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Record W2806218724 · doi:10.1002/adma.201801720

Activated Electron‐Transport Layers for Infrared Quantum Dot Optoelectronics

2018· article· en· W2806218724 on OpenAlexaff
Jongmin Choi, Jea Woong Jo, F. Pelayo Garcı́a de Arquer, Yong‐Biao Zhao, Bin Sun, Junghwan Kim, Min‐Jae Choi, Se‐Woong Baek, Andrew H. Proppe, Ali Seifitokaldani, Dae‐Hyun Nam, Peicheng Li, Olivier Ouellette, Younghoon Kim, Oleksandr Voznyy, Sjoerd Hoogland, Shana O. Kelley, Zheng‐Hong Lu, Edward H. Sargent

Bibliographic record

VenueAdvanced Materials · 2018
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceOptoelectronicsPhotovoltaicsPassivationQuantum dotDopingBand gapElectrodeSolar cellTandemEnergy conversion efficiencyUltravioletQuantum efficiencyNanotechnologyPhotovoltaic systemLayer (electronics)

Abstract

fetched live from OpenAlex

Photovoltaic (PV) materials such as perovskites and silicon are generally unabsorptive at wavelengths longer than 1100 nm, leaving a significant portion of the IR solar spectrum unharvested. Small-bandgap colloidal quantum dots (CQDs) are a promising platform to offer tandem complementary IR PV solutions. Today, the best performing CQD PVs use zinc oxide (ZnO) as an electron-transport layer. However, these electrodes require ultraviolet (UV)-light activation to overcome the low carrier density of ZnO, precluding the realization of CQD tandem photovoltaics. Here, a new sol-gel UV-free electrode based on Al/Cl hybrid doping of ZnO (CAZO) is developed. Al heterovalent doping provides a strong n-type character while Cl surface passivation leads to a more favorable band alignment for electron extraction. CAZO CQD IR solar cell devices exhibit, at wavelengths beyond the Si bandgap, an external quantum efficiency of 73%, leading to an additional 0.92% IR power conversion efficiency without UV activation. Conventional ZnO devices, on the other hand, add fewer than 0.01 power points at these operating conditions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.016
GPT teacher head0.268
Teacher spread0.252 · 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

Citations68
Published2018
Admission routes1
Has abstractyes

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