迷你评论:为下一代材料科学提供协同驱动的量子动力学,人工智能和量子计算
Opeyemi S Akanbi1, Jack P Shannon1, Jerome Delhommelle2
1Department of Physics & Applied Physics, University of Massachusetts Lowell, Lowell, Massachusetts 01854, United States.
The journal of physical chemistry letters
|November 5, 2025
概括
结合量子动力学,人工智能 (AI) 和量子计算的协同方法加快了下一代量子材料的发现. 这些方法可以快速探索和设计具有高级应用性能增强的材料.
科学领域:
- 材料科学 材料科学 材料科学
- 量子物理学 量子物理学 是一种量子物理学.
- 计算化学计算化学
背景情况:
- 下一代材料设计正在通过自动化平台迅速发展.
- 人工智能 (AI) 和机器人是现代合成规划和执行的关键组成部分.
研究的目的:
- 分析结合量子力学,人工智能/机器学习和量子计算的协同方法.
- 加速发现和设计具有增强性质和新功能的量子材料.
主要方法:
- 利用驱动量子动力学来理解物质对时间依赖场的反应.
- 使用人工智能/机器学习来快速探索广的材料设计空间.
- 利用量子计算来识别新的量子相,并优化材料特性.
主要成果:
- 协同效应的方法提供了复杂的材料行为和属性的访问.
- 在量子电池,太阳能电池和量子信息处理方面展示了成功的应用.
- 识别具有卓越性能的新型量子相和材料.
结论:
- 量子动力学,人工智能和量子计算的整合对于未来的材料发现至关重要.
- 对量子计算和量子机器学习的AI的持续研究将进一步推进下一代材料.
- 这些协同作用的方法有望打开材料科学和技术的新前沿.
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