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Record W2915859582 · doi:10.1002/0471440264.pst648

Nitroxide‐Mediated Polymerization

2016· other· en· W2915859582 on OpenAlexaff
Eduardo Vivaldo‐Lima, Gabriel Jaramillo‐Soto, Alexander Penlidis

Bibliographic record

VenueEncyclopedia of Polymer Science and Technology · 2016
Typeother
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNitroxide mediated radical polymerizationPolymerizationMonomerNanotechnologyPolymerRadical polymerizationChemistryComputer scienceMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Nitroxide‐mediated polymerization (NMP) has been studied abundantly in the past three decades. There are several very good and recent reviews on the topic available in the literature. Although in this article we provide an overview on the research efforts focused on the polymer chemistry of NMP, our emphasis is placed on research aspects of NMP from a polymer reaction engineering perspective. Namely, we emphasize the use of engineering tools (such as mathematical modeling) on the design, analysis, and control of NMP processes (process engineering) and the well‐defined microstructures obtained by NMP (product engineering). These aspects are not sufficiently discussed or even included in previous reviews on NMP. Despite of all the intensive research programs carried out in academia and industrial research centers over 30 years, there are still several issues that limit the commercial exploitation of NMP. These issues, which include slow polymerization rates, reduced amount of monomers amenable for polymerization by NMP, low molecular weights, and insufficient commercial availability of NMP controllers, are also discussed.

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)0.000
metaresearch head score (Gemma)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.003
GPT teacher head0.219
Teacher spread0.216 · 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
GenreOther

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

Citations3
Published2016
Admission routes1
Has abstractyes

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