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Record W2895759650 · doi:10.1002/adma.201803830

Butylamine‐Catalyzed Synthesis of Nanocrystal Inks Enables Efficient Infrared CQD Solar Cells

2018· article· en· W2895759650 on OpenAlexafffund
Junghwan Kim, Olivier Ouellette, Oleksandr Voznyy, Mingyang Wei, Jongmin Choi, Min‐Jae Choi, Jea Woong Jo, Se‐Woong Baek, James Z. Fan, Makhsud I. Saidaminov, Bin Sun, Peicheng Li, Dae‐Hyun Nam, Sjoerd Hoogland, Zheng‐Hong Lu, F. Pelayo Garcı́a de Arquer, Edward H. Sargent

Bibliographic record

VenueAdvanced Materials · 2018
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceNanocrystalButylamineNanotechnologyCatalysisInfraredQuantum dot solar cellChemical engineeringSolar cellOptoelectronicsPolymer solar cellOrganic chemistryOpticsChemistry

Abstract

fetched live from OpenAlex

Abstract The best‐performing colloidal‐quantum‐dot (CQD) photovoltaic devices suffer from charge recombination within the quasi‐neutral region near the back hole‐extracting junction. Graded architectures, which provide a widened depletion region at the back junction of device, could overcome this challenge. However, since today's best materials are processed using solvents that lack orthogonality, these architectures have not yet been implemented using the best‐performing CQD solids. Here, a new CQD ink that is stable in nonpolar solvents is developed via a neutral donor ligand that functions as a phase‐transfer catalyst. This enables the realization of an efficient graded architecture that, with an engineered band‐alignment at the back junction, improves the built‐in field and charge extraction. As a result, optimized IR CQD solar cells ( E g ≈ 1.3 eV) exhibiting a power conversion efficiency (PCE) of 12.3% are reported. The strategy is applied to small‐bandgap (1 eV) IR CQDs to augment the performance of perovskite and crystalline silicon (cSi) 4‐terminal tandem solar cells. The devices show the highest PCE addition achieved using a solution‐processed active layer: a value of +5% when illuminated through a 1.58 eV bandgap perovskite front filter, providing a pathway to exceed PCEs of 23% in 4T tandem configurations with IR CQD PVs.

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 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 score0.007
Threshold uncertainty score0.818

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 studies0.0000.000
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 head0.004
GPT teacher head0.197
Teacher spread0.193 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations83
Published2018
Admission routes2
Has abstractyes

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