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Record W2019468239 · doi:10.1021/jp0644816

Mechanism and Origin of Exciton Spin Relaxation in CdSe Nanorods

2006· article· en· W2019468239 on OpenAlexaff
Jeongho Kim, C. Wong, P. Sreekumari Nair, Karolina P. Fritz, Sandeep Kumar, Gregory D. Scholes

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2006
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExcitonNanorodRelaxation (psychology)Condensed matter physicsSpin (aerodynamics)Molecular physicsBiexcitonSpin polarizationMaterials scienceChemistryElectronPhysicsNanotechnologyQuantum mechanics

Abstract

fetched live from OpenAlex

The dynamics of exciton spin relaxation in CdSe nanorods of various sizes and shapes are measured by an ultrafast transient polarization grating technique. The measurement of the third-order transient grating (3-TG) signal utilizing linear cross-polarized pump pulses enables us to monitor the history of spin relaxation among the bright exciton states with a total angular momentum of F = +/-1. From the measured exciton spin relaxation dynamics, it is found that the effective mechanism of exciton spin relaxation is sensitive to the size of the nanorod. Most of the measured cross-polarized 3-TG signals show single-exponential spin relaxation dynamics, while biexponential spin relaxation dynamics are observed in the nanorod of the largest diameter. This analysis suggests that a direct exciton spin flip process between the bright exciton states with F = +/-1 is the dominant spin relaxation mechanism in small nanocrystals, and an indirect spin flip via the dark states with F = +/-2 contributes as the size of the nanocrystal increases. This idea is examined by simulations of 3-TG signals with a kinetic model for exciton spin relaxation considering the states in the exciton fine structure. Also, it is revealed that the rate of exciton spin relaxation has a strong correlation with the diameter, d, of the nanorod, scaled by the power law of 1/d4, rather than other shape parameters such as length, volume, or aspect ratio.

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 score0.012
Threshold uncertainty score0.148

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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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

Citations37
Published2006
Admission routes1
Has abstractyes

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