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Record W2153355901 · doi:10.1081/mc-120027933

Emulsion‐Based Pressure‐Sensitive Adhesives: A Review

2004· review· en· W2153355901 on OpenAlex
Renata Jovanović, Marc A. Dubé

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of macromolecular science. Part C, Reviews in macromolecular chemistry and physics/Journal of macromolecular science. Reviews in macromolecular chemistry and physics · 2004
Typereview
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPressure sensitiveEmulsionAdhesiveMaterials scienceComposite materialChemical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Pressure sensitive adhesives (PSAs) adhere instantaneously to a variety of surfaces upon application of slight pressure and can be obtained using different technologies. Increasing environmental concerns and regulations are the major driving forces for the development of emulsion‐based PSAs. Given the number of factors affecting the emulsion polymerization process and versatility of emulsion‐based polymers, there is a need to identify and model those factors that significantly influence particular PSA applications. In this review, factors such as emulsion polymerization components, latex rheology, and film formation are examined in light of their relevance to adhesion. In addition, the body of knowledge related to measurement methods, design factors, and modeling of each of the three major PSA performance characteristics (i.e., tack, peel strength, and shear strength) is reviewed with a particular emphasis on emulsion‐based PSAs. Keywords: Pressure sensitive adhesivesEmulsion polymerizationPeel strengthTackShear strength

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.

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)0.011
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.373
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.003
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0100.003
Bibliometrics0.0000.006
Science and technology studies0.0010.004
Scholarly communication0.0010.001
Open science0.0040.001
Research integrity0.0010.004
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 head0.022
GPT teacher head0.294
Teacher spread0.272 · 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