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Record W4408963825 · doi:10.1016/j.eng.2025.02.021

Corrosion and Material Degradation in Geological CO2 Storage: A Critical Review

2025· review· en· W4408963825 on OpenAlexaff
Xin Fan, Qing Hu, Y. Frank Cheng

Bibliographic record

VenueEngineering · 2025
Typereview
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCorrosionDegradation (telecommunications)MetallurgyEnvironmental scienceForensic engineeringMaterials scienceEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

At present, carbon capture and storage (CCS) is the only mature and commercialized technology capable of effectively and economically reducing greenhouse gas emissions to achieve a significant and immediate impact on the CO 2 level on Earth. Notably, long-term geological storage of captured CO 2 has emerged as a primary storage method, given its minimal impact on surface ecological environments and high level of safety. The integrity of CO 2 storage wellbores can be compromised by the corrosion of steel casings and degradation of cement in supercritical CO 2 storage environments, potentially leading to the leakage of stored CO 2 from the sites. This critical review endeavors to establish a knowledge foundation for the corrosion and materials degradation associated with geological CO 2 storage through an in-depth examination and analysis of the environments, operation, and the state-of-the-art progress in research pertaining to the topic. This article discusses the physical and chemical properties of CO 2 in its supercritical phase during injection and storage. It then introduces the principle of geological CO 2 storage, considerations in the construction of storage systems, and the unique geo–bio–chemical environment involving aqueous media and microbial communities in CO 2 storage. After a comprehensive analysis of existing knowledge on corrosion in CO 2 storage, including corrosion mechanisms , parametric effects , and corrosion rate measurements, this review identifies technical gaps and puts forward potential avenues for further research in steel corrosion within geological CO 2 storage systems.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.307
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2025
Admission routes1
Has abstractyes

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