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Record W1248051192

Investigation into synthesis and the microstructure of silver nanoparticles coated with alkanethiols and thiol-functionalized polymers

2015· dissertation· en· W1248051192 on OpenAlexfundno aff
Farhad Faghihi

Bibliographic record

VenueOpen ULeth Scholarship (OPUS) (University of Lethbridge) · 2015
Typedissertation
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesUniversity of Lethbridge
KeywordsThiolMicrostructurePolymerMaterials scienceNanoparticlePolymer chemistryNanotechnologyChemical engineeringPolymer scienceOrganic chemistryComposite materialChemistryEngineering
DOInot available

Abstract

fetched live from OpenAlex

A comprehensive investigation into the synthesis and the characterization of discrete silver nanoparticles coated with alkanethiols and thiolate functionalized polymers is presented. Small and uniform alkanethiol capped silver nanoparticles were synthesized via the Brust and Schiffrin method. To improve the characteristics of the resulting nanoparticles, the intermediate stage of this reaction was investigated. The major precursor to the silver nanoparticles was identified and its microstructure was characterized.
\nPolymers bearing single or multiple thiolates were prepared by synthesis of well-defined precursors via RAFT polymerization and their subsequent post-polymerization modification. Nanoparticles stabilized with thiol-terminated PMMA were produced via a “grafting-to” process. A novel method was developed for the synthesis of small, uniform, and re-dispersible nanoparticles encapsulated with multiple-thiolate functional random copolymers of vinylbenzyl chloride. The effect of reaction conditions on the quality of these nanoparticles were evaluated. Adsorption of the copolymers on the nanoparticles were studied by 1H NMR relaxation measurements.

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 categoriesMeta-epidemiology (narrow)
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 score0.263
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.221
Teacher spread0.203 · 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.

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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

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