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Record W2323993109 · doi:10.1021/nn3033997

Electric Field-Induced Emission Enhancement and Modulation in Individual CdSe Nanowires

2012· article· en· W2323993109 on OpenAlexaff
Felix Vietmeyer, Tamar Tchelidze, Veronica Tsou, Boldizsár Jankó, Masaru Kuno

Bibliographic record

VenueACS Nano · 2012
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Waterloo
FundersDivision of Chemistry
KeywordsNanowirePhotoluminescenceMaterials scienceElectric fieldModulation (music)OptoelectronicsQuantum-confined Stark effectRelaxation (psychology)Quantum dotField electron emissionCondensed matter physicsNanotechnologyStark effectElectronPhysics

Abstract

fetched live from OpenAlex

CdSe nanowires show reversible emission intensity enhancements when subjected to electric field strengths ranging from 5 to 22 MV/m. Under alternating positive and negative biases, emission intensity modulation depths of 14 ± 7% are observed. Individual wires are studied by placing them in parallel plate capacitor-like structures and monitoring their emission intensities via single nanostructure microscopy. Observed emission sensitivities are rationalized by the field-induced modulation of carrier detrapping rates from NW defect sites responsible for nonradiative relaxation processes. The exclusion of these states from subsequent photophysics leads to observed photoluminescence quantum yield enhancements. We quantitatively explain the phenomenon by developing a kinetic model to account for field-induced variations of carrier detrapping rates. The observed phenomenon allows direct visualization of trap state behavior in individual CdSe nanowires and represents a first step toward developing new optical techniques that can probe defects in low-dimensional materials.

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 score0.021
Threshold uncertainty score0.261

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 science0.0000.000
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 head0.036
GPT teacher head0.267
Teacher spread0.231 · 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

Citations27
Published2012
Admission routes1
Has abstractyes

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