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Nano-TiO<sub>2</sub>/polyurethane composites for antibacterial and self-cleaning coatings

2012· article· en· W2088618704 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

VenueNanotechnology · 2012
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsWestern University
Fundersnot available
KeywordsPolyurethaneMaterials sciencePolymerizationMonomerPolymerBifunctionalPolymer chemistryComposite materialChemical engineeringOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

Grafting from polymerization was used to synthesize nano-titania/polyurethane (nTiO(2)/polyurethane) composite coatings, where nTiO(2) was chemically attached to the backbone of the polyurethane polymer matrix with a bifunctional monomer, 2,2-bis(hydroxymethyl) propionic acid (DMPA). This bifunctional monomer can coordinate to nTiO(2) through an available -COOH group, with two available hydroxyl groups that can react with diisocyanate terminated pre-polyurethane through step-growth polymerization. The coordination reaction was monitored by FTIR and TGA, with the coordination reaction found to follow first order kinetics. After step-growth polymerization, the polyurethane nanocomposites were found to be stable on standing with excellent distribution of Ti in the polymer matrix without any significant agglomeration compared to simple physical mixtures of nTiO(2) in the polyurethane coatings. The functionalized nTiO(2)-polyurethane composite coatings showed excellent antibacterial activity against gram-negative bacteria Escherichia coli; 99% of E. coli were killed within less than one hour under solar irradiation. Self-cleaning was also demonstrated using stearic acid as a model for 'dirt'.

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 score0.027
Threshold uncertainty score0.922

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 integrity0.0010.000
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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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