具有各种插层原子和层主的层状插层化合物带状结构数据库。

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Naoto Kawaguchi, Kiyou Shibata, Teruyasu Mizoguchi
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引用次数: 0

摘要

在这里,我们提供了一个包含 9,004 种层状插层化合物电子能带结构的数据库,在这种化合物中,原子与不同的插层原子插层到宿主层状化合物中,同时还提供了与层状宿主化合物相关的 468 种结构。此外,我们还提供了从电子态(如带隙)推导出的属性以及与稳定性相关的属性(如形成能)。由于空间群和 k 路径的变化,直接比较插层前后的带状结构通常具有挑战性。不过,在本研究中,我们开发了与宿主材料一致的新 k 路径,从而可以直接比较插层前后的能带结构。这样就可以直接定量讨论插层引起的能带结构变化,并为插层驱动的能带工程提供了宝贵的数据库。层状插层化合物被广泛应用于超导和能源应用等多个领域,因此了解其电子结构十分必要。利用我们数据库的特点,有望开发出功能更强的层状化合物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Band structure database of layered intercalation compounds with various intercalant atoms and layered hosts.

Here we provide a database comprising electronic band structures of 9,004 layered intercalation compounds, where atoms are intercalated into a host layered compound with different intercalant atoms, along with 468 structures related to the layered host compounds. Additionally, we provide properties derived from the electronic states such as band gap as well as stability-related properties like formation energies. Direct comparison of the band structures before and after intercalation is generally challenging due to changes in their space group and k-path. However, in this study, we developed new k-paths consistent with the host materials, allowing for the direct comparison of band structures before and after intercalation. This enables direct and quantitative discussion of the band structure changes induced by the intercalations and provides a valuable database for intercalant-driven band engineering. Layered intercalation compounds are widely used in many fields, including superconductivity and energy applications, and understanding of electronic structures is necessary. The feature of our database holds promises for the development of layered compounds with enhanced functionalities through database utilization.

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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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