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Record W2022300605 · doi:10.1021/jp034683r

Evolution of Sodium Silicate Sols through the Sol-to-Gel Transition Assessed by the Fluorescence-Based Nanoparticle Metrology Approach

2003· article· en· W2022300605 on OpenAlexaff
Dina Tleugabulova, Zheng Zhang, John D. Brennan

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2003
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMicroviscosityPyranineSodium silicateNanoparticleAqueous solutionChemical engineeringChemistrySilicateRhodamine 6GMaterials scienceAnalytical Chemistry (journal)ChromatographyOrganic chemistryNanotechnologyComposite material

Abstract

fetched live from OpenAlex

The fluorescence-based nanosize metrology approach, proposed recently by Geddes and Birch (Geddes, C. D.; Birch, D. J. S. J. Non-Cryst. Solids 2000, 270, 191), was used to characterize the evolution of primary silica particles through the sol-to-gel transition and during aging of sodium silicate (SS) derived silica. In this study, the evolution of silica particles within SS derived silica was examined as a function of pH and glycerol doping through the sol-to-gel transition and up to 10 months after gelation. Time-resolved anisotropy decays were measured for the cationic dye rhodamine 6G, which was strongly adsorbed to the silica nanoparticles, and for the anionic probe pyranine, which provided accurate data on the microviscosity of the internal aqueous solution within sols and gels. The data provide evidence for the presence of nonaggregated primary particles far beyond the gelation point and even after prolonged aging of the resulting silica when aging is done either at low pH or in the presence of glycerol. Both the fraction of stable primary particles and the final size of the primary particles within the aged silica were dependent on the pH and the presence of glycerol. In general, lower pH values (pH 3.5) or the presence of glycerol increased the fraction of primary particles relative to samples at prepared at pH 6.5. Gelation pH did not have an affect on the final particle size, which was 1.5 ± 0.4 nm at both pH 3.5 and 6.5. On the other hand, a smaller particle size (0.9 ± 0.2 nm) was observed for SS sols and hydrogels containing 50% glycerol.

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)0.001
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 score0.007
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.014
GPT teacher head0.235
Teacher spread0.221 · 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

Citations23
Published2003
Admission routes1
Has abstractyes

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