Computational approaches to materials design promise to accelerate the discovery of materials with superior functionalities. This Review presents key computational advances in materials design over the past few decades, highlighting the paradigm shift from conventional screening approaches to inverse generation driven by deep generative models. Current challenges and future perspectives of materials inverse design are also discussed.
- Mouyang Cheng
- Chu-Liang Fu
- Mingda Li
