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Record W2896598473 · doi:10.1002/smll.201801668

Direct Measurement of Electronic Band Structure in Single Quantum Dots of Metal Chalcogenide Composites

2018· article· en· W2896598473 on OpenAlexafffund
Daniele Benetti, Daling Cui, Haiguang Zhao, Federico Rosei, Alberto Vomiero

Bibliographic record

VenueSmall · 2018
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsInstitut National de la Recherche Scientifique
FundersCanada Research ChairsEuropean Commission
KeywordsKelvin probe force microscopeQuantum dotChalcogenideMaterials scienceHighly oriented pyrolytic graphiteNanotechnologyComposite numberElectronic structureOptoelectronicsPyrolytic carbonElectronic band structureFermi levelChemical physicsComposite materialGraphiteChemical engineeringChemistryCondensed matter physicsAtomic force microscopyElectronComputational chemistry

Abstract

fetched live from OpenAlex

Metal chalcogenide quantum dots (QDs) are among the most promising materials as light harvesters in all-inorganic systems for applications in solar cells and production of solar fuels. The electronic band structure of composite QDs formed by lead and cadmium chalcogenides directly grafted on highly oriented pyrolytic graphite surfaces through successive ionic layer absorption and reaction is investigated. Atomic force microscopy and Kelvin probe force microscopy (KPFM) are applied to investigate PbS, CdS, and PbS/CdS QD systems. The variation of the surface potential of individual QDs is measured, investigating the evolution of the electronic band structure as a function of QD size and composition. A shift of the Fermi level toward more negative values occurs when QD size is increased. The shift is more pronounced in CdS than in PbS, while the composite PbS/CdS exhibits an intermediate behavior. The calculated shift is in good agreement with the experiments. These results highlight the ability of KPFM to directly measure the electronic band structure in individual QDs of metal chalcogenide composites. This feature regulates charge dynamics in composite systems, thereby affecting device performance. This work provides valuable insights for applications in several fields, in which charge injection plays a major role.

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)0.001
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 score0.003
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.037
GPT teacher head0.222
Teacher spread0.184 · 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

Citations23
Published2018
Admission routes2
Has abstractyes

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