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◆ RSC Advances2026-01-01· Process engineering

Synergizing advanced materials and artificial intelligence for next-generation carbon capture, utilization, and storage (CCUS): a review

Somia Mazhar, Muhammad Waseem Mumtaz, Mohamed El Oirdi, Hamid Mukhtar, Muhammad Asam Raza, Mohd Farhan, Mohammad Aatif, Ghazala Muteeb

原始摘要(英文原文)· Original abstract
into fuels and chemicals in a closed carbon economy. For long-term storage, routes for secure and versatile sequestration include mineral carbonation, hydrate formation, and mixed-matrix membranes. Artificial Intelligence (AI) and Machine Learning (ML) enabled technology is increasingly crucial to the effectiveness of CCUS, not only in high-throughput material screening and predictive modeling for catalytic activity and plume migration forecasting, but also in system optimization. New digital tools, including digital twins, IoT-enabled monitoring, and life cycle assessments, increase the reliability, scalability, and sustainability of CCUS deployment. While there are many challenges remaining, especially with respect to cost, stability, and industrial scalability, CCUS can be seen as an emerging transformative technology towards net-zero energy transitions with advances occurring rapidly in synergy with materials science and digital intelligence.
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Synergizing advanced materials and artificial intelligence for next-generation carbon capture, utilization, and storage (CCUS): a review — 科研速览 Science Skim