Suppr超能文献

基于力常数分析的材料维度识别

Identification of Material Dimensionality Based on Force Constant Analysis.

作者信息

Bagheri Mohammad, Berger Ethan, Komsa Hannu-Pekka

机构信息

Microelectronics Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu FIN-90014, Finland.

出版信息

J Phys Chem Lett. 2023 Sep 7;14(35):7840-7847. doi: 10.1021/acs.jpclett.3c01635. Epub 2023 Aug 25.

Abstract

Identification of low-dimensional structural units from the bulk atomic structure is a widely used approach for discovering new low-dimensional materials with new properties and applications. Such analysis is usually based solely on bond-length heuristics, whereas an analysis based on bond strengths would be physically more justified. Here, we study dimensionality classification based on the interatomic force constants of a structure with different approaches for selecting the bonded atoms. The implemented approaches are applied to the existing database of first-principles calculated force constants with a large variety of materials, and the results are analyzed by comparing them to those of several bond-length-based classification methods. Depending on the approach, they can either reproduce results from bond-length-based methods or provide complementary information. As an example of the latter, we managed to identify new non-van der Waals two-dimensional material candidates.

摘要

从体相原子结构中识别低维结构单元是发现具有新特性和应用的新型低维材料的一种广泛使用的方法。这种分析通常仅基于键长启发式方法,而基于键强度的分析在物理上更具合理性。在这里,我们使用不同的选择键合原子的方法,基于结构的原子间力常数研究维度分类。所实施的方法应用于现有的包含各种材料的第一性原理计算力常数数据库,并通过将结果与几种基于键长的分类方法的结果进行比较来进行分析。根据方法的不同,它们要么重现基于键长方法的结果,要么提供补充信息。作为后者的一个例子,我们成功地识别出了新的非范德华二维材料候选物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecc9/10494234/6f62e2fe8fb0/jz3c01635_0005.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验