Synergizing advanced materials and artificial intelligence for next-generation carbon capture, utilization, and storage (CCUS): a review
次世代炭素回収・有効利用・貯蔵(CCUS)のための先端材料と人工知能の相乗効果:レビュー (AI 翻訳)
Somia Mazhar, Muhammad Waseem Mumtaz, M. El Oirdi, Hamid Mukhtar, Muhammad Asam Raza, Mohd Farhan, Mohammad Aatif, Ghazala Muteeb
🤖 gxceed AI 要約
日本語
本レビューは、先進材料とAI/MLを活用したCCUSの最新進展を総括する。バイオ炭やナノ材料によるCO2回収、MOFやグラフェン触媒による利用、鉱物炭酸化やハイドレート形成による貯蔵技術を紹介。AI/MLは材料スクリーニングやシステム最適化に不可欠である。コストやスケーラビリティの課題は残るが、ネットゼロへの変革技術として期待される。
English
This review covers advancements in CCUS through advanced materials and AI/ML. It discusses biochar and nanomaterial adsorbents for CO2 capture, MOFs and graphene catalysts for utilization, and mineral carbonation for storage. AI/ML enables high-throughput screening, predictive modeling, and system optimization. Challenges of cost and scalability remain, but CCUS is seen as transformative for net-zero.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本ではCCUSはGX政策の重要柱であり、2030年までの年間100万トン貯留目標など具体策が進む。本レビューは材料・AIの最前線を網羅しており、日本のCCUS研究・実装に直接活用できる知見を提供する。
In the global GX context
Globally, CCUS is recognized by IPCC and IEA as essential for climate goals. This review provides a comprehensive update on materials and digital innovations, relevant for researchers and practitioners advancing decarbonization.
👥 読者別の含意
🔬研究者:Useful overview of state-of-the-art CCUS materials and AI/ML applications, including emerging trends in digital twins and IoT.
🏢実務担当者:Highlights promising materials and AI tools for CCUS; may guide technology selection for pilot projects.
🏛政策担当者:Provides context on current capabilities and challenges; useful for understanding CCUS potential.
📄 Abstract(原文)
The increasing rate of global carbon dioxide (CO2) emissions, mainly resulted from the industrial and energy sectors is a serious global challenge for climate stability. Carbon Capture, Utilization, and Storage (CCUS) technologies are being considered as important route to achieve the decarbonization objectives established in the Paris Agreement through reduction of CO2 levels in the atmosphere while allowing for its conversion to useful products. This review presents advancements in materials and technologies that are used to enhance the efficiency of CCUS process. Adsorbents based on biochar and nanomaterials, including carbon nanotubes, graphene derivatives, cellulose nanofibers, and nanoporous carbon, have significant CO2 capture potential, due to their tunable porosity and large surface area. In utilization metal–organic frameworks (MOFs), graphene-based catalysts, and single-atom catalysts (SACs) have promising selectivity in the electrochemical reduction of CO2 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.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1039/d5ra07338cfirst seen 2026-05-05 23:29:58
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。