Exploiting Defects in a Jam: Phase-change materials that can readily switch between crystalline and amorphous states are increasingly finding use in nonvolatile memory devices (see the Perspective byHewak and Gholipour). Using high-resolution transmission electron microscopy,Namet al.(p.1561) show that for Ge₂Sb₂Te₅, the application of an electric field drives crystal dislocations in one direction, leading to their accumulation and eventual jamming, which causes the phase transition.Lokeet al.(p.1566) found that by applying a constant low voltage to Ge₂Sb₂Te₅, they could accelerate its phase-switching speeds, without harming the long-term stability of the switched state.

Amorphous silicon (a-Si) is a widely studied non-crystalline material, and yet the subtle details of its atomistic structure are still unclear. Here, we show that accurate structural models of a-Si can be obtained using a machine-learning-based interatomic potential. Our best a-Si network is obtained by simulated cooling from the melt at a rate of 10¹¹ K/s (that is, on the 10 ns timescale), contains less than 2% defects, and agrees with experiments regarding excess energies, diffraction data, and ²⁹Si NMR chemical shifts. We show that this level of quality is impossible to achieve with faster quench simulations. We then generate a 4,096-atom system which correctly reproduces the magnitude of the first sharp diffraction peak (FSDP) in the structure factor, achieving the closest agreement with experiments to date. Our study demonstrates the broader impact of machine-learning potentials for elucidating structures and properties of technologically important amorphous materials.

Amorphous and crystalline materials differ in their long-range structural order. On the other hand, short-range order in amorphous and crystalline materials often appears similar. Here, we use a recently introduced method for obtaining quantitative measures for structural similarity to compare crystalline and amorphous materials. We compare seven common crystalline polymorphs of TiO₂, all assembled out of TiO₆ or TiO₇ polyhedral building blocks, to liquid and amorphous TiO₂ in a quantitative two-dimensional similarity plot. We find high structural similarity between a model of amorphous TiO₂, obtained by ab initio molecular-dynamics, and the B-TiO₂ crystalline polymorph. The general approach presented here sheds new light on a long-standing controversy in the structural theory of amorphous solids.