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Record W2334934826 · doi:10.1021/sc400316v

Kinetics Study of Curing Epoxy Resins with Hydrolyzed Proteins and the Effect of Denaturants Urea and Sodium Dodecyl Sulfate

2013· article· en· W2334934826 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsUniversity of Alberta
FundersAlberta Livestock and Meat Agency
KeywordsChemistryDiglycidyl etherDifferential scanning calorimetrySodium dodecyl sulfateActivation energyUreaCuring (chemistry)EpoxyHydrolysisKineticsSodiumNuclear chemistryChromatographyOrganic chemistryPolymer chemistryBisphenol A

Abstract

fetched live from OpenAlex

The primary goal of this study was to determine the effect of two protein denaturants, urea and sodium dodecyl sulfate (SDS), on the apparent activation energy of cross-linking bisphenol A diglycidyl ether (DGEBA) with hydrolysate of waste animal proteins. Nonisothermal differential scanning calorimetry was used to measure the apparent activation energy of the reactions. The use of SDS resulted in a marked reduction in activation energy, comparable to the reduction in activation energy when a catalyst for epoxy rings, triethylamine (TEA), was used. The addition of urea slightly increased the activation energy. The heat of reaction increased in the presence of SDS because more reactive sites were made available for curing. This work demonstrates the use of SDS as a protein denaturant additive was an energetically efficient alternative to higher degrees of protein hydrolysis for subsequent curing of DGEBA.

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 categoriesMeta-epidemiology (narrow)
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 score0.238
Threshold uncertainty score1.000

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 head0.001
GPT teacher head0.159
Teacher spread0.157 · 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