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Record W2765725413 · doi:10.1021/acs.jpcc.7b08439

Extending Semiconductor Nanocrystals from the Quantum Dot Regime to the Molecular Cluster Regime

2017· article· en· W2765725413 on OpenAlexaff
Lakshay Jethi, Timothy G. Mack, Patanjali Kambhampati

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2017
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsMcGill University
Fundersnot available
KeywordsBohr radiusQuantum dotNanocrystalRADIUSMaterials scienceCluster (spacecraft)SemiconductorChemical physicsMolecular physicsAtomic radiusCondensed matter physicsNanotechnologyChemistryOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

The size-dependent optical and electronic properties of semiconductor nanocrystal (NC) have been exploited over decades for various applications. This size dependence involves a transition from the regime of bulk colloids of ∼100 nm radius to quantum dots (QDs) of ∼10 nm radius, the details of which are material specific. To understand the transition from the QD regime (∼10 nm) to the molecular cluster regime (∼1 nm) of nanocrystals, we have carefully synthesized a set of CdSe nanocrystals with sizes ranging from 0.89 to 1.66 nm in radius. As the nanocrystals become small, the surface emission strongly increases in amplitude, and the core emission broadens and red-shifts. These effects are rationalized in terms of coupling to ligands via electron transfer theory. The core emission spectra arise from increased vibrational coupling of ligands for very small NC. The surface emission amplitudes arise from a size-dependent surface free energy. The transition from the QD to the molecular cluster regime is found to be at 1.2 nm radius, in contrast to the transition from the bulk to QD transition at the Bohr radius of 5.4 nm in CdSe. These size-dependent surface electronic phenomena may be used for light emission applications.

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)0.001
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 score0.016
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.026
GPT teacher head0.269
Teacher spread0.243 · 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

Citations52
Published2017
Admission routes1
Has abstractyes

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