A process-level perspective of the impact of molecular force fields on the computational screening of MOFs for carbon capture

Conor Cleeton, Felipe Lopes de Oliveira, Rodrigo F. Neumann, Amir H. Farmahini, Binquan Luan, Mathias Steiner and Lev Sarkisov

Energy Environ. Sci., 2023, 16, 3899
DOI: 10.1039/D3EE00858D

High-aspect-ratio nanostructured hydroxyapatite: towards new functionalities for a classical material

Anna Diez-Escudero, Montserrat Espanol and Maria-Pau Ginebra

Chem. Sci., 2024, 15, 55
DOI: 10.1039/D3SC05344J

AI-driven advances in metal–organic frameworks: from data to design and applications

Yuhang Song, Jiakai Li, Dongzhi Chi, Zhengtao Xu, Jie Liu, Mingxi Chen and Ziyu Wang

Chem. Commun., 2025, 61, 15972
DOI: 10.1039/D5CC04220H

Adaptive Allocation of Monte Carlo Samples for Efficient, Multifidelity Computational Screening of Metal–Organic Frameworks

Qia Ke, N. Scott Bobbitt, Jana Doppa, Huazheng Wang and Cory M. Simon

J. Chem. Theory Comput., 2026, 22, 558
DOI: 10.1021/acs.jctc.5c01431

Data-Driven Insights on the Impact of Functionalization on Metal–Organic Framework Free Energies

Fernando Fajardo-Rojas, Ryther Anderson, Mingwei Li, Remco Chang and Diego A. Gómez-Gualdrón

Chem. Mater., 2025, 37, 5502
DOI: 10.1021/acs.chemmater.5c00129

Advanced porous MOF materials and technologies for high-efficiency ppm-level toxic gas separation

Shouyi Hu, Guijun Guo, Jiaxi Zhang, Mehak Nawaz Khan, Shuanghua Xu, Fan Yang, Brian W. Schwandt, Zhigang Hu and Jianxin Zou

Materials Science and Engineering: R: Reports, 2024, 161, 100874
DOI: 10.1016/j.mser.2024.100874

Machine Learning-Guided High-Throughput Screening of Metal–Organic Frameworks for Atmospheric Ozone Capture: A Computational Materials Informatics Approach

Saiwei Ge, Zhiqiang Wang and Jingjing Pei

J. Chem. Inf. Model., 2025, 65, 11778
DOI: 10.1021/acs.jcim.5c02152

Multimode propellant discovery: a computational high-throughput screening paradigm

Shehan M. Parmar, Orion Cohen, Kristin A. Persson, Ghanshyam L. Vaghjiani, Jesse G. McDaniel and Richard E. Wirz

J Electr Propuls, 2026, 5
DOI: 10.1007/s44205-025-00174-6

Interactions of Common Synthesis Solvents with MOFs Studied via Free Energies of Solvation: Implications on Stability and Polymorph Selection

Fernando Fajardo-Rojas, Ryther Anderson, Katherine Ardila, Alexander J. Pak and Diego A. Gómez-Gualdrón

Chem. Mater., 2026, 38, 607
DOI: 10.1021/acs.chemmater.5c01410

A New Era of Modeling MOF‐Based Membranes: Cooperation of Theory and Data Science

Hakan Demir and Seda Keskin

Macro Materials & Eng, 2024, 309
DOI: 10.1002/mame.202300225

Two-dimensional metal-organic frameworks (2D–MOFs) as a carrier for enzyme immobilization: A review on design and bio-applications

Pravin D. Patil, Niharika Gargate, Manishkumar S. Tiwari and Shamraja S. Nadar

International Journal of Biological Macromolecules, 2025, 291, 138984
DOI: 10.1016/j.ijbiomac.2024.138984

Industrialising Metal–Organic Frameworks─Bridging Laboratory Innovation and Future Applications

Zixi Xie and Jingwei Hou

Ind. Eng. Chem. Res., 2025, 64, 7941
DOI: 10.1021/acs.iecr.5c00579

Metal–Organic Frameworks for Phthalate Capture

Ezgi Gulcay-Ozcan, Paul Iacomi, Pedro F. Brântuas, Guillaume Rioland, Guillaume Maurin and Sabine Devautour-Vinot

ACS Appl. Mater. Interfaces, 2023, 15, 48216
DOI: 10.1021/acsami.3c10481

Challenges in characterizing adsorbents for gas storage and separation

D. P. Broom

Adsorption, 2024, 30, 1565
DOI: 10.1007/s10450-023-00424-9

Artificial Intelligence Meets Laboratory Automation in Discovery and Synthesis of Metal–Organic Frameworks: A Review

Yiming Zhao, Yongjia Zhao, Jian Wang and Zhuo Wang

Ind. Eng. Chem. Res., 2025, 64, 4637
DOI: 10.1021/acs.iecr.4c04636

Highly Accurate and Fast Prediction of MOF Free Energy via Machine Learning

Andre Niyongabo Rubungo, Fernando Fajardo-Rojas, Diego A. Gómez-Gualdrón and Adji Bousso Dieng

J. Am. Chem. Soc., 2025, 147, 48035
DOI: 10.1021/jacs.5c13960

Computationally Guided Discovery of Metal–Organic Frameworks with One-Dimensional Channels for Highly Selective Adsorption of Xylene Isomers

Saad Aldin Mohamed, Nengxiu Zhu, Rui Zheng, Dan Zhao and Jianwen Jiang

ACS Nano, 2026
DOI: 10.1021/acsnano.6c02484

Advancing from MOFs and COFs to Functional Macroscopic Porous Constructs

Seyyed Alireza Hashemi, Ahmadreza Ghaffarkhah, Ali Akbar Isari, Mahyar Panahi‐Sarmad, Feng Jiang, Orlando J. Rojas, Stefan Wuttke, Mircea Dincă and Mohammad Arjmand

Advanced Materials, 2025, 37
DOI: 10.1002/adma.202411617

Computation-informed optimization of Ni(PyC)2 functionalization for noble gas separations

Nickolas Gantzler, Min-Bum Kim, Alexander Robinson, Maxwell W. Terban, Sanjit Ghose, Robert E. Dinnebier, Arthur Henry York, Davide Tiana, Cory M. Simon and Praveen K. Thallapally

Cell Reports Physical Science, 2022, 3, 101025
DOI: 10.1016/j.xcrp.2022.101025

Functional Material Systems Enabled by Automated Data Extraction and Machine Learning

Payam Kalhor, Nicole Jung, Stefan Bräse, Christof Wöll, Manuel Tsotsalas and Pascal Friederich

Adv Funct Materials, 2024, 34
DOI: 10.1002/adfm.202302630

Machine learning-enabled design of MOF-based membranes for efficient C3H8-selective separation

Zhengqing Zhang, Min Wang, Wenjing Tian, Xiaohao Cao, Mengdi Zhao, Yuxiu Sun and Zhihua Qiao

Journal of Membrane Science, 2026, 745, 125244
DOI: 10.1016/j.memsci.2026.125244

Multiscale Computational Approaches toward the Understanding of Materials

Marta Bordonhos, Tiago L. P. Galvão, José R. B. Gomes, José D. Gouveia, Miguel Jorge, Mirtha A. O. Lourenço, José M. Pereira, Germán Pérez‐Sánchez, Moisés L. Pinto, Carlos M. Silva, João Tedim and Bruno Zêzere

Advcd Theory and Sims, 2023, 6
DOI: 10.1002/adts.202200628