Zhuowen Feng Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
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Biography and Research Information
OverviewAI-generated summary
Zhuowen Feng is pursuing a Ph.D. in electrical engineering at the University of Arkansas, Fayetteville. His research focuses on wide bandgap semiconductor devices and power electronics, particularly silicon carbide (SiC) power MOSFETs and resonant converters designed for solar energy applications. Feng's work also extends to the reliability of power modules in demanding conditions and the optimization of lithography patterning on SiC wafers using electron beam technology. He has contributed to several publications exploring SiC CMOS technology for harsh environments and simulation methods for assessing temperature and radiation effects on SiC resonant-converter reliability. Feng collaborates with researchers at the University of Arkansas, including Abu Shahir Md Khalid Hasan, Zhong Chen, and Pengyu Lai, with whom he has co-authored multiple publications.
Metrics
- h-index: 4
- Publications: 11
- Citations: 61
Selected Publications
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A New Simulation Method to Assess Temperature and Radiation Effects on SiC Resonant-Converter Reliability (2026)
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A Simplified Gate Driver Architecture for Achieving Fast Switching in Medium-Voltage SiC Power Modules (2025)
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Use of E-Beam Lithography to Optimize Lithography Patterning on SiC Wafers (2025)
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A 200 <sup>∘</sup>C SiC Phase-Leg Power Module With Integrated Gate Drivers: Development, Performance Assessment, and Path Forward (2025)
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A review of silicon carbide CMOS technology for harsh environments (2024)
Collaboration Network
Top Collaborators
- A Novel Public Sentiment Analysis Method Based on an Isomerism Learning Model via Multiphase Processing
- Distributed opinion competition scheme with gradient-based neural network in social networks
- PTE: Prompt tuning with ensemble verbalizers
- A review of silicon carbide CMOS technology for harsh environments
- A 200 <sup>∘</sup>C SiC Phase-Leg Power Module With Integrated Gate Drivers: Development, Performance Assessment, and Path Forward
- A New Simulation Method to Assess Temperature and Radiation Effects on SiC Resonant-Converter Reliability
- A review of silicon carbide CMOS technology for harsh environments
- A New Simulation Method to Assess Temperature and Radiation Effects on SiC Resonant-Converter Reliability
- A New Simulation Method to Assess Temperature and Radiation Effects on SiC Resonant-Converter Reliability
- A review of silicon carbide CMOS technology for harsh environments
- Use of E-Beam Lithography to Optimize Lithography Patterning on SiC Wafers
- A 200 <sup>∘</sup>C SiC Phase-Leg Power Module With Integrated Gate Drivers: Development, Performance Assessment, and Path Forward
- A review of silicon carbide CMOS technology for harsh environments
- A 200 <sup>∘</sup>C SiC Phase-Leg Power Module With Integrated Gate Drivers: Development, Performance Assessment, and Path Forward
- A 200 <sup>∘</sup>C SiC Phase-Leg Power Module With Integrated Gate Drivers: Development, Performance Assessment, and Path Forward
- A Simplified Gate Driver Architecture for Achieving Fast Switching in Medium-Voltage SiC Power Modules
- A New Simulation Method to Assess Temperature and Radiation Effects on SiC Resonant-Converter Reliability
- A New Simulation Method to Assess Temperature and Radiation Effects on SiC Resonant-Converter Reliability
- A Simplified Gate Driver Architecture for Achieving Fast Switching in Medium-Voltage SiC Power Modules
- A New Simulation Method to Assess Temperature and Radiation Effects on SiC Resonant-Converter Reliability
- A Novel Public Sentiment Analysis Method Based on an Isomerism Learning Model via Multiphase Processing
- A Novel Public Sentiment Analysis Method Based on an Isomerism Learning Model via Multiphase Processing
- A Novel Public Sentiment Analysis Method Based on an Isomerism Learning Model via Multiphase Processing
- A Novel Public Sentiment Analysis Method Based on an Isomerism Learning Model via Multiphase Processing
- A Novel Public Sentiment Analysis Method Based on an Isomerism Learning Model via Multiphase Processing
- A Novel Public Sentiment Analysis Method Based on an Isomerism Learning Model via Multiphase Processing
- A review of silicon carbide CMOS technology for harsh environments
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