Small is the New Large: Demonstration of how Microanalyses Elucidate Large‐Scale CO2 Uptake Through Mineralization
小さなものが新たな大きなものへ：微視的分析が鉱化作用による大規模CO2吸収を解明する方法の実証 (AI 翻訳)
Faisal W. K. Khudhur, Ian B. Butler, S. Gilfillan
🤖 gxceed AI 要約
日本語
本論文は、CO2の鉱物化（in situ mineralization）に関する微視的イメージング技術（X線マイクロCT、電子顕微鏡など）の統合的利用方法をレビューする。相関顕微鏡や機械学習の活用、反応性輸送モデルの信頼性向上、セメントや玄武岩を用いた実験観察に基づく鉱物化適性評価の決定木を提案している。
English
This paper reviews advanced imaging techniques (X-ray microCT, electron microscopy) for understanding CO2 mineralization at the microscale. It highlights correlative microscopy and machine learning, improves reactive transport modeling, and proposes a decision tree for assessing formation suitability based on experiments with cement and basalt.
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CCSの実証実験が進む中、本レビューは微視的分析によるCO2鉱物化評価の手法を整理しており、炭酸塩鉱物を利用した国内貯留層の評価に貢献する可能性がある。
In the global GX context
This review integrates microscale imaging for CCS mineralization, relevant for global CCS scale-up. The decision tree based on cement and basalt studies aids formation assessment, contributing to secure CO2 storage methods.
👥 読者別の含意
🔬研究者:Researchers can adopt the integrated imaging framework and machine learning methods for advanced CO2 mineralization studies.
🏢実務担当者:Practitioners in CCS projects can use the decision tree for assessing formation suitability for CO2 mineralization.
🏛政策担当者:Policymakers should note the potential of microscale analysis to improve CO2 storage capacity estimates, supporting CCS deployment.
📄 Abstract（原文）
Safe and permanent storage of CO2 via Carbon Capture and Storage (CCS) technologies is required to limit global warming to 1.5°C–2°C above pre‐industrial levels. In situ mineralization of CO2 within reactive formations or silicate‐rich materials containing Ca‐ and Mg‐bearing minerals, such as cement and basalt, is a potentially rapid and secure method of geological CO2 storage. We review how advanced imaging techniques including X‐ray microcomputed tomography and electron microscopy can be integrated to understand the CO2 mineralization process at the microscale. We highlight how novel methods, including correlative microscopy and machine learning, are pivotal in studying complex reactions within heterogeneous samples. We explain how integrating microstructure analysis increases the reliability of reactive transport modeling and consequently improves the CO2 storage capacity assessment. Furthermore, we discuss challenges that need addressing to improve accuracy in measuring properties like reactive surface area and highlight the key areas for future research, including method validation and error estimation of properties acquired through imaging. While image analysis offers profound insights into CO2 mineralization, significant advancement is required in segmentation accuracy and reproducibility. Furthermore, using experimental observations from studies of cement and basalt, we suggest a decision tree for assessing the suitability of formations for CO2 mineralization.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1002/adsu.202501549first seen 2026-05-06 00:00:19
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