![accurate 4-3056 accurate 4-3056](https://pubs.rsc.org/image/article/2020/me/c9me00163h/c9me00163h-f1_hi-res.gif)
An Ultramicroporous Nickel-Based Metal–Organic Framework for Adsorption Separation of CO2 over N2 or CH4. Yongwei Chen, Houxiao Wu, Daofei Lv, Wenyuan Yang, Zhiwei Qiao, Zhong Li, Qibin Xia.Role of Pore Chemistry and Topology in the CO2 Capture Capabilities of MOFs: From Molecular Simulation to Machine Learning.
![accurate 4-3056 accurate 4-3056](https://pubs.rsc.org/image/article/2021/CS/d1cs00558h/d1cs00558h-f15_hi-res.gif)
Ryther Anderson, Jacob Rodgers, Edwin Argueta, Achay Biong, Diego A.ACS Applied Materials & Interfaces 2018, 10 Unusual Moisture-Enhanced CO2 Capture within Microporous PCN-250 Frameworks. Yongwei Chen, Zhiwei Qiao, Jiali Huang, Houxiao Wu, Jing Xiao, Qibin Xia, Hongxia Xi, Jun Hu, Jian Zhou, Zhong Li.Journal of Chemical Theory and Computation 2019, 15 Evaluating Charge Equilibration Methods To Generate Electrostatic Fields in Nanoporous Materials. The Journal of Physical Chemistry C 2019, 123 Robust Machine Learning Models for Predicting High CO2 Working Capacity and CO2/H2 Selectivity of Gas Adsorption in Metal Organic Frameworks for Precombustion Carbon Capture. Hana Dureckova, Mykhaylo Krykunov, Mohammad Zein Aghaji, Tom K.The Journal of Physical Chemistry Letters 2019, 10 C-GeM: Coarse-Grained Electron Model for Predicting the Electrostatic Potential in Molecules. ACS Applied Materials & Interfaces 2020, 12 Machine Learning Enabled Tailor-Made Design of Application-Specific Metal–Organic Frameworks. Xiangyu Zhang, Kexin Zhang, Yongjin Lee.In Silico Discovery of Covalent Organic Frameworks for Carbon Capture. Deeg, Daiane Damasceno Borges, Daniele Ongari, Nakul Rampal, Leopold Talirz, Aliaksandr V. The Journal of Physical Chemistry C 2020, 124 Efficient and Accurate Charge Assignments via a Multilayer Connectivity-Based Atom Contribution (m-CBAC) Approach. Transferable and Extensible Machine Learning-Derived Atomic Charges for Modeling Hybrid Nanoporous Materials. Accelerating Discovery of Metal–Organic Frameworks for Methane Adsorption with Hierarchical Screening and Deep Learning. Ruihan Wang, Yeshuang Zhong, Leming Bi, Mingli Yang, Dingguo Xu.The Journal of Physical Chemistry C 2021, 125 Metal–Organic Frameworks for Xylene Separation: From Computational Screening to Machine Learning. Zhiwei Qiao, Yaling Yan, Yaxing Tang, Hong Liang, Jianwen Jiang.Journal of Chemical Theory and Computation 2021, 17 Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal–Organic Frameworks. Srinivasu Kancharlapalli, Arun Gopalan, Maciej Haranczyk, Randall Q.Performance-Based Screening of Porous Materials for Carbon Capture. Farmahini, Shreenath Krishnamurthy, Daniel Friedrich, Stefano Brandani, Lev Sarkisov. This article is cited by 67 publications.