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Record W2039415710 · doi:10.1063/1.3454923

Self-organized phase segregation between inorganic nanocrystals and PC61BM for hybrid high-efficiency bulk heterojunction photovoltaic cells

2010· article· en· W2039415710 on OpenAlexaff
Sai‐Wing Tsang, Huiying Fu, Jianying Ouyang, Yanguang Zhang, Kui Yu, Jianping Lu, Ye Tao

Bibliographic record

VenueApplied Physics Letters · 2010
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsSteacie Institute for Molecular SciencesInstitute for Microstructural Sciences
Fundersnot available
KeywordsMaterials sciencePhotovoltaic systemHeterojunctionHybrid solar cellNanocrystalPhase (matter)Energy conversion efficiencyPolymer solar cellOptoelectronicsComposite numberLayer (electronics)Quantum dot solar cellNanotechnologyChemical engineeringComposite materialChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

We demonstrate a simple approach to generate phase segregation between colloidal PbS nanocrystals (NCs) and organic [6,6]-phenyl C61 butyric acid methyl ester (PC61BM). Continuous vertical phase segregation is observed in cross-linked composite films of NCs and PC61BM. Hybrid bulk heterojunction photovoltaic cells fabricated with the phase segreated composite layer have achieved the state-of-art power conversion efficiency of 3.7% under one sun of simulated Air Mass 1.5 Global solar irradiation. The presented method can be generally applied in other NC/organic systems for the development of hybrid heterojunction photovoltaic cells.

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)
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 score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.011
GPT teacher head0.213
Teacher spread0.203 · 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

Citations23
Published2010
Admission routes1
Has abstractyes

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