Defect engineering of two-dimensional transition-metal dichalcogenides: applications, challenges, and opportunities
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 …
ubiquitous in a wide range of 2D transition-metal dichalcogenides (TMDs). They could be …
When machine learning meets 2D materials: a review
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 …
freedom (spin, excitonic, valley, sublattice, and layer pseudospin) together with the unique …
Recent advances on transition metal dichalcogenides for electrochemical energy conversion
Transition metal dichalcogenides (TMDCs) hold great promise for electrochemical energy
conversion technologies in view of their unique structural features associated with the …
conversion technologies in view of their unique structural features associated with the …
Converting nanotoxicity data to information using artificial intelligence and simulation
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 …
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
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 …
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
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 …
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
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 …
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
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 …
for the creation and optimization of electrocatalysts, which enhance key electrochemical …
Progress and challenges for memtransistors in neuromorphic circuits and systems
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 …
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
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 …
can supersede the high cost and scarcity of metal platinum (Pt) for the hydrogen evolution …