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Record W2001225142 · doi:10.1117/12.484193

Thin films of light-responsive polymers for sensing and surface patterning

2003· article· en· W2001225142 on OpenAlexaff
Christopher J. Barrett, Ozzy Mermut, Kevin G. Yager

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsAzobenzeneEllipsometryAdsorptionChromophoreAllylaminePolymerMaterials scienceThin filmChemical engineeringLayer (electronics)Layer by layerKineticsPolyelectrolytePolymer chemistryChemistryPhotochemistryNanotechnologyOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

The kinetics of electrostatic layer-by-layer adsorption of a weakly charged polycation, poly(allylamine hydrochloride), PAH, and a polyanion containing an azobenzene chromophore, P-Azo, was studied using UV-vis spectroscopy and ellipsometry. The thickness of the multilayer films was first measured over the adsorption pH range of 3 to 11, and the growth of multilayers was examined as function of time and concentration. Films assembled in bath pH near that of their pKa value produced both the thickest films, and displayed remarkably rapid adsorption isotherms. In some PAH/P-Azo films a significantly large thickness was achieved in less than 5 seconds, which is more than two orders of magnitude faster than what is usually observed. We show that this anomalously rapid adsorption is a consequence of the weak acid-base nature of the layers. Self-assembled polymer films containg azobenzene groups are interesting materials as the chromophores can be addressed as light-responsive groups for surface patterning and sensing.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.013
GPT teacher head0.244
Teacher spread0.230 · 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 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

Citations0
Published2003
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicPolymer Surface Interaction StudiesFrench-language works237,207