Effect Of Trace Impurities In a CO2 Flow

CO2 流中痕量杂质的影响

• 批准号: 10022761
• 金额: $ 1.88万
• 依托单位: AI EXPLORATION LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10022761
• 关键词: Effect; Trace; Impurities; CO2; Flow

AI Exploration has developed a novel sensor that can measure trace H2O in a multi-component CO2 flow for Carbon Capture and Storage applications.During this project we aim to address the measurement challenge we have with our existing sensor. The presence of different types and levels of other impurities (besides H2O) poses a significant challenge to perform this measurement accurately and repeatedly. The focus of this project is to test AIX's existing prototype system along side other measurement systems in NPL's primary standard multi-gas, multi-pressure humidity lab to assess the performance of AIX's technology in different environmental conditions and compare the performance to other sensing approaches.The true benefit of solving this problem is it will allow AI Exploration to fast track the product towards commercial industrial trials with large operators like BP which will increase its competitiveness in the marketplace.

AI Exploration开发了一种新型传感器，可以测量多组分CO2流中的痕量H2O，用于碳捕集和封存应用。在这个项目中，我们的目标是解决我们现有传感器面临的测量挑战。不同类型和水平的其他杂质（除H2O外）的存在对准确和重复地执行此测量构成了重大挑战。该项目的重点是测试AIX现有的原型系统沿着在NPL的主要标准多气体，多的压力湿度实验室，以评估AIX技术在不同环境条件下的性能，并将其性能与其他传感方法进行比较。解决这个问题的真正好处是，它将使AI Exploration能够快速跟踪产品进入商业工业试验，这将提高其在市场上的竞争力。