重新思考从计算材料科学到SnSe热电学
Shulin Bai1, Xiao Zhang2, Li-Dong Zhao1,3,4
1School of Materials Science and Engineering, Beihang University, Beijing 100191, China.
研究人员开发了高性能热电锡化物 (SnSe) 晶体,用于高效的热电转换. 这一进步解决了可持续的无材料的能源需求,为下一代热电设备铺平了道路.
科学领域:
- 材料科学 材料科学 材料科学
- 固态物理 固态物理
- 计算材料科学科学 计算材料科学
背景情况:
- 越来越多的能源危机和环境问题推动了对可持续能源解决方案的需求.
- 热电技术提供直接的热电转换,零排放和长寿命.
- 传统的热电器由于狭窄的带隙而存在性能限制,限制了它们的工作温度范围.
研究的目的:
- 探索和开发高性能热电锡化 (SnSe) 晶体.
- 研究提高p型和n型SnSe的策略,以实现高效的能源转换.
- 为了利用计算材料科学来设计先进的热电材料.
主要方法:
- 利用电子结构计算和多频段模拟来进行p型SnSe优化.
- 应用缺陷化学和点缺陷计算来调整p型SnSe属性.
- 分析了n型SnSe的电荷密度和计算的变形潜力,重点关注电荷和声子传输脱.
主要成果:
- 在p型Sn$_{0.91}$Pb$_{0.09}$Se.中实现了~75μW cm−1 K−2的超高功率系数 (PF) 和~1.9的ZTave.
- 通过控制内在缺陷,进一步增强了p型SnCu$_{0.001}$Se到PF > 100μW cm−2和ZT ~1.5.
- 开发了Pb合金和Cl合的SnSe (SnSe-Cl-PbSe),在一个广泛的温度范围 (300773 K) 中使用ZTave~1.7.
结论:
- 层状SnSe晶体是有希望的无热电材料,因为它们的宽带间隙和超低导热率.
- 计算方法,包括高通量计算 (HTC) 和机器学习 (ML),可以加速热电材料的发现.
- 开发的战略为为可持续能源应用设计下一代热电材料和设备提供了一条途径.
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