Tackling The Challenge Of A Huge Materials Science Search Space With Quantum-Inspired Annealing

ADVANCED INTELLIGENT SYSTEMS(2021)

引用 44|浏览6
暂无评分
摘要
Efficient screening of chemicals is essential for exploring new materials. However, the search space is astronomically large, making calculations with conventional computers infeasible. For example, an N-component system of organic molecules generates >10(60N) candidates. Here, a quantum-inspired annealing machine is used to tackle the challenge of the large search space. The prototype system extracts candidate chemicals and their composites with desirable parameters, such as melting temperature and ionic conductivity. The system can be at least 10(4)-10(8) times faster than conventional approaches. Such dramatic acceleration is critical for exploring the enormous search space in virtual screening of materials.
更多
查看译文
关键词
lithium-ion batteries, machine learning, materials informatics, organic functional materials, quantum-inspired annealing
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要