The Impact of Microwave Annealing on MoS2 Devices Assisted by Neural Network-Based Big Data Analysis

Author:

Su Xing12ORCID,Cui Siwei12ORCID,Zhang Yifei12,Yang Hui34,Wu Dongping12

Affiliation:

1. State Key Laboratory of ASIC and System, Fudan University, Shanghai 200433, China

2. School of Microelectronics, Fudan University, Shanghai 200433, China

3. School of Artificial Intelligence Science and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China

4. Institute of Photonic Chips, University of Shanghai for Science and Technology, Shanghai 200093, China

Abstract

Microwave annealing, an emerging annealing method known for its efficiency and low thermal budget, has established a foundational research base in the annealing of molybdenum disulfide (MoS2) devices. Typically, to obtain high-quality MoS2 devices, mechanical exfoliation is commonly employed. This method’s challenge lies in achieving uniform film thickness, which limits the use of extensive data for studying the effects of microwave annealing on the MoS2 devices. In this experiment, we utilized a neural network approach based on the HSV (hue, saturation, value) color space to assist in distinguishing film thickness for the fabrication of numerous MoS2 devices with enhanced uniformity and consistency. This method allowed us to precisely assess the impact of microwave annealing on device performance. We discovered a relationship between the device’s electrical performance and the annealing power. By analyzing the statistical data of these electrical parameters, we identified the optimal annealing power for MoS2 devices as 700 W, providing insights and guidance for the microwave annealing process of two-dimensional materials.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

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