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Record W4281614296 · doi:10.1007/s12274-022-4421-4

Size matters: Steric hindrance of precursor molecules controlling the evolution of CdSe magic-size clusters and quantum dots

2022· article· en· W4281614296 on OpenAlexaff
Juan Shen, Chaoran Luan, N. L. Rowell, Yang Li, Meng Zhang, Xiaoqin Chen, Kui Yu

Bibliographic record

VenueNano Research · 2022
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsSteric effectsChemistryQuantum dotCadmium selenideSelenideMoleculeCarboxylic acidNanotechnologyStereochemistrySeleniumOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

Little is known about how to precisely promote the selective production of either colloidal semiconductor metal chalcogenide (ME), magic-size clusters (MSCs), or quantum dots (QDs). Recently, a two-pathway model has been proposed to comprehend their evolution; here, we reveal for the first time that the size of precursors plays a decisive role in the selected evolution pathway of MSCs and QDs. With the reaction of cadmium myristate (Cd(MA)2) and tri-n-octylphosphine selenide (SeTOP) in 1-octadecene (ODE) as a model system, the size of Cd precursors was manipulated by the steric hindrance of carboxylic acid (RCOOH) additive. Without RCOOH, the reaction produced both CdSe MSCs and QDs (from 100 to 240 °C). With RCOOH, the reaction produced MSCs or QDs when R was small (such as CH3−) or large (such as C6H5−), respectively. According to the two-pathway model, the selective evolution is attributed to the promotion and suppression of the self-assembly of Cd and Se precursors, respectively. We propose that the addition of carboxylic acid may occur ligand exchange with Cd(MA)2, causing the different sizes of Cd precursor. The results suggest that the size of Cd precursors regulates the self-assemble behavior of the precursors, which dictates the directed evolution of either MSCs or QDs. The present findings bring insights into the two-pathway model, as the size of M and E precursors determine the evolution pathways of MSCs or QDs, the understanding of which is of great fundamental significance toward mechanism-enabled design and predictive synthesis of functional nanomaterials.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.062
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.038
GPT teacher head0.299
Teacher spread0.260 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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