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Record W3081719165 · doi:10.1002/cssc.202001983

Sustainable Shape‐Memory Polyurethane from Abietic Acid: Superior Mechanical Properties and Shape Recovery with Tunable Transition Temperatures

2020· article· en· W3081719165 on OpenAlexaff
Pitchaimari Gnanasekar, Jing Chen, Shrestha Roy Goswami, Heyu Chen, Ning Yan

Bibliographic record

VenueChemSusChem · 2020
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsUniversity of Toronto
FundersNational Key Research and Development Program of China
KeywordsPolyurethaneAbietic acidMaterials scienceRosinShape-memory alloyHydrolysisAmorphous solidChemical engineeringBiodegradationComposite materialChemistryOrganic chemistryResin acid

Abstract

fetched live from OpenAlex

A new chemical architecture from abietic acid, consisting of a cycloaliphatic unsaturated terminal diisocyanate (AADI) structure, is synthesized and fully characterized. The AADI is then used to construct an amorphous and biocompatible shape-memory polyurethane (SMPU) network system with adjustable cross-linking densities over a wide range. The SMPU network exhibits good shape-memory properties with a shape fixing rate of greater than 98 % and a shape recovery rate of 95 %. In vitro hydrolytic biodegradation weight loss ratio of SMPUs reaches 71 % within eight weeks. The physical properties of these SMPUs are comparable to those reported for SMPUs obtained from commercially available petroleum-derived diisocyanates. This is the first time that multiple SMPU networks based on abietic acid have been reported. These environmentally-friendly SMPUs display a wide range of physicomechanical properties with promising hydrolytic degradability, showing good potential for practical application.

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 score0.008
Threshold uncertainty score0.918

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)0.0010.000

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 head0.016
GPT teacher head0.192
Teacher spread0.176 · 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

Citations17
Published2020
Admission routes1
Has abstractyes

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