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Record W2797355286 · doi:10.24084/repqj16.454

Design and Synthesis of New Fullerene Derivatives for Organic Solar Cells

2018· article· en· W2797355286 on OpenAlexaff
Jianping Lu, Salima Alem, Afshin Dadvand, Jianfu Ding, Ye Tao

Bibliographic record

VenueRenewable Energy and Power Quality Journal · 2018
Typearticle
Languageen
FieldChemistry
TopicFullerene Chemistry and Applications
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsFullereneOrganic solar cellMaterials scienceChemistryNanotechnologyOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

Bulk heterojunction (BHJ) organic solar cells based on p-type polymers and n-type fullerene derivatives have attracted increasing attention due to their promising potential for providing low–cost solar electricity. In this paper, we will introduce our recent work on the development of new fullerene derivatives. Through Rh complex catalyzed coupling reactions and cycloaddition reactions, we attached several organic functional groups to the fullerene skeleton. It was found that the organic substituents had little impact on the fullerene energy levels. Instead, the organic substituents have huge impact on the other physical properties of the resulting fullerene derivatives, such as solubility, crystallinity, and electron mobility. We designed and synthesized a novel series of alkoxy substituted indene derivatives as solubilizing groups for fullerenes. Preliminary experimental results demonstrated that these 5 alkoxyindene modified C70 derivatives are superior to widely used PC71BM when blended with poly[N-heptadecanyl-2,7 carbazole-alt-5,5-(4',7'-di-2-thienyl-2',1',3'- benzothiadiazole)] (PCDTBT) in BHJ solar cells. The device series resistance decreased from 10 cm2 for the PC71BM based device to 4 cm2 for the 5-methoxyindene-C70 monoadduct based device. As a result, the device fill factor increased from 0.60 to 0.69, and the overall EQE-calibrated power conversion efficiency was enhanced from 5.6% to 6.2%.

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 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: none
Teacher disagreement score0.495
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)0.0010.000

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 head0.031
GPT teacher head0.270
Teacher spread0.239 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueRenewable Energy and Power Quality JournalSame topicFullerene Chemistry and ApplicationsFrench-language works237,207