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Record W2082355876 · doi:10.1021/nl080373e

Engineering the Temporal Response of Photoconductive Photodetectors via Selective Introduction of Surface Trap States

2008· article· en· W2082355876 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

VenueNano Letters · 2008
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhotoconductivityPhotodetectorTrap (plumbing)OptoelectronicsMaterials scienceResponse timeDark currentNanotechnologyPhysicsComputer science

Abstract

fetched live from OpenAlex

Photoconductive photodetectors fabricated using simple solution-processing have recently been shown to exhibit high gains (>1000) and outstanding sensitivities ( D* > 10(13) Jones). One ostensible disadvantage of exploiting photoconductive gain is that the temporal response is limited by the release of carriers from trap states. Here we show that it is possible to introduce specific chemical species onto the surfaces of colloidal quantum dots to produce only a single, desired trap state having a carefully selected lifetime. In this way we demonstrate a device that exhibits an attractive photoconductive gain (>10) combined with a response time ( approximately 25 ms) useful in imaging. We achieve this by preserving a single surface species, lead sulfite, while eliminating lead sulfate and lead carboxylate. In doing so we preserve the outstanding sensitivity of these devices, achieving a specific detectivity of 10(12) Jones in the visible, while generating a temporal response suited to imaging 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.

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 score0.006
Threshold uncertainty score0.357

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 studies0.0000.000
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 head0.013
GPT teacher head0.203
Teacher spread0.190 · 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