Understanding, discovery, and synthesis of 2D materials enabled by machine learning
Machine learning (ML) is becoming an effective tool for studying 2D materials. Taking as
input computed or experimental materials data, ML algorithms predict the structural …
input computed or experimental materials data, ML algorithms predict the structural …
Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation
The ever-increasing demand for novel materials with superior properties inspires retrofitting
traditional research paradigms in the era of artificial intelligence and automation. An …
traditional research paradigms in the era of artificial intelligence and automation. An …
Material evolution with nanotechnology, nanoarchitectonics, and materials informatics: what will be the next paradigm shift in nanoporous materials?
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 …
society. With the shift toward sustainable living, it is anticipated that the development of …
Exfoliation mechanisms of 2D materials and their applications
Due to the strong in-plane but weak out-of-plane bonding, it is relatively easy to separate
nanosheets of two-dimensional (2D) materials from their respective bulk crystals. This …
nanosheets of two-dimensional (2D) materials from their respective bulk crystals. This …
Deep learning for material synthesis and manufacturing systems: A review
V Bhuvaneswari, M Priyadharshini, C Deepa… - Materials Today …, 2021 - Elsevier
Deep learning (DL) techniques are the evolutionary methods of machine learning (ML)
advancements in which current industrial operations are focusing and this method is way far …
advancements in which current industrial operations are focusing and this method is way far …
Progress and prospects in two-dimensional magnetism of van der Waals materials
Abstract Two-dimensional (2D) magnetism in van der Waals (vdW) atomic crystals and
moiré superlattices has emerged as a topic of tremendous interest in the fields of condensed …
moiré superlattices has emerged as a topic of tremendous interest in the fields of condensed …
When Machine Learning Meets 2D Materials: A Review
B Lu, Y Xia, Y Ren, M Xie, 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 …
freedom (spin, excitonic, valley, sublattice, and layer pseudospin) together with the unique …
[HTML][HTML] Recent advances in bioinspired vision sensor arrays based on advanced optoelectronic materials
H Li, H Yu, D Wu, X Sun, L Pan - APL Materials, 2023 - pubs.aip.org
Animals can learn about the outside world in many ways, and the visual organ is a key
organ for acquiring information about the outside world. With the continuous development of …
organ for acquiring information about the outside world. With the continuous development of …
Deep learning enabled inorganic material generator
Recent years have witnessed utilization of modern machine learning approaches for
predicting the properties of materials using available datasets. However, to identify potential …
predicting the properties of materials using available datasets. However, to identify potential …
3D deep learning enables accurate layer mapping of 2D materials
Layered, two-dimensional (2D) materials are promising for next-generation photonics
devices. Typically, the thickness of mechanically cleaved flakes and chemical vapor …
devices. Typically, the thickness of mechanically cleaved flakes and chemical vapor …