Progress toward the computational discovery of new metal–organic framework adsorbents for energy applications

PZ Moghadam, YG Chung, RQ Snurr - Nature Energy, 2024 - nature.com
Metal–organic frameworks (MOFs) are a class of nanoporous material precisely synthesized
from molecular building blocks. MOFs could have a critical role in many energy …

Leveraging Machine Learning for Metal–Organic Frameworks: A Perspective

H Tang, L Duan, J Jiang - Langmuir, 2023 - ACS Publications
Metal–organic frameworks (MOFs) have attracted tremendous interest because of their
tunable structures, functionalities, and physiochemical properties. The nearly infinite …

Recyclable and Degradable Biomass-Based Water Vapor Sorbents for Efficient Atmospheric Water Harvesting

M Wu, Y Zhou, S Aleid, X Tang, Y Zhao… - ACS Sustainable …, 2024 - ACS Publications
Solar-driven sorption-based atmospheric water harvesting (SAWH) is an emerging
freshwater production technology for alleviating increasing water scarcity. However, existing …

Machine learning-assisted prediction of water adsorption isotherms and cooling performance

Z Liu, D Shen, S Cai, Z Tu, S Li - Journal of Materials Chemistry A, 2023 - pubs.rsc.org
Water adsorption in porous adsorbents has drawn considerable attention for its tremendous
potential in numerous environment-and energy-related applications. However, owing to the …

Computational Simulations of Metal–Organic Frameworks to Enhance Adsorption Applications

H Daglar, HC Gulbalkan, GO Aksu… - Advanced …, 2024 - Wiley Online Library
Abstract Metal–organic frameworks (MOFs), renowned for their exceptional porosity and
crystalline structure, stand at the forefront of gas adsorption and separation applications …

Insights into Isotherm Step and Pore-Filling Mechanisms for Water Adsorption in Covalent Organic Frameworks

D Brahma, N Dwarkanath… - Chemistry of …, 2024 - ACS Publications
Atmospheric water harvest using porous materials is an attractive solution to the water crisis.
The inflection point (α) in the water adsorption isotherm is one of the crucial criteria to screen …

Enhancing Ballistic Transport and C3–C4 Alcohol Dehydration through Machine Learning-Designed Cationic Graphene Oxide Membranes

L Sun, Q Liu, Z Liang, Z Yang… - … Sustainable Chemistry & …, 2024 - ACS Publications
Machine learning (ML) plays a pivotal role in material design and performance prediction.
However, research in ML related to fabricating two-dimensional (2D) graphene oxide (GO) …

Rapidly tailor metal–organic frameworks for arsenate removal using graph convolutional neural networks

Z Lin, J Chen, Y Fang, S Deng, H Li, Y Yang… - Separation and …, 2025 - Elsevier
Metal-organic frameworks (MOFs) are effective materials for the removal of highly toxic
arsenates (As (V)). However, the intricate structure–activity relationships of MOFs for As (V) …

[HTML][HTML] Towards a comprehensive understanding of atmospheric water harvesting technologies–a systematic and bibliometric review

EB Agyekum, F Odoi-Yorke, WF Mbasso, RO Darko… - Energy Reports, 2024 - Elsevier
An effective way to alleviate water scarcity is atmospheric water harvesting (AWH),
particularly for inland areas that lack liquid water sources. This study reviewed studies on …

Accelerating Discovery of Water Stable Metal− Organic Frameworks by Machine Learning

Z Zhang, F Pan, SA Mohamed, C Ji, K Zhang, J Jiang… - Small, 2024 - Wiley Online Library
Metal− organic frameworks (MOFs) provide an extensive design landscape for nanoporous
materials that drive innovation across energy and environmental fields. However, their …