Papers citing Applications of machine learning in metal-organic frameworks
High Throughput Methods in the Synthesis, Characterization, and Optimization of Porous Materials
Advanced Materials · 2020
Ivan G. Clayson, Daniel Hewitt, Martin Hutereau, Tom Pope, Ben Slater
Read original paper ↗ ·Persistent homology advances interpretable machine learning for nanoporous materials.
arXiv (Cornell University) · 2020
Aditi S. Krishnapriyan, Joseph H. Montoya, Jens S. Hummelshøj, Dmitriy Morozov
Read original paper ↗ ·Towards a machine learned thermodynamics: exploration of free energy landscapes in molecular fluids, biological systems and for gas storage and separation in metal–organic frameworks
Molecular Systems Design & Engineering · 2020
Caroline Desgranges, Jérôme Delhommelle
Read original paper ↗ ·Towards explainable message passing networks for predicting carbon dioxide adsorption in metal-organic frameworks
arXiv (Cornell University) · 2020
Ali Raza, Faaiq Waqar, Árni Sturluson, Cory M. Simon, Xiaoli Z. Fern
Read original paper ↗ ·Machine Learning-Aided Computational Study of Metal–Organic Frameworks for Sour Gas Sweetening
The Journal of Physical Chemistry C · 2020
Eun Hyun Cho, Xuepeng Deng, Changlong Zou, Li‐Chiang Lin
Read original paper ↗ ·Stabilities and Electronic Structures of Transition Metal (Cu, Ag, Au, Ni, Pd, Pt) Cluster-Confined UiO-66
The Journal of Physical Chemistry C · 2020
Fangfang Wang, Liang Feng, Yunyi Zhang, Xujian Chen, De‐Li Chen, Weidong Zhu
Read original paper ↗ ·Two-dimensional conjugated microporous polymer films: fabrication strategies and potential applications
Polymer Chemistry · 2020
Zhengdong Liu, Yuhang Yin, Mustafa Eginligil, Laiyuan Wang, Juqing Liu, Wei Huang
Read original paper ↗ ·A Collection of More than 900 Gas Mixture Adsorption Experiments in Porous Materials from Literature Meta-Analysis
Industrial & Engineering Chemistry Research · 2020
Xuqing Cai, Farhad Gharagheizi, Lukas W. Bingel, Danny Shade, Krista S. Walton, David S. Sholl
Read original paper ↗ ·Bayesian optimization of nanoporous materials
Molecular Systems Design & Engineering · 2021
Aryan Deshwal, Cory M. Simon, Janardhan Rao Doppa
Read original paper ↗ ·Computational techniques for characterisation of electrically conductive MOFs: quantum calculations and machine learning approaches
Journal of Materials Chemistry C · 2021
Federica Zanca, Lawson T. Glasby, Sanggyu Chong, Siyu Chen, Jihan Kim, David Fairen‐Jiménez, Bartomeu Monserrat, Peyman Z. Moghadam
Read original paper ↗ ·Current Research Trends and Perspectives on Solid-State Nanomaterials in Hydrogen Storage
Research · 2021
Jie Zheng, Chen‐Gang Wang, Hui Wen Zhou, Enyi Ye, Jianwei Xu, Zibiao Li, Xian Jun Loh
Read original paper ↗ ·Finely tuned inverse design of metal–organic frameworks with user-desired Xe/Kr selectivity
Journal of Materials Chemistry A · 2021
Yunsung Lim, Junkil Park, Sangwon Lee, Jihan Kim
Read original paper ↗ ·Insights into the estimation of capacitance for carbon-based supercapacitors
RSC Advances · 2021
Majedeh Gheytanzadeh, Alireza Baghban, Sajjad Habibzadeh, Ahmad Mohaddespour, Otman Abida
Read original paper ↗ ·Metal–organic frameworks for chemical sensing devices
Materials Horizons · 2021
Joseph Funso Olorunyomi, Shu Teng Geh, Rachel A. Caruso, Cara M. Doherty
Read original paper ↗ ·Techno-economic analysis of metal–organic frameworks for adsorption heat pumps/chillers: from directional computational screening, machine learning to experiment
Journal of Materials Chemistry A · 2021
Zenan Shi, Xueying Yuan, Yaling Yan, Yuanlin Tang, Junjie Li, Hong Liang, Lianpeng Tong, Zhiwei Qiao
Read original paper ↗ ·Occurrence and removal of antibiotics from industrial wastewater
Environmental Chemistry Letters · 2021
Dilipkumar Akhil, Divya Lakshmi, P. Senthil Kumar, Dai‐Viet N. Vo, Ashokkumar Kartik
