Origins of hole traps in hydrogenated nanocrystalline and amorphous silicon revealed through machine learning

Tim Mueller, Eric Johlin, and Jeffrey C. Grossman

Phys. Rev. B 89, 115202 – Published 10 March 2014

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.

Received 29 October 2013

DOI:https://doi.org/10.1103/PhysRevB.89.115202

Authors & Affiliations

Tim Mueller¹, Eric Johlin², and Jeffrey C. Grossman^2,*

¹Department of Materials Science and Engineering, Johns Hopkins University, Baltimore Maryland 21218, USA
²Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge Massachusetts 02139, USA

^*Author to whom correspondence should be addressed: jcg@mit.edu

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Issue

Vol. 89, Iss. 11 — 15 March 2014

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Physical Review B

covering condensed matter and materials physics