Metallization of diamond

Zhe Shi, Ming Dao, Evgenii Tsymbalov, Alexander Shapeev, Ju Li, Subra Suresh

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

Experimental discovery of ultralarge elastic deformation in nanoscale diamond and machine learning of its electronic and phonon structures have created opportunities to address new scientific questions. Can diamond, with an ultrawide bandgap of 5.6 eV, be completely metallized, solely under mechanical strain without phonon instability, so that its electronic bandgap fully vanishes? Through first-principles calculations, finite-element simulations validated by experiments, and neural network learning, we show here that metallization/demetallization as well as indirect-to-direct bandgap transitions can be achieved reversibly in diamond below threshold strain levels for phonon instability. We identify the pathway to metallization within six-dimensional strain space for different sample geometries. We also explore phonon-instability conditions that promote phase transition to graphite. These findings offer opportunities for tailoring properties of diamond via strain engineering for electronic, photonic, and quantum applications.

Original languageEnglish
Pages (from-to)24634-24639
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume117
Issue number40
DOIs
Publication statusPublished - 6 Oct 2020

Keywords

  • elastic strain engineering
  • machine learning
  • materials under extreme conditions
  • metallic diamond
  • multiscale simulations

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