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Record W3083700370 · doi:10.1002/aenm.202002084

Efficient and Stable Colloidal Quantum Dot Solar Cells with a Green‐Solvent Hole‐Transport Layer

2020· article· en· W3083700370 on OpenAlexaff
Hong Il Kim, Junwoo Lee, Min‐Jae Choi, Seung Un Ryu, Kyoungwon Choi, Seungjin Lee, Sjoerd Hoogland, F. Pelayo Garcı́a de Arquer, Edward H. Sargent, Taiho Park

Bibliographic record

VenueAdvanced Energy Materials · 2020
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
FundersNational Research Foundation of KoreaMinistry of Education
KeywordsMaterials scienceEnergy conversion efficiencyStackingChlorobenzenePolymerActive layerQuantum dotChemical engineeringPolymer solar cellQuantum efficiencyOptoelectronicsColloidDegradation (telecommunications)Layer (electronics)NanotechnologyComposite materialOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

Abstract Next‐generation solution‐processed solar cells will hopefully be processed using green solvents, and will unite high performance with operating stability. Colloidal quantum dot/polymer hybrid solar cells are of interest for their harvest of the visible as well as the near infrared; however, today's best polymer hole‐transporting layers (HTLs) rely on processing using hazardous solvents such as chlorobenzene. This stems from the strong polymer–polymer attraction in polymeric p ‐type materials, which accounts for their limited solubility. Here, a new random polymeric HTL (asy‐ranPBTBDT) is reported that is soluble in green solvents such as 2‐methylanisole without compromising ultimate device power conversion efficiency. The new polymer structure induces a strong π–π stacking face‐on orientation and less lateral grain growth compared to control asy‐PBTBDT, leading to reduced charge recombination and improved device stability. The resulting device exhibits a power conversion efficiency (PCE) of 13.2% and retains 89% of its initial efficiency after 120 h of continuous device operation at the maximum power point, compared to a PCE of 11.4% and 71% degradation for control 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.

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 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 score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.204
Teacher spread0.189 · 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

Citations37
Published2020
Admission routes1
Has abstractyes

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