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Computationally predicted energies and properties of defe... | ResearchHub
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Computationally predicted energies and properties of defects in GaN
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Authors
John Lyons
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John Lyons
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Chris Walle
Published
March 20, 2017
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Journal
npj Computational Materials
Topics
Computer Science
Materials Science
Mathematics
Physics
Artificial Intelligence
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DOI
10.1038/s41524-017-0014-2
License
CC-BY
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Supporters
Support the authors with ResearchCoin
Tip RSC
Journal
npj Computational Materials
Topics
Computer Science
Materials Science
Mathematics
Physics
Artificial Intelligence
Show all topics
DOI
10.1038/s41524-017-0014-2
License
CC-BY
Other Formats
PDF
