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Record W2473921358 · doi:10.1021/acs.nanolett.6b01957

10.6% Certified Colloidal Quantum Dot Solar Cells via Solvent-Polarity-Engineered Halide Passivation

2016· article· en· W2473921358 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNano Letters · 2016
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaKing Abdullah University of Science and TechnologyMinistry of Knowledge Economy
KeywordsPassivationPhotovoltaicsQuantum dotMaterials scienceSolar cellEnergy conversion efficiencyNanotechnologyOptoelectronicsChemical engineeringPhotovoltaic systemLayer (electronics)

Abstract

fetched live from OpenAlex

Colloidal quantum dot (CQD) solar cells are solution-processed photovoltaics with broad spectral absorption tunability. Major advances in their efficiency have been made via improved CQD surface passivation and device architectures with enhanced charge carrier collection. Herein, we demonstrate a new strategy to improve further the passivation of CQDs starting from the solution phase. A cosolvent system is employed to tune the solvent polarity in order to achieve the solvation of methylammonium iodide (MAI) and the dispersion of hydrophobic PbS CQDs simultaneously in a homogeneous phase, otherwise not achieved in a single solvent. This process enables MAI to access the CQDs to confer improved passivation. This, in turn, allows for efficient charge extraction from a thicker photoactive layer device, leading to a certified solar cell power conversion efficiency of 10.6%, a new certified record in CQD photovoltaics.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.036
Threshold uncertainty score0.997

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)0.0040.004

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 head0.020
GPT teacher head0.206
Teacher spread0.186 · 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