Profiel
Xiaofang Yang has held the title of Chief Technology Officer at Princeton Nuenergy, Inc. since 2019.
Dr. Yang is also the founder of Princeton Nuenergy, Inc. which was founded in 2019.
Actieve functies van Xiaofang Yang
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Princeton Nuenergy, Inc.
 Princeton Nuenergy, Inc. Environmental ServicesIndustrial Services Princeton Nuenergy, Inc. is an innovative clean-tech company based in Princeton, NJ, founded in 2019 by Chao Yan, Xiaofang Yang, Bruce E. Koel, and Yiguang Ju. The American company has launched the first end-to-end production-scale lithium-ion battery direct recycling line in 2022, using their patented low-temperature plasma-assisted separation process (LPAS™) to produce high-quality cathode and anode materials suitable for direct reintroduction into cell manufacturing. The company's LPAS® technology delivers a cost-efficient, environmentally friendly lithium-ion battery recycling solution with exceptional ESG performance at half the cost and with a much lower environmental footprint compared to conventional methods. The company also performs diagnostics of second-life batteries using machine learning and high-sensitivity optical fiber sensors. | Oprichter | 01-01-2019 |
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Princeton Nuenergy, Inc.
Princeton Nuenergy, Inc. Environmental ServicesIndustrial Services Princeton Nuenergy, Inc. is an innovative clean-tech company based in Princeton, NJ, founded in 2019 by Chao Yan, Xiaofang Yang, Bruce E. Koel, and Yiguang Ju. The American company has launched the first end-to-end production-scale lithium-ion battery direct recycling line in 2022, using their patented low-temperature plasma-assisted separation process (LPAS™) to produce high-quality cathode and anode materials suitable for direct reintroduction into cell manufacturing. The company's LPAS® technology delivers a cost-efficient, environmentally friendly lithium-ion battery recycling solution with exceptional ESG performance at half the cost and with a much lower environmental footprint compared to conventional methods. The company also performs diagnostics of second-life batteries using machine learning and high-sensitivity optical fiber sensors. | Industrial Services |
