SOURCE-LINKED INTELLIGENCE

Engineering Metal-Organic Framework-Polymer Binder Interfaces for Carbon Capture

CORDIS · observation · Publication date unknown

g MOF-binder composites with enhanced mechanical properties and controlled porosity. By utilizing parallel molecular simulations, we will predict the interface properties in a high-throughput manner. Machine learning techniques, drawing from both simulated and literature-mined data, will enable the development of a robust screening method. Additionally, our work will be integrated with the state-of-the-art Process-Informed design of tailor-made Sorbent Materials (PrISMa) platform, which connects material design, process optimization, techno-economics, and life-cycle assessment. This integration will allow for the evaluation and comparison of MOF formulations in terms of their greenhouse gas emissions throughout the lifecycle of the carbon capture plant, addressing one of the final steps in the deployment of carbon capture technologies. To achieve these goals, the Researcher will receive training in high-throughput atomistic simulation workflows, materials informatics, and machine learning for material discovery, along with a holistic engineering approach through PrISMa. Moreover, th

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recordType

award

status

SIGNED

region

EU

value

209914.56

unit

EUR