Hierarchically Structured Allotropes of Phosphorus from Data-Driven Exploration.

ABSTRACT: The discovery of materials is increasingly guided by quantum-mechanical crystal-structure prediction, but the structural complexity in bulk and nanoscale materials remains a bottleneck. Here we demonstrate how data-driven approaches can vastly accelerate the search for complex structures, combining a machine-learning (ML) model for the potential-energy surface with efficient, fragment-based searching. We use the characteristic building units observed in Hittorf's and fibrous phosphorus to seed stochastic ("random") structure searches over hundreds of thousands of runs. Our study identifies a family of hierarchically structured allotropes based on a P8 cage as principal building unit, including one-dimensional (1D) single and double helix structures, nanowires, and two-dimensional (2D) phos

SUBMITTER: Deringer VL 

PROVIDER: S-EPMC7540597 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature