Bibliographic Details
| Title: |
Dielectric-engineered Ag nanowire/dielectric multilayers composite transparent conductive thin films with exceeding 99% transmittance and enhanced stability. |
| Authors: |
Yu, Shihui1 (AUTHOR) shihui.yu@tju.edu.cn, An, Wenxing2 (AUTHOR), Dong, Helei1,3 (AUTHOR) donghelei@nuc.edu.cn |
| Source: |
Ceramics International. May2026:Part A, Vol. 52 Issue 11, p15639-15647. 9p. |
| Subjects: |
Nanowires, Transparency (Optics), Nanocomposite materials, Electric conductivity, Durability, Transparent electronics, Optoelectronic devices, Dielectrics |
| Abstract: |
Flexible transparent conductive thin films (TCFs) are critical components in optoelectronic devices but are often limited by the trade-off between optical transparency, conductivity and stability. Herein, we report a dielectric-engineered Ag nanowire (Ag NW)/Nb 2 O 5 /SiO 2 /Nb 2 O 5 /SiO 2 (Ag NW/SNSN) composite TCF with ultra-high light transmittance. Guided by optical interference modeling, the four-layer SNSN dielectric stack is optimized to suppress reflection and absorption losses, causing a relative transmittance above 99% and a high figure of merit (∼1082), while the sheet resistance is 43.3 Ω/sq. Furthermore, the conductivity of composite TCFs does not show great change after tape test and ultrasonication, suggesting a strong adhesion of Ag NWs to the substrate. Moreover, the Ag NW/SNSN composite TCFs show a good stability to resist long-term storage, oxidation, sulfidation, and chloride corrosion. These results demonstrate that coupling dielectric interference design with nanoscale encapsulation enables TCFs operating near the theoretical transmittance limit of the substrate, offering a versatile strategy for flexible, durable, and high-performance optoelectronic devices. [ABSTRACT FROM AUTHOR] |
|
Copyright of Ceramics International is the property of Elsevier B.V. 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.) |
| Database: |
Engineering Source |