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Record W4393863420 · doi:10.1021/acs.jpclett.4c00553

Frequency-Dependent Microelectrophoresis Study of Colloids with Tunable Surface Charge

2024· article· en· W4393863420 on OpenAlexafffund
Ashish Joy, Shivani Semwal, Anand Yethiraj

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2024
Typearticle
Languageen
FieldChemistry
TopicElectrostatics and Colloid Interactions
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicroelectrophoresisElectrophoresisColloidSurface chargeCharge densityDouble layer (biology)HemocytometerChemistryChemical physicsAnalytical Chemistry (journal)Materials scienceNanotechnologyChromatographyLayer (electronics)Physical chemistry

Abstract

fetched live from OpenAlex

Nonaqueous poly(methyl methacrylate) (PMMA) colloidal suspensions in a solvent that is simultaneously matched in both density and refractive index have been important for real-space studies of colloidal self-assembly, but their complex electrostatic character remains largely unexplored. Electrophoresis is a powerful tool for determining the surface potential and charge of the colloidal suspension; however, because of refractive index matching, standard electrophoresis measurements are not feasible. We carry out microscope-based microelectrophoresis measurements on PMMA colloids in cyclohexyl bromide and cis-trans decalin to measure particle charge as a function of salt concentration in both DC and frequency-variable AC fields. The colloid charge depends on salt concentration and reverses sign near 0.35 μM, providing evidence that solution ions are actively modifying the colloid surface. The frequency dependence of the electrophoretic mobility yields the characteristic time scale for electric double-layer polarization and provides intriguing evidence for Manning condensation and polyion formation.

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 score0.000
Threshold uncertainty score0.002

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)0.0000.000

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 head0.005
GPT teacher head0.224
Teacher spread0.219 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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