Computational Material Design & Carbon Capture
Dan Sorescu - Using high performance computing and machine learning enables scientists to solve complex technical and environmental challenges faster and pave the way for advanced, more efficient energy systems development.
Computational Molecular Science – NETL maintains expertise in the modeling of materials at the atomic, molecular, and meso scales, which enables a fundamental understanding of materials behavior and provides insight into development opportunities and performance optimization strategies. This approach is being used to improve the performances of advanced alloys, fuel cell systems, functional materials used as sorbents, catalysts, and in sensor applications. These processes allow NETL to assess the performance of emerging new materials in the context of new energy technologies and to identify ways to improve materials efficiency, performance and cost.
Mixed Matrix Modeling & Data Analytics – NETL focuses on developing efficient carbon capture and storage technologies to mitigate the emission of carbon dioxide. Mixed matrix membranes (MMMs) offer the potential for optimized carbon capture performance. NETL used high performance computing to rapidly screen more than a million MMMs and identify promising options for post-combustion carbon capture. MMMs based on NETL Polymer 3 are projected to decrease the cost of carbon capture from $63 to $48 per metric ton of CO2 removed.
Computational Material Design & Carbon Capture
Dan Sorescu - Using high performance computing and machine learning enables scientists to solve complex technical and environmental challenges faster and pave the way for advanced, more efficient energy systems development.
Computational Molecular Science – NETL maintains expertise in the modeling of materials at the atomic, molecular, and meso scales, which enables a fundamental understanding of materials behavior and provides insight into development opportunities and performance optimization strategies. This approach is being used to improve the performances of advanced alloys, fuel cell systems, functional materials used as sorbents, catalysts, and in sensor applications. These processes allow NETL to assess the performance of emerging new materials in the context of new energy technologies and to identify ways to improve materials efficiency, performance and cost.
Mixed Matrix Modeling & Data Analytics – NETL focuses on developing efficient carbon capture and storage technologies to mitigate the emission of carbon dioxide. Mixed matrix membranes (MMMs) offer the potential for optimized carbon capture performance. NETL used high performance computing to rapidly screen more than a million MMMs and identify promising options for post-combustion carbon capture. MMMs based on NETL Polymer 3 are projected to decrease the cost of carbon capture from $63 to $48 per metric ton of CO2 removed.