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Record W2613843084 · doi:10.1021/acsami.7b04028

Energy Transfer Kinetics in Photosynthesis as an Inspiration for Improving Organic Solar Cells

2017· article· en· W2613843084 on OpenAlexafffund
Collins Nganou, Gerhard Lackner, Bezu Teschome, M. Jamal Deen, Noam Adir, David Pouhè, Doru C. Lupascu, Martin Mkandawire

Bibliographic record

VenueACS Applied Materials & Interfaces · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhotosynthetic Processes and Mechanisms
Canadian institutionsMcMaster UniversityCape Breton University
FundersNatural Sciences and Engineering Research Council of CanadaUniversität Duisburg-EssenTechnische Universität BerlinTechnische Universität DresdenIsrael Science FoundationBundesministerium für Bildung und ForschungUnited States-Israel Binational Science Foundation
KeywordsMaterials scienceOrganic solar cellPhotocurrentExcitonCarbon nanotubeOptoelectronicsPhotochemistryKineticsPhotosynthetic reaction centreElectron transferChemical physicsNanotechnologyChemistryPolymerPhysics

Abstract

fetched live from OpenAlex

Clues to designing highly efficient organic solar cells may lie in understanding the architecture of light-harvesting systems and exciton energy transfer (EET) processes in very efficient photosynthetic organisms. Here, we compare the kinetics of excitation energy tunnelling from the intact phycobilisome (PBS) light-harvesting antenna system to the reaction center in photosystem II in intact cells of the cyanobacterium Acaryochloris marina with the charge transfer after conversion of photons into photocurrent in vertically aligned carbon nanotube (va-CNT) organic solar cells with poly(3-hexyl)thiophene (P3HT) as the pigment. We find that the kinetics in electron hole creation following excitation at 600 nm in both PBS and va-CNT solar cells to be 450 and 500 fs, respectively. The EET process has a 3 and 14 ps pathway in the PBS, while in va-CNT solar cell devices, the charge trapping in the CNT takes 11 and 258 ps. We show that the main hindrance to efficiency of va-CNT organic solar cells is the slow migration of the charges after exciton formation.

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 score0.004

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.237
Teacher spread0.227 · 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

Citations5
Published2017
Admission routes2
Has abstractyes

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