Abstract
Understanding the structural origins of the properties of amorphous materials remains one of the most important challenges in structural science. In this study we demonstrate that local 'structural simplicity', embodied by the degree to which atomic environments within a material are similar to each other, is powerful concept for rationalising the structure of canonical amorphous material amorphous silicon (a-Si). We show, by restraining a reverse Monte Carlo refinement against pair distribution function (PDF) data to be simpler, that the simplest model consistent with the PDF is a continuous random network (CRN). A further effect of producing a simple model of a-Si is the generation of a (pseudo)gap in the electronic density of states, suggesting that structural homogeneity drives electronic homogeneity. That this method produces models of a-Si that approach the state-of-the-art without the need for chemically specific restraints (beyond the assumption of homogeneity) suggests that simplicity-based refinement approaches may allow experiment-driven structural modelling techniques to be developed for the wide variety of amorphous semiconductors with strong local order.
Highlights
Amorphous materials are the crucial components of many next-generation technologies, including the high capacity anode material silicon[1] and the porous carbons used as supercapacitors[2] used for electrochemical storage, but despite their scientific and technological importance, many questions remain about their structures
In this study we demonstrate that local ‘structural simplicity’, embodied by the degree to which atomic environments within a material are similar to each other, is powerful concept for rationalising the structure of canonical amorphous material amorphous silicon (a-Si)
By restraining a reverse Monte Carlo refinement against pair distribution function (PDF) data to be simpler, that the simplest model consistent with the PDF is a continuous random network (CRN)
Summary
Amorphous materials are the crucial components of many next-generation technologies, including the high capacity anode material silicon[1] and the porous carbons used as supercapacitors[2] used for electrochemical storage, but despite their scientific and technological importance, many questions remain about their structures. Biasing the refinement to such that the variance in atomic PDFs is minimised (the INVERT approach which embodies the assumption that all atoms should have similar pair correlations) did allow RMC to produce models of a-Si and a-SiO2 with improved structural properties, these configurations were still lacking in some key electronic properties (e.g. absence of any band gap) [Fig. 1]27.
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