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Record W2359615498

Polymer product engineering:an emerging discipline of chemical engineering for high performance polymer materials

2014· article· en· W2359615498 on OpenAlexaff
Bo Li

Bibliographic record

VenueScientia Sinica Chimica · 2014
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPolymerizationPolymerChemical reaction engineeringMaterials sciencePolyolefinCopolymerRadical polymerizationNanotechnologyPolymer sciencePolymer chemistryChemical engineeringProcess engineeringCatalysisChemistryOrganic chemistryEngineeringComposite material
DOInot available

Abstract

fetched live from OpenAlex

Chemical product engineering represents an emerging discipline rooted to chemical engineering. Its core content of research lies in precision production of chemical structures. Polymer products contain complex structures at multiple scales. Polymerization processes, to a large extent, determine polymer chain microstructures and morphologies. In the recent years, we developed various polymerization processes and produced polymers having precisely designed chain microstructures. These polymer products showed high performances and superior material properties in targeted applications. Our methodology employs kinetic modeling combined with reactor technologies, based on extensive mechanistic research on polymerization mechanisms. In controlled/living radical (co) polymerization, we developed a novel model-based computer-programed semi-batch copolymerization technology that allows unprecedented precise control over end-to-end copolymer composition of individual chains. In catalytic polymerization of olefins, we developed a reactor technology for in-situ production of polyolefin alloys. This paper provides a brief summary of the recent advances in the polymer product engineering researches.

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: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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
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
Published2014
Admission routes1
Has abstractyes

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