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Record W4313596284 · doi:10.1002/cjce.24825

Synthesis and characterization of polyolefin thermoplastic elastomers: A review

2023· review· en· W4313596284 on OpenAlexvenueno aff
Minghao Sun, Yangke Xiao, Kan Liu, Xuan Yang, Pingwei Liu, Suyun Jie, Jijiang Hu, Shengbin Shi, Qingyue Wang, Khak Ho Lim, Zhenxue Liu, Bo‐Geng Li, Wenjun Wang

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2023
Typereview
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsnot available
FundersZhejiang UniversityState Key Laboratory of Chemical EngineeringNational Natural Science Foundation of China
KeywordsPolyolefinElastomerThermoplastic elastomerMaterials scienceNatural rubberOlefin fiberThermoplasticCopolymerPolymer scienceComposite materialPolymer chemistryPolymer

Abstract

fetched live from OpenAlex

Abstract Polyolefin thermoplastic elastomers (TPE‐Os) are high‐performance polyolefins consisting of both plastic and rubber phases. Compared with other thermoplastic elastomers, the TPE‐Os possess better chemical stability, transparency, re‐processability, and electrical insulation, which renders their broad applications possible. By manipulating chain structures and topologies of the TPE‐Os, differently structured polyolefins with improved thermal and mechanical properties have been developed, including ethylene and α‐olefin random copolymers (POEs), olefin block copolymers (OBCs), comb‐shaped polyolefin elastomers (CPOEs), and dynamically cross‐linked polyolefin elastomers. Herein, we review the synthesis of the POE, OBC, CPOE, and dynamical cross‐linked polyolefin elastomer, including the catalyst systems, polymerization techniques, processes, and kinetic modelling. The characterization of the TPE‐Os and the relationships between the TPE‐O chain structure, aggregated state, and product performance are discussed. The future development of higher‐performance TPE‐Os is envisaged.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.235
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations80
Published2023
Admission routes1
Has abstractyes

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