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Record W4412117412 · doi:10.1139/cjce-2025-0009

Electrochemical surface engineering for optimizing concrete interactions with formwork and reinforcement

2025· article· en· W4412117412 on OpenAlexvenueno aff
N. Coniglio

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsFormworkReinforcementElectrochemistryMaterials scienceStructural engineeringEngineeringComputer scienceComposite materialElectrodeChemistry

Abstract

fetched live from OpenAlex

Concrete is a material commonly used in the construction industry. A critical functional aspect of concrete lies in managing the adhesion between curing concrete and solid materials such as formwork and reinforced bars. This paper reviews current methodologies for adhesion control, emphasizing the role of electrochemical science in engineering surface reactivity and stability to achieve adjusted adhesion properties. Main topics include the contribution of the interfacial transition zone, corrosion inhibitors addition, and surface polarization techniques, with an attention on their synergistic actions on adherence during the hydration process. In addition, major challenges are identified in bridging the gap between laboratory-scale findings and practical, field-based applications. Future directions are proposed, focusing on the integration of advanced materials, predictive modeling, and scalable technologies. The review concludes by highlighting the necessity of aligning fundamental research with industrial needs, paving the way for sustainable, efficient, and durable concrete structures that meet modern construction demands.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.175
Teacher spread0.171 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations2
Published2025
Admission routes1
Has abstractyes

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