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Record W4409498777 · doi:10.5006/lac23-20430

Synthesis of High Solids Alkyds Modified with Reactive Diluents for Encapsulation and Use in Self-healing Coatings

2023· article· en· W4409498777 on OpenAlexaff
Felipe Garcia Nunes, Elber V. Bendinelli, Mark D. Soucek, Idalina Vieira Aoki

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsDiluentEncapsulation (networking)Self-healingMaterials scienceChemical engineeringChemistryComputer scienceOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

A great effort has been devoted to the research of self-healing coatings, as they provide anticorrosive protection even when the painting is damaged [1]. The encapsulation of drying oils is an established strategy to promote self-healing. Microcapsules release the seed oil upon mechanical damage, which triggers self-healing in the coating defect as the oil undergoes oxidative polymerization [2]. Alkyds are also a great candidate for microencapsulation due to their green nature, oxidative-driven polymerization, and better anticorrosive properties than seed oils [3]. However, the high viscosity of alkyds imposes great challenges for their encapsulation. In this work, a high solids alkyd from dehydrated castor oil (DCO) was developed with suitable viscosity for microencapsulation using seed oil-based reactive diluents.

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)0.000
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 score0.090
Threshold uncertainty score0.483

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 head0.023
GPT teacher head0.254
Teacher spread0.231 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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