Metalated covalent organic frameworks: from synthetic strategies to diverse applications

Q Guan, LL Zhou, YB Dong - Chemical Society Reviews, 2022 - pubs.rsc.org
Covalent organic frameworks (COFs) are a class of organic crystalline porous materials
discovered in the early 21st century that have become an attractive class of emerging …

Construction of covalent organic frameworks via multicomponent reactions

Q Guan, LL Zhou, YB Dong - Journal of the American Chemical …, 2023 - ACS Publications
Multicomponent reactions (MCRs) combine at least three reactants to afford the desired
product in a highly atom-economic way and are therefore viewed as efficient one-pot …

Programmable logic in metal–organic frameworks for catalysis

Y Shen, T Pan, L Wang, Z Ren, W Zhang… - Advanced …, 2021 - Wiley Online Library
Metal–organic frameworks (MOFs) have emerged as one of the most widely investigated
materials in catalysis mainly due to their excellent component tunability, high surface area …

New use for Lentinus edodes bran biochar for tetracycline removal

X Liu, Z Shao, Y Wang, Y Liu, S Wang, F Gao… - Environmental …, 2023 - Elsevier
The abuse of antibiotics poses a threat to the ecological environment and biological health,
and how to effectively reduce the residue of tetracycline (TC) in the environment has …

Material evolution with nanotechnology, nanoarchitectonics, and materials informatics: what will be the next paradigm shift in nanoporous materials?

W Chaikittisilp, Y Yamauchi, K Ariga - Advanced Materials, 2022 - Wiley Online Library
Materials science and chemistry have played a central and significant role in advancing
society. With the shift toward sustainable living, it is anticipated that the development of …

Machine learning meets with metal organic frameworks for gas storage and separation

C Altintas, OF Altundal, S Keskin… - Journal of Chemical …, 2021 - ACS Publications
The acceleration in design of new metal organic frameworks (MOFs) has led scientists to
focus on high-throughput computational screening (HTCS) methods to quickly assess the …

Machine‐Learning‐Assisted Nanozyme Design: Lessons from Materials and Engineered Enzymes

J Zhuang, AC Midgley, Y Wei, Q Liu, D Kong… - Advanced …, 2024 - Wiley Online Library
Nanozymes are nanomaterials that exhibit enzyme‐like biomimicry. In combination with
intrinsic characteristics of nanomaterials, nanozymes have broad applicability in materials …

Toward machine learning-enhanced high-throughput experimentation

NS Eyke, BA Koscher, KF Jensen - Trends in Chemistry, 2021 - cell.com
Recent literature suggests that the fields of machine learning (ML) and high-throughput
experimentation (HTE) have separately received considerable attention from chemists and …

Machine learning accelerates the investigation of targeted MOFs: performance prediction, rational design and intelligent synthesis

J Lin, Z Liu, Y Guo, S Wang, Z Tao, X Xue, R Li, S Feng… - Nano Today, 2023 - Elsevier
Metal-organic frameworks (MOFs) are a new class of nanoporous materials that are widely
used in various emerging fields due to their large specific surface area, high porosity and …

Transferable multilevel attention neural network for accurate prediction of quantum chemistry properties via multitask learning

Z Liu, L Lin, Q Jia, Z Cheng, Y Jiang… - Journal of chemical …, 2021 - ACS Publications
The development of efficient models for predicting specific properties through machine
learning is of great importance for the innovation of chemistry and material science …