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Record W2513200125 · doi:10.1021/acsmacrolett.5b00320

One-Pack Epoxy Foaming with CO<sub>2</sub> as Latent Blowing Agent

2015· article· en· W2513200125 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 Macro Letters · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsEpoxyBlowing agentThermosetting polymerMaterials scienceCuring (chemistry)Amine gas treatingCarbamateFoaming agentThermal stabilityComposite materialChemical engineeringOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

In this work, we have successfully developed a novel approach to epoxy foaming using CO 2 as the latent blowing agent. The active amine groups of a commercially available curing agent for epoxy resin are blocked by CO 2 to obtain ammonium carbamate. The prepared ammonium carbamate can be decomposed by heating. Above 100 °C, CO 2 is released from the amine groups and acts as the blowing agent, while the amine compound is used as the curing agent and cures the epoxy resin. The ammonium carbamate combines the functionalities of latent blowing agent and curing agent. The one-pack epoxy foaming formulation has good storage stability under ambient conditions. The thermoset epoxy foams prepared from the one-pack formulation have low density, good mechanical properties, and thermal stability, competitive with the epoxy foams prepared by other methods. This novel approach is simple, environmentally benign, and cost-effective, which represents a promising direction in the development of epoxy foaming technologies.

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 categoriesInsufficient payload (model declined to judge)
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 score0.005
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)0.0000.001

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 head0.022
GPT teacher head0.235
Teacher spread0.213 · 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