Defect engineering of two-dimensional transition-metal dichalcogenides: applications, challenges, and opportunities

Q Liang, Q Zhang, X Zhao, M Liu, ATS Wee - ACS nano, 2021 - ACS Publications
Atomic defects, being the most prevalent zero-dimensional topological defects, are
ubiquitous in a wide range of 2D transition-metal dichalcogenides (TMDs). They could be …

When machine learning meets 2D materials: a review

B Lu, Y **a, Y Ren, M **e, L Zhou, G Vinai… - Advanced …, 2024 - Wiley Online Library
The availability of an ever‐expanding portfolio of 2D materials with rich internal degrees of
freedom (spin, excitonic, valley, sublattice, and layer pseudospin) together with the unique …

Recent advances on transition metal dichalcogenides for electrochemical energy conversion

X Wu, H Zhang, J Zhang, XW Lou - Advanced Materials, 2021 - Wiley Online Library
Transition metal dichalcogenides (TMDCs) hold great promise for electrochemical energy
conversion technologies in view of their unique structural features associated with the …

Converting nanotoxicity data to information using artificial intelligence and simulation

X Yan, T Yue, DA Winkler, Y Yin, H Zhu… - Chemical …, 2023 - ACS Publications
Decades of nanotoxicology research have generated extensive and diverse data sets.
However, data is not equal to information. The question is how to extract critical information …

Engineered 2D transition metal dichalcogenides—a vision of viable hydrogen evolution reaction catalysis

L Lin, P Sherrell, Y Liu, W Lei, S Zhang… - Advanced Energy …, 2020 - Wiley Online Library
The hydrogen evolution reaction (HER) is an emerging key technology to provide clean,
renewable energy. Current state‐of‐the‐art catalysts still rely on expensive and rare noble …

Machine learning in electron microscopy for advanced nanocharacterization: current developments, available tools and future outlook

M Botifoll, I Pinto-Huguet, J Arbiol - Nanoscale Horizons, 2022 - pubs.rsc.org
In the last few years, electron microscopy has experienced a new methodological paradigm
aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine …

Atomic‐Level Design of Active Site on Two‐Dimensional MoS2 toward Efficient Hydrogen Evolution: Experiment, Theory, and Artificial Intelligence Modelling

C Sun, L Wang, W Zhao, L **e, J Wang… - Advanced Functional …, 2022 - Wiley Online Library
Atom‐economic catalysts open a new era of computationally driven atomistic design of
catalysts. Rationally manipulating the structures of the catalyst with atomic‐level precision …

[HTML][HTML] Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation

R Ding, J Chen, Y Chen, J Liu, Y Bando… - Chemical Society …, 2024 - pubs.rsc.org
Machine learning (ML) is rapidly emerging as a pivotal tool in the hydrogen energy industry
for the creation and optimization of electrocatalysts, which enhance key electrochemical …

Progress and challenges for memtransistors in neuromorphic circuits and systems

X Yan, JH Qian, VK Sangwan… - Advanced Materials, 2022 - Wiley Online Library
Due to the increasing importance of artificial intelligence (AI), significant recent effort has
been devoted to the development of neuromorphic circuits that seek to emulate the energy …

Oxygen-facilitated dynamic active-site generation on strained MoS2 during photo-catalytic hydrogen evolution

L Wang, L **e, W Zhao, S Liu, Q Zhao - Chemical Engineering Journal, 2021 - Elsevier
Molybdenum disulfide (MoS 2) is considered as one of the most effective materials which
can supersede the high cost and scarcity of metal platinum (Pt) for the hydrogen evolution …