MétaCan
Menu
Back to cohort
Record W3201717881 · doi:10.18280/acsm.450410

Hydrothermal Aging and Bonding Properties of a New Room Temperature Cured Structural Adhesive in Building Components

2021· article· en· W3201717881 on OpenAlexvenueno aff
Hui Li, Guan Gong, Tian Lv

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2021
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
FundersNanhu Scholars Program for Young Scholars of Xinyang Normal UniversityXinyang Normal UniversityNatural Science Foundation of Henan ProvinceNatural Science Foundation of Hainan Province
KeywordsAdhesiveHydrothermal circulationMaterials scienceComposite materialCuring (chemistry)Relative humidityArrhenius equationUltimate tensile strengthGlass transitionHumidityStructural integrityActivation energyStructural engineeringLayer (electronics)PolymerChemistryChemical engineering

Abstract

fetched live from OpenAlex

his paper firstly explores the hydrothermal aging performance of a new room temperature cured structural adhesive at four different levels of relative humidity through dynamic mechanical analysis (DMA). The results show that the strengthening effect of post-curing was stronger than weakening effect of humidity. Then, the Arrhenius equation was introduced to calculate the ratio of the apparent activation energy of this adhesive at the glass transition temperature before and after hydrothermal aging. The little change of the ratio suggests that the adhesive boasts a strong resistance to hydrothermal aging. In addition, the adhesive was tested on concrete structures at room temperature to observe its repairing effect of concrete cracks. The observations reveal that the compressive strength of the cracked concrete block repaired by the adhesive was as high as 90.5% of that of the intact concrete block. Furthermore, the adhesive was used to bond rebars to concrete under three different constant tensile speeds. The results demonstrate that the bonding effect was better under slow constant loading.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.041
GPT teacher head0.273
Teacher spread0.233 · 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 designBench or experimental
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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAnnales de Chimie Science des MatériauxSame topicConcrete and Cement Materials ResearchFrench-language works237,207