MétaCan
Menu
Back to cohort
Record W4248523006 · doi:10.1149/ma2018-03/3/201

Sustained Lasing Using Colloidal Quantum Dots

2018· article· en· W4248523006 on OpenAlexaff
Michael M. Adachi

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsLasing thresholdMaterials scienceQuantum dotOptoelectronicsLaserLuminescenceSpontaneous emissionNanotechnologyOpticsWavelength

Abstract

fetched live from OpenAlex

Colloidal Quantum dots (CQDs) are solution synthesized nanocrystals that exhibit bright emission and narrow bandwidth, making them promising for light emission applications such as down-conversion luminescence, light amplification, and lasing. The emission wavelength of CQDs can also be controlled by the size of the nanocrystals potentially leading to tunable color light emission. In this work, CdSe-CdS-ZnS core-shell-shell quantum dots were synthesized and incorporated into a distributed feedback optical cavity to demonstrate sustained lasing. We show that the duration of lasing is limited by thermal runaway and that thermal management in the form of engineering the CQDs to form ultra-compact films and using a thermally conductive substrate can lead to efficient heat dissipation and therefore sustained lasing. The ultra-compact films were achieved by replacing long-chained organic ligands with inorganic-halide passivation. The new CQD films exhibited high modal gain (1,200 cm-1) and a low amplified spontaneous emission threshold of 50kw/cm2 (average peak power). Sustained lasing was first demonstrated for a microsecond, followed by fully continuous wave operation.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.035
GPT teacher head0.271
Teacher spread0.236 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueECS Meeting AbstractsSame topicQuantum Dots Synthesis And PropertiesFrench-language works237,207