Real-time visualization of CO2 electrolysis
Real-time visualization of CO2 electrolysis
批准号:
577135-2022
负责人:
BERLINGUETTE, CURTISP
金额:
$26.86万
依托单位国家:
加拿大
项目类别:
Alliance Grants
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31
中文摘要
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英文摘要
This project will advance electrochemical reactors (electrolysers) that have potential to mitigate greenhouse gas emissions by converting CO2 capture solutions into products used widely by society. The project team includes: Prof. Curtis Berlinguette at UBC, a world leader in CO2 capture and conversion research; Prof. Yoshua Bengio at UdeM, a pioneer in machine learning algorithm development; and Carbon Engineering, a global leading CO2 capture company headquartered in Squamish, BC. Electrochemical CO2 conversion is a promising strategy to enable renewable energy to be stored in carbon-based chemicals (e.g., CO) using atmospheric or emitted CO2. Electrolysers are largely closed systems with stainless steel housing. Consequently, input and output streams can be measured, but the chemical and physical phenomena occurring inside the reactor cannot be directly observed and are poorly understood. The Berlinguette Group is developing an innovative imaging technique that underpins this project and allows scientists to visualize the processes inside an operating electrolyser for the first time. This visualization tool can produce enormous data sets that are too large to be efficiently processed manually; through this project the Bengio Group will leverage machine learning (ML) to model the captured data in order to better analyze it and provide guidance for the optimization of the underlying process. Real-time visualization of CO2 electrolysis during this project will enable development of fundamental fluid flow models that provide valuable insights for the project team as well as the broader scientific and industrial communities. We will leverage project learnings to identify reactor materials, reactor configurations, and operating conditions that enhance conversion rates and energy efficiency. Such advancements are needed for future reactor deployment at commercial scale. Carbon Engineering will bring an industrial perspective to the project while gaining insight into how ML may be useful to their current workflows. The project will also train young scientists and engineers in Canada for careers in climate science and inform ambitious GHG mitigation opportunities.
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批准号:555469-2020
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项目类别:Alliance Grants
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资助金额:$21.86万
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财政年份:2022
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负责人:BERLINGUETTE, CURTISP
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依托单位:
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