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Bandgap prediction by deep learning in configurationally hybridized graphene and boron nitride

Research article (npj Computational Materials, 2019) · cited 136× · AI/ML
academia openalex:W2915603306
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Bandgap prediction by deep learning in configurationally hybridized graphene and boron nitride

Summary

Bandgap prediction by deep learning in configurationally hybridized graphene and boron nitride is a scholarly article[1].

Key Facts

  • Bandgap prediction by deep learning in configurationally hybridized graphene and boron nitride's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Bandgap prediction by deep learning in configurationally hybridized graphene and boron nitride. Retrieved May 24, 2026, from https://4ort.xyz/entity/bandgap-prediction-by-deep-learning-in-configurationally-hybridized-graphene-and-boron-nitride
MLA “Bandgap prediction by deep learning in configurationally hybridized graphene and boron nitride.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/bandgap-prediction-by-deep-learning-in-configurationally-hybridized-graphene-and-boron-nitride.
BibTeX @misc{4ortxyz_bandgap-prediction-by-deep-learning-in-configurationally-hybridized-graphene-and-boron-nitride_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Bandgap prediction by deep learning in configurationally hybridized graphene and boron nitride}}, year = {2026}, url = {https://4ort.xyz/entity/bandgap-prediction-by-deep-learning-in-configurationally-hybridized-graphene-and-boron-nitride}, note = {Accessed: 2026-05-24}}
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