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Record W2100934003 · doi:10.1002/chem.200501081

Control of Metal‐Ion Composition in the Synthesis of Ternary II‐II′‐VI Nanoparticles by Using a Mixed‐Metal Cluster Precursor Approach

2005· article· en· W2100934003 on OpenAlexafffund
M.W. DeGroot, Harald Rösner, John F. Corrigan

Bibliographic record

VenueChemistry - A European Journal · 2005
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Ontario
KeywordsNanoclustersNanoparticleNanocrystalline materialTernary operationNanocrystalCluster (spacecraft)Materials scienceCrystallographyMetalThermal decompositionMetal ions in aqueous solutionIonStoichiometryAnalytical Chemistry (journal)Physical chemistryChemistryNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

The ternary molecular nanoclusters [Zn(x)Cd(10-x)Se4(SePh)12(PnPr3)4] (x = 1.8, 1 a; x = 2.6, 1 b) were employed as single-source precursors for the synthesis of high-quality hexagonal Zn(x)Cd(1-x)Se nanocrystals. The tellurium clusters [Zn(x)Cd(10-x)Te4(TePh)12(PnPr3)4] (x = 1.8, 2 a; x = 2.6, 2 b) are equally convenient precursors for the synthesis cubic Zn(x)Cd(1-x)E nanoparticles. The thermolysis of the cluster molecules in hexadecylamine provides an efficient system in which the inherent metal-ion stoichiometry of the clusters is retained in the nanocrystalline products, whilst also affording control of particle size within the 2-5 nm range. In all cases, the nanoparticles are monodisperse, and luminescence spectra exhibit emission energies close to the absorption edge. Analysis of the optical spectra and X-ray diffraction patterns of these materials indicates a metal-ion concentration gradient within the structures of the nanocrystals, with Zn(II) ions predominantly located near the surface of the particles.

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)0.002
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 score0.011
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.022
GPT teacher head0.219
Teacher spread0.197 · 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

Citations42
Published2005
Admission routes2
Has abstractyes

Explore more

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