<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/EB4F0D57-524C-4412-8EA9-8CE8608DC134" ns1:id="EB4F0D57-524C-4412-8EA9-8CE8608DC134"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/C5100B05-4664-4108-8ADD-231A54EF1924" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/FD167717-2DFB-490A-B8A1-CC201B817E1E" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/E04097D1-7386-4BEC-AB80-85F0EEB80CB2" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/FD167717-2DFB-490A-B8A1-CC201B817E1E" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2022-03-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/34F42743-C66C-41C4-9359-28346905A2B5" ns1:rel="FUND" ns1:start="2022-01-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10022761</ns2:identifier></ns2:identifiers><ns2:title>Effect Of Trace Impurities In a CO2 Flow</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>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.</ns2:abstractText></ns2:project>