Origins of hole traps in hydrogenated nanocrystalline and amorphous silicon revealed through machine learning
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Mueller-2014-Origins of hole traps.pdf
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2.56 MB
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Author(s)
Mueller, Timothy K.
Grossman, Jeffrey C.
Johlin, Eric Carl
Date Issued
March 2014
Journal
Physical Review B
Publisher
American Physical Society
Citation
Mueller, Tim, Eric Johlin, and Jeffrey C. Grossman. “Origins of Hole Traps in Hydrogenated Nanocrystalline and Amorphous Silicon Revealed through Machine Learning.” Phys. Rev. B 89, no. 11 (March 2014). © 2014 American Physical Society
Version
Final published version
Abstract
Genetic programming is used to identify the structural features most strongly associated with hole traps in hydrogenated nanocrystalline silicon with very low crystalline volume fraction. The genetic programming algorithm reveals that hole traps are most strongly associated with local structures within the amorphous region in which a single hydrogen atom is bound to two silicon atoms (bridge bonds), near fivefold coordinated silicon (floating bonds), or where there is a particularly dense cluster of many silicon atoms. Based on these results, we propose a mechanism by which deep hole traps associated with bridge bonds may contribute to the Staebler-Wronski effect.
MIT Department
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Massachusetts Institute of Technology. Department of Mechanical Engineering
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1103/PhysRevB.89.115202
