Enhanced Binding Sites
- (2014) Malay Kumar Rana et al. Journal of Physical Chemistry C
- A Porous Metal–Organic Framework with Dynamic Pyrimidine Groups Exhibiting Record High Methane Storage Working Capacity
- (2014) Bin Li et al. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
- Simultaneously high gravimetric and volumetric methane uptake characteristics of the metal–organic framework NU-111
- (2013) Yang Peng et al. CHEMICAL COMMUNICATIONS
- Coexistence of cages and one-dimensional channels in a porous MOF with high H2 and CH4 uptakes
- (2013) Jiandong Pang et al. CHEMICAL COMMUNICATIONS
- A series of metal–organic frameworks with high methane uptake and an empirical equation for predicting methane storage capacity
- (2013) Yabing He et al. Energy & Environmental Science
- Large-Scale Quantitative Structure–Property Relationship (QSPR) Analysis of Methane Storage in Metal–Organic Frameworks
- (2013) Michael Fernandez et al. Journal of Physical Chemistry C
- Methane Storage in Metal–Organic Frameworks: Current Records, Surprise Findings, and Challenges
- (2013) Yang Peng et al. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
- The Chemistry and Applications of Metal-Organic Frameworks
- (2013) H. Furukawa et al. SCIENCE
- Evaluating metal–organic frameworks for natural gas storage
- (2013) Jarad A. Mason et al. Chemical Science
- A highly porous metal–organic framework, constructed from a cuboctahedral super-molecular building block, with exceptionally high methane uptake
- (2012) Ulrich Stoeck et al. CHEMICAL COMMUNICATIONS
- Accurate Computation of Gas Uptake in Microporous Organic Molecular Crystals
- (2012) Wenliang Li et al. Journal of Physical Chemistry C
- A high connectivity metal–organic framework with exceptional hydrogen and methane uptake capacities
- (2012) Demin Liu et al. Chemical Science
- Review and Analysis of Molecular Simulations of Methane, Hydrogen, and Acetylene Storage in Metal–Organic Frameworks
- (2011) Rachel B. Getman et al. CHEMICAL REVIEWS
- Algorithms and tools for high-throughput geometry-based analysis of crystalline porous materials
- (2011) Thomas F. Willems et al. MICROPOROUS AND MESOPOROUS MATERIALS
- Large-scale screening of hypothetical metal–organic frameworks
- (2011) Christopher E. Wilmer et al. Nature Chemistry
- Metal-Organic Frameworks with Exceptionally High Methane Uptake: Where and How is Methane Stored?
- (2010) Hui Wu et al. CHEMISTRY-A EUROPEAN JOURNAL
- A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu
- (2010) Stefan Grimme et al. JOURNAL OF CHEMICAL PHYSICS
- Methane storage mechanism in the metal-organic framework Cu3(btc)2: An in situ neutron diffraction study
- (2010) Juergen Getzschmann et al. MICROPOROUS AND MESOPOROUS MATERIALS
- Ultrahigh Porosity in Metal-Organic Frameworks
- (2010) H. Furukawa et al. SCIENCE
- Stabilization of Metal−Organic Frameworks with High Surface Areas by the Incorporation of Mesocavities with Microwindows
- (2009) Dan Zhao et al. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
- High-Capacity Methane Storage in Metal−Organic Frameworks M2(dhtp): The Important Role of Open Metal Sites
- (2009) Hui Wu et al. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationAdd 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