可物理解释的描述符驱动了用于储存的金属化物的材料设计
Seong-Hoon Jang1, Di Zhang1, Hung Ba Tran1
1Advanced Institute for Materials Research (WPI-AIMR), Tohoku University Sendai 980-8577 Japan jang.seonghoon.b4@tohoku.ac.jp shin-ichi.orimo.a6@tohoku.ac.jp li.hao.b8@tohoku.ac.jp.
可物理解释的模型预测金属化物对储存的性能. 基于的系统有望实现美国能源部的目标,指导未来的材料设计.
科学领域:
- 材料科学 材料科学 材料科学
- 计算化学的计算化学
- 储能 储能 储能 储能 储能 储能
背景情况:
- 设计用于储存的金属化物是具有挑战性的,因为它具有庞大的组成空间和复杂的结构-属性关系.
- 准确预测重量计密度 (w) 和平衡压力 (Peq,RT) 对于材料发现至关重要.
研究的目的:
- 开发可物理解释的模型,用于预测主要的金属化物性能指标 (w 和 P eq,RT).
- 为设计新储存材料制定化学直观的指导方针.
主要方法:
- 利用来自数字气平台 (DigHyd) 的5089种金属化物组成的精选数据集.
- 使用标量变换和非线性链接函数构建了超过160万个候选模型.
- 开发了基于2-3个化学上有意义的描述符 (例如,原子质量,电子阴性) 的封闭形式模型.
主要成果:
- 实现了与最先进的机器学习方法可比的预测准确度,具有完全的物理透明度.
- 揭示了重力度密度和金属化物中的平衡压力之间的基本权衡.
- 确定 (Be) 基系统是同时满足两个性能指标的有希望的候选者.
结论:
- 开发的模型为复杂化学空间中的材料设计提供了化学直观的指导方针.
- 基于的系统为接近美国能源部的储存目标提供了新的前景.
- 该方法建立了一个可扩展的数据驱动材料发现框架,适用于其他能源领域.
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