Search methods for inorganic materials crystal structure prediction

Abstract

Crystal structure prediction (CSP) is the problem of determining the most stable crystalline arrangements of materials given their chemical compositions. In general, CSP methodologies include two algorithmic steps, namely a method for assessing material stability of any given design, and a search algorithm for exploring the design space. For inorganic crystals, in particular, the most critical aspect is to develop an effective search algorithm. This paper summarizes previous research and discusses recent progress in search methods developed for inorganic CSP. Empirical methods, guided-sampling algorithms, and more recent data-driven approaches are discussed. Additionally, we describe a mathematical optimization-based search paradigm that has been recently introduced as an alternative CSP approach. A semiconductor nanowire design approach is then presented to illustrate this paradigm.