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Record W2725008483

Homo and Hetero-Assembly of Inorganic Nanoparticles

2012· article· en· W2725008483 on OpenAlexfundno aff
Cristina Resetco

Bibliographic record

VenueTSpace · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsNanoparticleNanotechnologyMaterials scienceChemical engineeringChemistryEngineering
DOInot available

Abstract

fetched live from OpenAlex

This thesis describes the synthesis and assembly of metal and semiconductor nanoparticles (NPs). The two research topics include i) hetero-assembly of metal and semiconductor NPs, ii) effect of ionic strength on homo-assembly of gold nanorods (GNRs). First, we present hetero-assembly of GNRs and semiconductor quantum dots (QDs) in a chain using biotin-streptavidin interaction. We synthesized alloyed CdTeSe QDs and modified them with mercaptoundecanoic acid to render them water-soluble and to attach streptavidin. We synthesized GNRs by a seed-mediated method and selectively modified the ends with biotin. Hetero-assembly of QDs and GNRs depended on the size, ligands, and ratio of QDs and GNRs. Second, we controlled the rate of homo-assembly of GNRs by varying the ionic strength of the DMF/water solution. The solubility of polystyrene on the ends of GNRs depended on the ionic strength of the solution, which correlated with the rate of assembly of GNRs into chains.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.276
Teacher spread0.253 · 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 designObservational
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
Published2012
Admission routes1
Has abstractyes

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