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Record W4223653752 · doi:10.1021/acsenergylett.2c00515

Heteroatoms as Rotational Blocking Groups for Non-Fullerene Acceptors in Indoor Organic Solar Cells

2022· article· en· W4223653752 on OpenAlexafffund
Chase L. Radford, Priyadarshani D. Mudiyanselage, Amy L. Stevens, Timothy L. Kelly

Bibliographic record

VenueACS Energy Letters · 2022
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHeteroatomBlocking (statistics)AcceptorFullereneMaterials scienceOrganic solar cellAlkylPhotochemistryOptoelectronicsNanotechnologyChemistryOrganic chemistryComputer scienceComposite material

Abstract

fetched live from OpenAlex

Organic solar cells are particularly attractive for indoor and low-light applications; however, photocurrents are low under these conditions, and devices are particularly sensitive to the presence of defects and trap states. A rotational blocking group is often added to non-fullerene acceptors to reduce both energetic disorder and the number of defects in the active layer. These blocking groups are most often alkyl chains, which require several synthetic steps to install; this inevitably lowers yields and increases costs. Here we report the addition of heteroatom-based blocking groups to the commonly used non-fullerene acceptor IDIC. These blocking groups are synthetically easy to install and highly effective; bromination leads to significant improvements in the efficiency of PTQ10:IDIC devices under both one-sun and low-light illumination. In contrast, thioether blocking groups improve efficiency under one-sun illumination but reduce it in dim light, highlighting the need to design and test donor:acceptor systems specifically for indoor applications.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.004
GPT teacher head0.178
Teacher spread0.174 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations22
Published2022
Admission routes2
Has abstractyes

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