Computationally assisted multistage design and prediction driving the discovery of deep-ultraviolet nonlinear optical materials

Abstract

With the rapid development of computer technology, material design and crystal-structural prediction based on density functional theory have become one “top-down” strategy to accelerate the process of advanced materials discovery. In this review, we outline several examples for material design and prediction which drive the discovery of deep-ultraviolet nonlinear optical materials. The computer-aided material design and prediction platform including the high-throughput screening systems is discussed. The property-driven materials multistage design process from functional groups, module to functional layer analysis and structural prediction is described to explore new deep-ultraviolet nonlinear optical materials. Finally, there are still grand challenges in computer-aided design and prediction, and it is hoped that the computer-aided strategy will provide a more powerful ability on the most promising nonlinear optical candidates and related fields.