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.