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Record W2331210574 · doi:10.1021/ar200113c

Nanoparticle ζ -Potentials

2011· article· en· W2331210574 on OpenAlexaff
Tennyson L. Doane, Chi-Hung Chuang, Reghan J. Hill, Clemens Burda

Bibliographic record

VenueAccounts of Chemical Research · 2011
Typearticle
Languageen
FieldChemistry
TopicElectrostatics and Colloid Interactions
Canadian institutionsMcGill University
Fundersnot available
KeywordsElectrophoresisElectrokinetic phenomenaElectrophoretic light scatteringNanoparticleNanotechnologySurface chargeParticle (ecology)ColloidCoatingChemistryMaterials scienceComputer scienceDynamic light scatteringChromatographyPhysical chemistry

Abstract

fetched live from OpenAlex

For over half a century, alternating electric fields have been used to induce particle transport, furnishing the ζ-potential of analytes with sizes ranging from a few nanometers to several micrometers. Concurrent advances in nanotechnology have provided new materials for catalysis, self-assembly, and biomedical applications, all of which benefit from a thorough understanding of particle surface charge. Therefore, the measurement of the ζ-potential via electrophoretic light scattering (ELS) has become essential for nanoparticle (NP) research. However, the interpretation of NP electrophoretic mobility, especially that of ligand-coated NPs, can be a complex undertaking. Despite the inherent intricacy of these data, key concepts from colloidal science can help to distill valuable information from ELS. In this Account, we adopt PEGylated Au NPs as an illustrative example to explore extensions of the classical theories of Smoluchowski, Hückel, and Henry to more contemporary theories for ligand-coated NP systems such as those from Ohshima, and Hill, Saville, and Russel. First, we review the basic experimental considerations necessary to understand NP electrophoretic mobility, identifying when O'Brien and White's numerical solution of the standard electrokinetic model should be adopted over Henry's closed-form analytical approximation. Next, we explore recent developments in the theory of ligand-coated particle electrophoresis, and how one can furnish accurate and meaningful relationships between measured NP mobility, ζ-potential, and surface charge. By identifying key ligand-coated NP parameters (e.g., coating thickness, permeability, molecular mass, and hydrodynamic segment size), we present a systematic method for quantitatively interpreting NP electrophoretic mobility. In addition to reviewing theoretical foundations, we describe our recent results that examine how the unique surface curvature of NPs alters and controls their properties. These data provide guidelines that can expedite the rational design of NPs for advanced uses, such as heterogeneous catalysis and in vivo drug delivery. As a practical demonstration of these concepts, we apply the ligand-coated theory to a recently developed noncovalent PEGylated Au NP drug-delivery system. Our analysis suggests that anion adsorption on the Au NP core may enhance the stability of these NP-drug conjugates in solution. In addition to providing useful nanochemistry insights, the information in this Account will be useful to biomedical and materials engineers, who use ELS and ζ-potentials for understanding NP dynamics.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.005

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 head0.114
GPT teacher head0.381
Teacher spread0.266 · 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

Citations331
Published2011
Admission routes1
Has abstractyes

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