reviewAdvanced ScienceJan 26, 2024GOLD OA

When Machine Learning Meets 2D Materials: A Review

BLBin LuYXYuze XiaYRYuqian RenXMXie MiaomiaoLZLiguo Zhou

Northwestern Polytechnical University · Yangtze River Delta Physics Research Center (China) · +7 more institutions

PubMed
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Abstract

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 ability to tailor heterostructures made layer by layer in a precisely chosen stacking sequence and relative crystallographic alignments, offers an unprecedented platform for realizing materials by design. However, the breadth of multi-dimensional parameter space and massive data sets involved is emblematic of complex, resource-intensive experimentation, which not only challenges the current state of the art but also renders exhaustive sampling untenable. To this end, machine learning, a very powerful data-driven approach and…

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122
total citations
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13.30
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100%
References
261
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Authors

11

Topics & keywords

Topics
Keywords
  • Computer science
  • Stacking
  • Artificial intelligence
  • Resource (disambiguation)
  • Layer (electronics)
  • Data science
  • Machine learning
  • Nanotechnology
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