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Record W2344031588 · doi:10.1021/acs.jpcc.5b10908

Computational Study of Magic-Size CdSe Clusters with Complementary Passivation by Carboxylic and Amine Ligands

2016· article· en· W2344031588 on OpenAlexafffund
Oleksandr Voznyy, Junais Habeeb Mokkath, Ankit Jain, Edward H. Sargent, Udo Schwingenschlögl

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2016
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaKing Abdullah University of Science and Technology
KeywordsPassivationPhotoluminescenceDangling bondExcitonCrystallographyCarboxylateLigand (biochemistry)Density functional theoryCluster (spacecraft)Amine gas treatingChemistryBinding energyMaterials scienceAbsorption spectroscopyMolecular physicsComputational chemistryAtomic physicsNanotechnologyCondensed matter physicsStereochemistryPhysicsOptoelectronicsOptics

Abstract

fetched live from OpenAlex

The electronic and optical properties of tetrahedral CdSe magic clusters (average diameter ∼1.5 nm) protected by carboxyl and amine ligands, which correspond to previously reported experimental structures, are studied using density functional theory. We find extreme ligand packing densities, capping every single dangling bond of the inorganic core, strong dependence of the Z-type metal carboxylate binding on the amount of excess amine, and potential for improved photoluminescence upon replacing phenyl ligands with alkanes. The computed absorption spectra of the Cd 35 Se 20 cluster agree well with experiments, resolving the 0.2 eV splitting of the first exciton peak due to spin–orbit coupling. We discuss the origin of the significant broadening of the optical spectra as due to phonons and structural variations in the ligand configurations and inorganic core apexes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.225
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations39
Published2016
Admission routes2
Has abstractyes

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Same venueThe Journal of Physical Chemistry CSame topicQuantum Dots Synthesis And PropertiesFrench-language works237,207