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Record W2142417366 · doi:10.1002/app.20195

Effects of water on the curing and properties of epoxy adhesive used for bonding FRP composite sheet to concrete

2004· article· en· W2142417366 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Applied Polymer Science · 2004
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsConcordia University
Fundersnot available
KeywordsAdhesiveDurabilityCuring (chemistry)Materials scienceEpoxyComposite materialComposite number

Abstract

fetched live from OpenAlex

Abstract When a concrete surface is contaminated by water due to rain, saline water, ground water, and water jetty treatment, water, alkalis, and other contaminants on the concrete surface may interact with an epoxy adhesive used for bonding fiber‐reinforced polymer composite sheets to concrete. This can influence both the curing rate and the degree of cure of the curing reaction. This in turn can affect the time required for field application. It can also influence the mechanical properties and durability of epoxy adhesives. In this paper, water effects on the curing and properties of two kinds of commercial adhesives were evaluated. Curing kinetics were studied using isothermal DSC analysis. Results showed that water accelerated the curing reaction. However, excess water offsets part of the accelerating effect. While water is typically considered to be harmful to properties of adhesives, it was seen that a small amount (less than 2%) of water improved degree of cure, mechanical properties, and durability of adhesives. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 92: 2261–2268, 2004

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.259

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 head0.010
GPT teacher head0.215
Teacher spread0.205 · 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