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Record W2261563029 · doi:10.1021/acs.iecr.5b03069

Development of Epoxy Foaming with CO<sub>2</sub> as Latent Blowing Agent and Principle in Selection of Amine Curing Agent

2015· article· en· W2261563029 on OpenAlexafffund
Qiang Ren, Haijin Xu, Qiang Yu, Shiping Zhu

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsMcMaster University
FundersJiangsu Provincial Department of EducationNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsCuring (chemistry)EpoxyAmine gas treatingBlowing agentCarbamateAmmoniumMaterials scienceFoaming agentChemistryChemical engineeringOrganic chemistryPolymer chemistryComposite material

Abstract

fetched live from OpenAlex

Some commercially available amines used as curing agents for epoxy resins can capture CO 2 to form ammonium carbamates, which represent a novel type of latent blowing and curing agent for epoxy foaming. The principles in the selection of suitable amines are critical for final applications. This work aimed to reveal these principles by screening and comparing the preparation, chemical structure and composition, and curing and foaming performance of several types of ammonium carbamates from typical amine curing agents. It is found that amines with p K a >9 are eligible to react with CO 2 to form ammonium carbamates with a high yield. Furthermore, the amines should have rigid cyclic groups in their structures to form a solid ammonium carbamate powder, which can be easily mixed with epoxy resins. The curing rate of the amine should not be much faster than the decomposition of the carbamate to obtain epoxy foams with good pore morphology and mechanical performance.

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)0.001
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 score0.004
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.083
GPT teacher head0.317
Teacher spread0.234 · 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 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

Citations28
Published2015
Admission routes2
Has abstractyes

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