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机器学习助力二维殷钢和反殷钢单分子层的发现。

Machine learning enables the discovery of 2D Invar and anti-Invar monolayers.

作者信息

Tian Shun, Zhou Ke, Yin Wanjian, Liu Yilun

机构信息

College of Energy, SIEMIS, Soochow University, Suzhou, China.

Laboratory for Multiscale Mechanics and Medical Science, SV LAB, School of Aerospace, Xi'an Jiaotong University, Xi'an, China.

出版信息

Nat Commun. 2024 Aug 14;15(1):6977. doi: 10.1038/s41467-024-51379-6.

DOI:10.1038/s41467-024-51379-6
PMID:39143099
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11324886/
Abstract

Materials demonstrating positive thermal expansion (PTE) or negative thermal expansion (NTE) are quite common, whereas those exhibiting zero thermal expansion (ZTE) are notably scarce. In this work, we identify the mechanical descriptors, namely in-plane tensile stiffness and out-of-plane bending stiffness, that can effectively classify PTE and NTE 2D crystals. By utilizing high throughput calculations and the state-of-the-art symbolic regression method, these descriptors aid in the discovery of ZTE or 2D Invar monolayers with the linear thermal expansion coefficient (LTEC) within  ±2 × 10 K in the middle range of temperatures. Additionally, the descriptors assist the discovery of large PTE and NTE 2D monolayers with the LTEC larger than  ±15 × 10 K, which are so-called 2D anti-Invar monolayers. Advancing our understanding of materials with exceptionally low or high thermal expansion is of substantial scientific and technological interest, particularly in the development of next-generation electronics at the nanometer or even Ångstrom scale.

摘要

表现出正热膨胀(PTE)或负热膨胀(NTE)的材料相当常见,而表现出零热膨胀(ZTE)的材料则极为稀少。在这项工作中,我们确定了机械描述符,即面内拉伸刚度和面外弯曲刚度,它们可以有效地对PTE和NTE二维晶体进行分类。通过利用高通量计算和最先进的符号回归方法,这些描述符有助于发现热膨胀系数(LTEC)在温度中间范围内±2×10 K的ZTE或二维殷钢单层。此外,这些描述符有助于发现LTEC大于±15×10 K的大PTE和NTE二维单层,即所谓的二维反殷钢单层。深入了解具有极低或极高热膨胀的材料具有重大的科学和技术意义,特别是在纳米甚至埃尺度的下一代电子产品开发中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3022/11324886/b39462349c47/41467_2024_51379_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3022/11324886/2eb767d9be6c/41467_2024_51379_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3022/11324886/be4215733cde/41467_2024_51379_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3022/11324886/e81ce24d1f79/41467_2024_51379_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3022/11324886/b39462349c47/41467_2024_51379_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3022/11324886/2eb767d9be6c/41467_2024_51379_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3022/11324886/be4215733cde/41467_2024_51379_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3022/11324886/e81ce24d1f79/41467_2024_51379_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3022/11324886/b39462349c47/41467_2024_51379_Fig5_HTML.jpg

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