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Record W3094861029 · doi:10.1002/cjce.23914

Experimental methods in chemical engineering: Zeta potential

2020· article· en· W3094861029 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2020
Typearticle
Languageen
FieldChemistry
TopicElectrostatics and Colloid Interactions
Canadian institutionsPolytechnique Montréal
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Apoio à Pesquisa do Distrito FederalCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsZeta potentialElectrophoresisSurface chargeNanoparticleColloidSuspension (topology)Double layer (biology)Particle (ecology)Particle sizeDebye lengthCounterionMaterials scienceNanotechnologyViscosityChemical physicsThermodynamicsChemical engineeringChemistryChromatographyIonLayer (electronics)Physical chemistryMathematicsPhysicsComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Zeta potential (ZP) is a parameter that expresses the electrochemical equilibrium between particles and liquids like in nanoparticle (NP) colloidal solutions with applications in medicine, pharmaceuticals, chemical production, mineral processing, and water and soil purification. Smoluchowski's theory applies to the ZP particles that are larger the interfacial layer but neglects surface conductivity. The Debye‐Hückel theory correctly approximates the concentration of ions in a double layer but fails to account for the dependence of ZP on the concentration of counterions. Determining ZP of NPs is essential to proper NP characterization. For instance, developing well‐defined therapeutic‐relevant nanoformulations needs information on NPs size, surface charge, stability and agglomeration behaviour. This approach has many practical challenges, from inadequate knowledge of operating standards to sampling, data interpretation and good laboratory practice for the experiments replicability. However, in drug delivery research, very little literature can provide a clear, succinct explanation of these techniques. Looking for specific guidelines to overcome frequently encountered problems during ZP measurements. This article explores factors influencing colloidal particle stability. Measurement criteria such as applied voltage, number of measurements, electrophoretic mobility (EPM), size distribution, surface shape, temperature, viscosity, particle concentration, zeta potential, nanoparticles, colloidal suspension, electrophoretic mobility, and pH.

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 score0.057
Threshold uncertainty score0.531

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 integrity0.0000.001
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 head0.011
GPT teacher head0.251
Teacher spread0.240 · 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