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Record W2518338203 · doi:10.1038/ncomms12223

General low-temperature reaction pathway from precursors to monomers before nucleation of compound semiconductor nanocrystals

2016· article· en· W2518338203 on OpenAlexafffund
Kui Yu, Xiangyang Liu, Ting Qi, Hua‐Qing Yang, Dennis M. Whitfield, Queena Y. Chen, Erik J. C. Huisman, Changwei Hu

Bibliographic record

VenueNature Communications · 2016
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsNational Research Council Canada
FundersFundamental Research Funds for the Central UniversitiesNational Research Council CanadaNational Natural Science Foundation of China
KeywordsMonomerNucleationStoichiometryChalcogenideNanocrystalLigand (biochemistry)ChemistryCrystallographyMetalPhysical chemistryMaterials scienceNanotechnologyPolymerOrganic chemistry

Abstract

fetched live from OpenAlex

Little is known about the molecular pathway to monomers of semiconductor nanocrystals. Here we report a general reaction pathway, which is based on hydrogen-mediated ligand loss for the precursor conversion to 'monomers' at low temperature before nucleation. We apply (31)P nuclear magnetic resonance spectroscopy to monitor the key phosphorous-containing products that evolve from MXn+E=PPh2H+HY mixtures, where MXn, E=PPh2H, and HY are metal precursors, chalcogenide precursors, and additives, respectively. Surprisingly, the phosphorous-containing products detected can be categorized into two groups, Ph2P-Y and Ph2P(E)-Y. On the basis of our experimental and theoretical results, we propose two competing pathways to the formation of M2En monomers, each of which is accompanied by one of the two products. Our study unravels the pathway of precursor evolution into M2En monomers, the stoichiometry of which directly correlates with the atomic composition of the final compound nanocrystals.

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 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 score0.053
Threshold uncertainty score0.422

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 science0.0010.000
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 head0.021
GPT teacher head0.260
Teacher spread0.239 · 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

Citations57
Published2016
Admission routes2
Has abstractyes

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