Physical Vapor Deposition of High-Mobility P-Type Tellurium and Its Applications for Gate-Tunable van der Waals PN Photodiodes
Year: 2024
Type: article
Abstract: High Resolution Image Download MS PowerPoint Slide Recently, tellurium has attracted resurgent interest due to its outstanding p-type characteristics and ambient environmental stability. Here, we present a substrate engineering-based physical vapor deposition method to synthesize high-quality Te nanoflakes and achieved a field-effect hole mobility of 1450 cm 2 /(V s), which is, to the best of our knowledge, the highest among existing synthesized two-dimensional p-type semiconductors. The high mobility of Te enables the fabrication of Te/MoS 2 PN diodes with highly gate-tunable characteristics. The Te/MoS 2 heterostructure is demonstrated to be used as visible-light photodetectors with a current responsivity up to 630 A/W, which is about 1 order of magnitude higher than one achieved using p-type Si-MoS 2 PN photodiodes. The photoresponse of Te/MoS 2 heterojunctions also exhibits strong gate tunability due to their ultrathin thickness and unique band alignment. The successful synthesis of high-mobility Te and its integration into Te/MoS 2 photodiodes show promise for the development of highly tunable and multifunctional photodetectors.
Authors: Tianyi Huang, Sen Lin, Jingyi Zou, Zexiao Wang, Yibai Zhong, Jingwei Li, Ruixuan Wang, Zhixing Wang, Kevin St. Luce, Rex Kim, Jianzhou Cui, Han Wang, Qing Li, Min Xu, Sheng Shen, Xu Zhang
Institutions: Carnegie Mellon University, University of Southern California
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,500
Funders: National Science Foundation, Pennsylvania Department of Community and Economic Development, Carnegie Mellon University, National Institutes of Health, National Institute of General Medical Sciences, Division of Electrical, Communications and Cyber Systems, Division of Biological Infrastructure
Awards: G2309930383, G2865218810, Novel machine learning approaches for improving structural discrimination in cryo-electron tomography, G4857701761, CAREER: Kirigami-Actuated Adaptive Metasurfaces with Dynamic Tunability enabled by 2D Materials, G5793283779, High Performance Computing for Multiscale Modeling of Biological Systems, G8581095836
OpenAlex ID: W4405624462