Computational functionality-driven design of semiconductors for optoelectronic applications

Abstract

The rapid development of the semiconductor industry has motivated researchers passion for accelerating the discovery of advanced optoelectronic materials. Computational functionality-driven design is an emerging branch of material science that has become effective at making material predictions. By combining advanced solid-state knowledge and high-throughput first-principles computational approaches with intelligent algorithms plus database development, experts can now efficiently explore many novel materials by taking advantage of the power of supercomputer architectures. Here, we discuss a set of typical design strategies that can be used to accelerate inorganic optoelectronic materials discovery from computer simulations: In silico computational screening; knowledge-based inverse design; and algorithm-based searching. A few representative examples in optoelectronic materials design are discussed to illustrate these computational functionality-driven modalities. Challenges and prospects for the computational functionality-driven design of materials are further highlighted at the end of the review. (Figure presented.).