AI-Driven Inverse Design of Materials: Past, Present, and Future
Renmin University of China · Shaanxi Normal University
Abstract
Abstract The discovery of advanced materials is a cornerstone of human technological development and progress. The structures of materials and their corresponding properties are essentially the result of a complex interplay of multiple degrees of freedom such as lattice, charge, spin, symmetry, and topology. This poses significant challenges for the inverse design methods of materials. Humans have long explored new materials through numerous experiments and proposed corresponding theoretical systems to predict new material properties and structures. With the improvement of computational power, researchers have gradually developed various electronic-structure calculation methods, such as the density functional…
Citation impact
- FWCI
- 21.50
- Percentile
- 100%
- References
- 307
Authors
8Topics & keywords
- Computer science
- Generative grammar
- Inverse
- Management science
- Artificial intelligence
- Mathematics
- Engineering
- Reduced inequalities