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Record W4313333139 · doi:10.1021/acsphotonics.2c01353

Vertical Architecture Solution-Processed Quantum Dot Photodetectors with Amorphous Selenium Hole Transport Layer

2022· article· en· W4313333139 on OpenAlexaff
Atreyo Mukherjee, Haripriya Kannan, Le Thanh Triet Ho, Zhihang Han, Jann Stavro, Adrian Howansky, Neha Nooman, Kim Kisslinger, Sébastien Léveillé, Orhan Kizilkaya, Xiangyu Liu, Håvard Mølnås, Shlok Joseph Paul, Dong Hyun Sung, Elisa Riedo, Abdul K. Rumaiz, Dragica Vasileska, Wei Zhao, Ayaskanta Sahu, Amir H. Goldan

Bibliographic record

VenueACS Photonics · 2022
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsAnalogic (Canada)
FundersArmy Research OfficeBasic Energy SciencesDivision of Electrical, Communications and Cyber SystemsNational Institute of Biomedical Imaging and BioengineeringSchlumberger Foundation
KeywordsPhotodetectorOptoelectronicsMaterials scienceQuantum dotDark currentSpecific detectivityQuantum efficiencyPhotodiodePhotonics

Abstract

fetched live from OpenAlex

Colloidal quantum dots (CQDs) provide wide spectral tunability and high absorption coefficients owing to quantum confinement and large oscillator strengths, which along with solution processability, allow a facile, low-cost, and room-temperature deposition technique for the fabrication of photonic devices. However, many solution-processed CQD photodetector devices demonstrate low specific-detectivity and slow temporal response. To achieve improved photodetector characteristics, limiting carrier recombination and enhancing photogenerated carrier separation are crucial. In this study, we develop and present an alternate vertical-stack photodetector wherein we use a solution-processed quantum dot photoconversion layer coupled to an amorphous selenium (a-Se) wide-bandgap charge transport layer that is capable of exhibiting single-carrier hole impact ionization and is compatible with active-matrix readout circuitry. This a-Se chalcogenide transport layer enables the fabrication of high-performance and reliable solution-processed quantum dot photodetectors, with enhanced charge extraction capabilities, high specific detectivity (D* ∼ 0.5–5 × 1012 Jones), fast 3 dB electrical bandwidth (3 dB BW ∼ 22 MHz), low dark current density (JD ∼ 5–10 pA/cm2), low noise current (in ∼ 20–25 fW/Hz1/2), and high linear dynamic range (LDR ∼ 130–150 dB) across the measured visible electromagnetic spectrum (∼405–656 nm).

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 categoriesInsufficient payload (model declined to judge)
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 score0.999

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.218
Teacher spread0.201 · 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.

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

Citations7
Published2022
Admission routes1
Has abstractyes

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