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Record W2067557219 · doi:10.1126/science.1173812

Colloidal Quantum-Dot Photodetectors Exploiting Multiexciton Generation

2009· article· en· W2067557219 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience · 2009
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhotocurrentOptoelectronicsLead sulfidePhotoconductivityPhotodetectorQuantum dotMaterials scienceBand gapQuantum efficiencyPhotonMultiple exciton generationPhotovoltaicsUltravioletPhotovoltaic systemOpticsPhysics

Abstract

fetched live from OpenAlex

Multiexciton generation (MEG) has been indirectly observed in colloidal quantum dots, both in solution and the solid state, but has not yet been shown to enhance photocurrent in an optoelectronic device. Here, we report a class of solution-processed photoconductive detectors, sensitive in the ultraviolet, visible, and the infrared, in which the internal gain is dramatically enhanced for photon energies Ephoton greater than 2.7 times the quantum-confined bandgap Ebandgap. Three thin-film devices with different quantum-confined bandgaps (set by the size of their constituent lead sulfide nanoparticles) show enhancement determined by the bandgap-normalized photon energy, Ephoton/Ebandgap, which is a clear signature of MEG. The findings point to a valuable role for MEG in enhancing the photocurrent in a solid-state optoelectronic device. We compare the conditions on carrier excitation, recombination, and transport for photoconductive versus photovoltaic devices to benefit from MEG.

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.

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 score0.010
Threshold uncertainty score0.565

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.045
GPT teacher head0.268
Teacher spread0.223 · 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