JOURNAL ARTICLE
Electronic, Transport, and Optical Properties of Potential Transparent Conductive Material Rb2Pb2O3.
Published In: Physica Status Solidi - Rapid Research Letters, 2024, v. 18, n. 12. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Xia, Jing‐Yi; Zeng, Wei; Liu, Zheng‐Tang; Liu, Qi‐Jun; Gao, Juan; Jiao, Zhen 3 of 3
Abstract
To better verify the potential of Rb2Pb2O3 as p‐type transparent conductive oxides (TCOs), the structural, electronic, mechanical, transport, and optical properties of Rb2Pb2O3 are calculated in detail under the framework of density functional theory. Significantly, Rb2Pb2O3 is a p‐type semiconductor with an indirect 2.82 eV bandgap. Herein, the Pb‐6p and O‐2p orbits hybridized to form ionic PbO bonds, which determines the degree of localization of electrons in valence band maximum. Interestingly, the RbO bond is extremely weak, and the Rb atom is rarely involved in bonding interactions. This contributes to isotropy, ductility, and good mobility of Rb2Pb2O3, making it soft and suitable for application in flexible electronics. More importantly, as a transparent conductive material, Rb2Pb2O3 not only shows good transparency in the visible region but also has good electrical conductivity. Therefore, Rb2Pb2O3 as an intrinsic p‐TCO with good performance is preliminarily identified. The theoretical finding provides a new candidate for p‐TCOs and paves the way for further performance improvement of Rb2Pb2O3. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Physica Status Solidi - Rapid Research Letters. 2024/12, Vol. 18, Issue 12, p1
- Document Type:Article
- Subject Area:Chemistry
- Publication Date:2024
- ISSN:1862-6254
- DOI:10.1002/pssr.202400135
- Accession Number:181275940
- Copyright Statement:Copyright of Physica Status Solidi - Rapid Research Letters is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.