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Electrophoretic deposition of linear polyethylenimine and composite films

2013· article· en· W1999570699 on OpenAlex

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

VenueSurface Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicElectrophoretic Deposition in Materials Science
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPolyethylenimineElectrophoretic depositionMaterials scienceDeposition (geology)Composite numberComposite materialElectrophoresisChemical engineeringNanotechnologyChromatographyCoatingChemistryEngineering

Abstract

fetched live from OpenAlex

Electrophoretic deposition method has been developed for the electrodeposition of linear polyethylenimine (LPEI) films. The deposition mechanism is based on the electrophoresis of protonated LPEI-H + , base generation at the cathode surface, charge neutralisation and formation of insoluble LPEI films. Quartz crystal microbalance data, coupled with the results of electron microscopy, showed that deposition rate and film thickness can be varied and controlled by the variation of deposition time and voltage. LPEI films provided corrosion protection of stainless steel substrates. LPEI was used for the dispersion, charging and electrophoretic deposition of TiO 2 , hydrotalcite and MnO 2 particles and fabrication of composite films. Scanning electron microscopy and thermogravimetric analysis showed the formation of composite films, containing 45·4%TiO 2 , 53·1% hydrotalcite and 33·3%MnO 2 in the LPEI matrix. The film thickness was varied in the range of 0·1–4 μm by variation of the deposition time at a constant deposition voltage. The proposed approach paves the way for the fabrication of organic–inorganic composite films combining functional properties of LPEI and inorganic materials.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.214
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.003
GPT teacher head0.169
Teacher spread0.166 · 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