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Record W2407896445 · doi:10.1002/adfm.201601570

Graphdiyne: An Efficient Hole Transporter for Stable High‐Performance Colloidal Quantum Dot Solar Cells

2016· article· en· W2407896445 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.

Bibliographic record

VenueAdvanced Functional Materials · 2016
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsMaterials scienceQuantum dotAnodeOptoelectronicsWork functionEnergy conversion efficiencyPhotovoltaic systemColloidLayer (electronics)Active layerNanotechnologyElectrodeChemical engineeringPhysics

Abstract

fetched live from OpenAlex

Graphdiyne, a novel large π‐conjugated carbon hole transporting material, is employed as anode buffer layer in colloidal quantum dots solar cells. Power conversion efficiency is notably enhanced to 10.64% from 9.49% compared to relevant reference devices. Hole transfer from the quantum dot solid active layer to the anode can be appreciably enhanced only by using graphdiyne to lower the work function of the colloidal quantum dot solid. It is found that the all‐carbon buffer layer prolongs the carrier lifetime, reducing surface recombination on the previously neglected back side of the photovoltaic device. Remarkably, the device also shows high long‐term stability in ambient air. The results demonstrate that graphdiyne may have diverse applications in enhancing optoelectronic devices.

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 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 score0.009
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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.212
Teacher spread0.195 · 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