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Record W2333015484 · doi:10.1021/es303392v

Deposition Kinetics of Quantum Dots and Polystyrene Latex Nanoparticles onto Alumina: Role of Water Chemistry and Particle Coating

2013· article· en· W2333015484 on OpenAlexaff
Iván R. Quevedo, Adam L. J. Olsson, Nathalie Tufenkji

Bibliographic record

VenueEnvironmental Science & Technology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsMcGill University
Fundersnot available
KeywordsQuartz crystal microbalanceChemical engineeringHumic acidNanoparticleDeposition (geology)Particle depositionPolystyreneAdsorptionSurface chargeChemistryCoatingParticle (ecology)Quantum dotMaterials scienceNanotechnologyOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

A clear understanding of the factors controlling the deposition behavior of engineered nanoparticles (ENPs), such as quantum dots (QDs), is necessary for predicting their transport and fate in natural subsurface environments and in water filtration processes. A quartz crystal microbalance with dissipation monitoring (QCM-D) was used to study the effect of particle surface coatings and water chemistry on the deposition of commercial QDs onto Al2O3. Two carboxylated QDs (CdSe and CdTe) with different surface coatings were compared with two model nanoparticles: sulfate-functionalized (sPL) and carboxyl-modified (cPL) polystyrene latex. Deposition rates were assessed over a range of ionic strengths (IS) in simple electrolyte (KCl) and in electrolyte supplemented with two organic molecules found in natural waters; namely, humic acid and rhamnolipid. The Al2O3 collector used here is selected to be representative of oxide patches found on the surface of aquifer or filter grains. Deposition studies showed that ENP deposition rates on bare Al2O3 generally decreased with increasing salt concentration, with the exception of the polyacrylic-acid (PAA) coated CdTe QD which exhibited unique deposition behavior due to changes in the conformation of the PAA coating. QD deposition rates on bare Al2O3 were approximately 1 order of magnitude lower than those of the polystyrene latex nanoparticles, likely as a result of steric stabilization imparted by the QD surface coatings. Adsorption of humic acid or rhamnolipid on the Al2O3 surface resulted in charge reversal of the collector and subsequent reduction in the deposition rates of all ENPs. Moreover, the ratio of the two QCM-D output parameters, frequency and dissipation, revealed key structural information of the ENP-collector interface; namely, on bare Al2O3, the latex particles were rigidly attached as compared to the more loosely attached QDs. This study emphasizes the importance of considering the nature of ENP coatings as well as organic molecule adsorption onto particle and collector surfaces to avoid underestimating ENP mobility in natural and engineered aquatic environments.

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 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 score0.084
Threshold uncertainty score0.570

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 studies0.0000.002
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 head0.002
GPT teacher head0.169
Teacher spread0.167 · 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 teacher head, 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

Citations65
Published2013
Admission routes1
Has abstractyes

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