Zhenghan Peng
Ph.D. Student in Materials Science and Engineering, admitted Autumn 2024
Education & Certifications
-
B.S., Sichuan University, Materials Physics (2022)
All Publications
-
Modulate the Interfacial Oxygen Vacancy for High Performance MoS2 Photosensing−Memory Device
Advanced Optical Materials
2022
View details for DOI 10.1002/adom.202202378
-
Layer-by-Layer Growth of AA-Stacking MoS2 for Tunable Broadband Phototransistors
ACS APPLIED MATERIALS & INTERFACES
2021; 13 (49): 59154-59163
Abstract
The stacking configuration has been considered as an important additional degree of freedom to tune the physical property of layered materials, such as superconductivity and interlayer excitons. However, the facile growth of highly uniform stacking configuration is still a challenge. Herein, the AA-stacking MoS2 domains with a ratio up to 99.5% has been grown by using the modified chemical vapor deposition through introducing NaCl molecules in the confined space. By tuning the growth time, MoS2 domains would transit from an AA-stacking bilayer to an AAAAA-stacking five-layer. The epitaxial growth mechanism has been insightfully studied, revealing that the critical nucleation size of the AA-stacking bilayer is 5.0 ± 3.0 μm. Through investigation of the photoluminescence, the photoemission, especially the indirect photoexcitation, is dependent on both the stacking fashion and layer number. Furthermore, by studying the gate-tuned MoS2 phototransistors, we found a significant dependence on the stacking configuration of MoS2 of the photoexcitation and a different gate tunable photoresponse. The AAA-stacking trilayer MoS2 phototransistor delivers a photoresponse of 978.14 A W-1 at 550 nm. By correction of the external quantum efficiency with external field and illumination power density, it has been found that the photoresponse tunability is dependent on the layer number due to the strong photogating effect. This strategy provides a general avenue for the epitaxial growth of van der Waals film which will further facilitate the applications in a tunable photodetector.
View details for DOI 10.1021/acsami.1c19906
View details for Web of Science ID 000752977200088
View details for PubMedID 34856097
-
Machine learning atomic-scale stiffness in metallic glass
EXTREME MECHANICS LETTERS
2021; 48
View details for DOI 10.1016/j.eml.2021.101446
View details for Web of Science ID 000686901700002