Read original paper ↗ ·Machine learning for advanced energy materials
Energy and AI · 2021
Liu Yun, Oladapo Christopher Esan, Zhefei Pan, Liang An
Read original paper ↗ ·Two-dimensional MOF and COF nanosheets for next-generation optoelectronic applications
Coordination Chemistry Reviews · 2021
Xiaohui Ren, Gengcheng Liao, Zhongjun Li, Hui Qiao, Yuan Zhang, Xiang Yu, Bing Wang, Hui Feng Tan, Li Shi, Xiang Qi, Han Zhang
Read original paper ↗ ·Computational catalysis for metal-organic frameworks: An overview
Coordination Chemistry Reviews · 2021
Gavin A. McCarver, Thayalan Rajeshkumar, Konstantinos D. Vogiatzis
Read original paper ↗ ·Nanoporous Material Recognition via 3D Convolutional Neural Networks: Prediction of Adsorption Properties
The Journal of Physical Chemistry Letters · 2021
Eun Hyun Cho, Li‐Chiang Lin
Read original paper ↗ ·A Recommendation System to Predict Missing Adsorption Properties of Nanoporous Materials
ChemRxiv · 2021
Árni Sturluson, Ali Raza, Grant D. McConachie, Daniel W. Siderius, Xiaoli Z. Fern, Cory M. Simon
Read original paper ↗ ·Adsorption behavior of metal-organic frameworks: From single simulation, high-throughput computational screening to machine learning
Computational Materials Science · 2021
Yaling Yan, Lulu Zhang, Shuhua Li, Hong Liang, Zhiwei Qiao
Read original paper ↗ ·Separation and Purification of Hydrocarbons with Porous Materials
Angewandte Chemie · 2021
Yaqi Wu, Bert Marc Weckhuysen
Read original paper ↗ ·Separation and Purification of Hydrocarbons with Porous Materials
Angewandte Chemie International Edition · 2021
Yaqi Wu, Bert Marc Weckhuysen
Read original paper ↗ ·Machine learning the quantum-chemical properties of metal–organic frameworks for accelerated materials discovery
Matter · 2021
Andrew Rosen, Shaelyn M. Iyer, Debmalya Ray, Zhenpeng Yao, Alán Aspuru‐Guzik, Laura Gagliardi, Justin M. Notestein, Randall Q. Snurr
Read original paper ↗ ·Discovering Relationships between OSDAs and Zeolites through Data Mining and Generative Neural Networks
ACS Central Science · 2021
Zach Jensen, Soonhyoung Kwon, Daniel Schwalbe‐Koda, Cecilia Paris, Rafael Gómez‐Bombarelli, Yuriy Román‐Leshkov, Avelino Corma, Manuel Moliner, Elsa Olivetti
Read original paper ↗ ·Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks
Scientific Reports · 2021
Aditi S. Krishnapriyan, Joseph H. Montoya, Maciej Harańczyk, Jens S. Hummelshøj, Dmitriy Morozov
Read original paper ↗ ·Machine Learning Meets with Metal Organic Frameworks for Gas Storage and Separation
Journal of Chemical Information and Modeling · 2021
Çiğdem Altıntaş, Ömer Faruk Altundal, Seda Keskın, Ramazan Yıldırım
Read original paper ↗ ·A review on metal-organic frameworks photoelectrochemistry: A headlight for future applications
Coordination Chemistry Reviews · 2021
Kheibar Dashtian, Saeed Shahbazi, Meysam Tayebi, Zohreh Masoumi
Read original paper ↗ ·Efficient Models for Predicting Temperature-Dependent Henry’s Constants and Adsorption Selectivities for Diverse Collections of Molecules in Metal–Organic Frameworks
The Journal of Physical Chemistry C · 2021
Xiaohan Yu, Sihoon Choi, Dai Tang, Andrew James Medford, David S. Sholl
Read original paper ↗ ·Artificial intelligence (AI) applications in adsorption of heavy metals using modified biochar
The Science of The Total Environment · 2021
Divya Lakshmi, Dilipkumar Akhil, Ashokkumar Kartik, Kannappan Panchamoorthy Gopinath, Jayaseelan Arun, Amit Bhatnagar, Jörg Rinklebe, Woong Kim, Muthusamy Govarthanan
Read original paper ↗ ·Topological methods for analysis and design of coordination polymers
Russian Chemical Reviews · 2021
Eugeny V. Alexandrov, Alexander P. Shevchenko, Nadezhda A. Nekrasova, Vladislav A. Blatov
Read original paper ↗ ·Recommendation System to Predict Missing Adsorption Properties of Nanoporous Materials
