Work

Artificial Neural Network based Model for Power GaN HEMTs down to 4.2K

Year: 2024

Type: conference-paper

Source: IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA)

DOI: 10.1109/icta64028.2024.10860543

Authors: Zikun Xiang, Haochen Zhang, Bolun Zeng, Lei Yang, Liling Qiu, Xi Jin, Guoping Guo, Chao Luo, Haiding Sun

Institutions: University of Science and Technology of China, CAS Key Laboratory of Quantum Information, USTC

Language: English

Topic: GaN-based semiconductor devices and materials

Subfield: Condensed Matter Physics

Field: Physics and Astronomy

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: closed

Funder: National Science Foundation

OpenAlex ID: W4407214427

FWCI:

Cites: 8

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Related to: 10