Metastable materials discovery in the age of large-scale computation

Abstract

Computational materials discovery has been successful in predicting novel, technologically relevant materials. However, it has remained focused almost exclusively on finding ground-state structures. Now that the lower-hanging fruit has been found in many fields of application, materials exploration is moving toward metastable materials: higher energy phases that are stable at practical time scales. Because of the challenges associated with predicting which phases are realistic, this class of materials has remained relatively unexplored, despite numerous examples of metastable structures with unmatched properties (e.g., diamond). This article highlights recent advances in developing computational and theoretical methods for predicting useful and realizable metastable materials. Topics discussed cover (1) the latest strategies for identifying potential metastable phases, (2) methodologies for assessing which phases can be realized experimentally, and (3) current approaches to estimate the lifetime of metastable materials.

Colloidal Bismuth Chalcohalide Nanocrystals

“…Interestingly, the BiSCl NCs crystallized only in a previously unknown polymorph, thus confirming how the colloidal synthesis of nanoscopic crystals may give access to phases that cannot be stabilized at larger size scales. [29,49,50] The colloidal Bi chalcohalide NCs showed composition dependent band gaps and large optical absorption coefficients across the Vis spectral range, comparable to those of other semiconductors such as the Pb chalcogenides and halide perovskites. The colloidal BiEX NCs can be processed from the solution phase at ambient conditions without significant degradation: both surface chemistry modification and thermal annealing were exploited to prepare robust NC solids that can withstand photocorrosion more than the Pb chalcogenides and halide perovskite NCs.…”

Investigation of the Pb–Fe–Se Ternary System and the Synthesis of a Ternary Pb1–xFexSe Phase

“…Computationally predicting potentially stable materials with desired properties has become an important tool to increase the rate of innovation, outlined by the rise of computational − and experimental material databases. − However, a major hurdle has been the actual synthesis of the predicted compounds. − The convex hull approach, which compares the heat of formation of predicted compounds to that of a mixture of the known thermodynamically stable compounds, is commonly used for assessing the potential stability of predicted materials. ,, The local free-energy minima predicted in hull energy calculations, however, have systematic errors that depend on the functionals used. Furthermore, the ability to synthesize a given structure also depends on the magnitude of the energy barriers between minima and the volume of configuration space occupied by the local free-energy minima as well. ,, A second issue is the lack of experimental synthesis parameters and approaches that can be used to target a specific structure. Traditional synthesis approaches vary experimental parameters (composition, temperature, pressure, flux composition, etc.)…”

Free energy predictions for crystal stability and synthesisability

“…Another approach that has been employed to predict which metastable phases are more likely to be accessible is the concept of basin of attraction. 87 As any metastable structure is a local minimum on the energy landscape, they will each form a basin of attraction on the multidimensional configuration coordinate space. Intuitively, the (hyper)volume of the basin could be related to the accessibility of a certain phase, since a larger volume will result in more (random) atomic configurations ending up in that minimum.…”