Chemistry of Materials · 2021
Árni Sturluson, Ali Raza, Grant D. McConachie, Daniel W. Siderius, Xiaoli Z. Fern, Cory M. Simon
Read original paper ↗ ·High-Throughput Screening of Anion-Pillared Metal–Organic Frameworks for the Separation of Light Hydrocarbons
The Journal of Physical Chemistry C · 2021
Chenkai Gu, Jing Liu, David S. Sholl
Read original paper ↗ ·Recommendation System to Predict Missing Adsorption Properties of Nanoporous Materials
Venue not supplied by source · 2021
Árni Sturluson, Ali Raza, Grant D. McConachie, Daniel W. Siderius, Xiaoli Z. Fern, Cory M. Simon
Read original paper ↗ ·Integrated metal–organic framework and pressure/vacuum swing adsorption process design: Descriptor optimization
AIChE Journal · 2021
Xiang Zhang, Teng Zhou, Kai Sundmacher
Read original paper ↗ ·Modeling Multicomponent Gas Adsorption in Nanoporous Materials with Two Versions of Nonlocal Classical Density Functional Theory
Industrial & Engineering Chemistry Research · 2021
Musen Zhou, Jingqi Wang, Jose Garcia, Yu Liu, Jianzhong Wu
Read original paper ↗ ·Parametrization of Nonbonded Force Field Terms for Metal–Organic Frameworks Using Machine Learning Approach
Journal of Chemical Information and Modeling · 2021
Vadim Korolev, Yuriy M. Nevolin, Thomas A. Manz, Pavel V. Protsenko
Read original paper ↗ ·Realizing the data-driven, computational discovery of metal-organic framework catalysts
Current Opinion in Chemical Engineering · 2021
Andrew Rosen, Justin M. Notestein, Randall Q. Snurr
Read original paper ↗ ·MOFs in the time domain
Nature Reviews Chemistry · 2021
Daniel J. Cerasale, Dominic C. Ward, Timothy L. Easun
Read original paper ↗ ·Combining crystal graphs and domain knowledge in machine learning to predict metal-organic frameworks performance in methane adsorption
Microporous and Mesoporous Materials · 2021
Ruihan Wang, Yurong Zou, Chunchun Zhang, Xin Wang, Mingli Yang, Dingguo Xu
Read original paper ↗ ·A New Machine Learning Framework for Efficient MOF Discovery: Application to Hydrogen Storage
Computer-aided chemical engineering/Computer aided chemical engineering · 2022
Teng Zhou, Zihao Wang, Kai Sundmacher
Read original paper ↗ ·Advances in metal–organic framework-based membranes
Chemical Society Reviews · 2022
Youdong Cheng, Shuvo Jit Datta, Sheng Zhou, Jiangtao Jia, Osama Shekhah, Mohamed Eddaoudi
Read original paper ↗ ·Application of transfer learning to predict diffusion properties in metal–organic frameworks
Molecular Systems Design & Engineering · 2022
Yunsung Lim, Jihan Kim
Read original paper ↗ ·Deep learning neural network potential for simulating gaseous adsorption in metal–organic frameworks
Materials Advances · 2022
Chi‐Ta Yang, Ishan Pandey, Dan Trinh, Chau‐Chyun Chen, Joshua D. Howe, Li‐Chiang Lin
Read original paper ↗ ·Explainable graph neural networks for organic cages
Digital Discovery · 2022
Qi Yuan, Filip Szczypiński, Kim E. Jelfs
Read original paper ↗ ·Large-scale cascade cooling performance evaluation of adsorbent/water working pairs by integrated mathematical modelling and machine learning
Journal of Materials Chemistry A · 2022
Zhilu Liu, Wei Hao Li, Shanshan Cai, Zhengkai Tu, Xiaobing Luo, Song Li
Read original paper ↗ ·Research Progresses of Metal-organic Framework HKUST-1-Based Membranes in Gas Separations※
化学学报 · 2022
Chong Li, Na Li, Li‐Mei Chang, Zhi‐Gang Gu, Jian Zhang
Read original paper ↗ ·Identification of optimal metal-organic frameworks by machine learning: Structure decomposition, feature integration, and predictive modeling
Computers & Chemical Engineering · 2022
Zihao Wang, Yageng Zhou, Teng Zhou, Kai Sundmacher
Read original paper ↗ ·MOFSocialNet: Exploiting Metal-Organic Framework Relationships via Social Network Analysis
Nanomaterials · 2022
Mehrdad Jalali, Manuel M. Tsotsalas, Christof Wöll
Read original paper ↗ ·