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Record W4214559020 · doi:10.1002/adma.202200321

Controlled Crystal Plane Orientations in the ZnO Transport Layer Enable High‐Responsivity, Low‐Dark‐Current Infrared Photodetectors

2022· article· en· W4214559020 on OpenAlexaff
Darshan H. Parmar, João M. Pina, Tong Zhu, Maral Vafaie, Ozan Atan, Margherita Biondi, Amin Morteza Najarian, Sjoerd Hoogland, Edward H. Sargent

Bibliographic record

VenueAdvanced Materials · 2022
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsResponsivityMaterials scienceDark currentPhotocurrentOptoelectronicsAtomic layer depositionPhotodetectorQuantum dotPhotoconductivityUltravioletInfraredAdsorptionCrystal (programming language)Quantum efficiencyZincLayer (electronics)NanotechnologyOpticsChemistry

Abstract

fetched live from OpenAlex

Colloidal quantum dots (CQD) have emerged as attractive materials for infrared (IR) photodetector (PD) applications because of their tunable bandgaps and facile processing. Presently, zinc oxide is the electron-transport layer (ETL) of choice in CQD PDs; however, ZnO relies on continuous ultraviolet (UV) illumination to remove adsorbed oxygen and maintain high external quantum efficiency (EQE), speed, and photocurrent. Here, it is shown that ZnO is dominated by electropositive crystal planes which favor excessive oxygen adsorption, and that this leads to a high density of trap states, an undesired shift in band alignment, and consequent poor performance. Over prolonged operation without UV exposure, oxygen accumulates at the electropositive planes, trapping holes and degrading performance. This problem is addressed by developing an electroneutral plane composition at the ZnO surface, aided by atomic layer deposition (ALD) as the means of materials processing. It is found that ALD ZnO has 10× lower binding energy for oxygen than does conventionally deposited ZnO. IR CQD PDs made with this ETL do not require UV activation to maintain low dark current and high EQE.

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)0.002
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 score0.019
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0070.000

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 head0.016
GPT teacher head0.249
Teacher spread0.234 · 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

Citations40
Published2022
Admission routes1
Has abstractyes

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