Shun Tian^1,2, Ke Zhou^1*, Wanjian Yin¹, Yilun Liu^2*

1 College of Energy, SIEMIS, Soochow University, Suzhou 215006, China

2 Laboratory for Multiscale Mechanics and Medical Science, SV LAB, School of Aerospace, Xi’an Jiaotong University, Xi’an 710049, China

* Corresponding authors emails: zhouke@suda.edu.cn, yilunliu@mail.xjtu.edu.cn

DOI10.24435/materialscloud:hc-zb [version v1]

Publication date: Jul 25, 2024

How to cite this record

Shun Tian, Ke Zhou, Wanjian Yin, Yilun Liu, Machine learning enables the discovery of 2D Invar and anti-Invar monolayers, Materials Cloud Archive 2024.111 (2024), https://doi.org/10.24435/materialscloud:hc-zb

Description

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 ±2×10⁻⁶ K⁻¹ in the middle range of temperatures. Additionally, the descriptors assist the discovery of large PTE and NTE 2D monolayers with the LTEC larger than ±15×10⁻⁶ K⁻¹, 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 developing next-generation electronics at the nanometer even Ångstrom scale.

Materials Cloud sections using this data

Files

File name	Size	Description
ZTE_ELTE.tar.xz MD5md5:1315686c0fc052a7e51a2baeeba62688	49.4 MiB	This repository contains 72 two-dimensional crystal structure files and the thermal expansion coefficents calculated using the Gruneisen theory.

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External references

Keywords

machine learning symbolic regression 2D materials thermal expansion zero thermal expansion bending stiffness linear coefficient of thermal expansion