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Record W3024224858 · doi:10.1039/d0ra01815e

Characterization and simulation study of organic solar cells based on donor–acceptor (D–π–A) molecular materials

2020· article· en· W3024224858 on OpenAlexaff
Anass El Karkri, Zakaria El Malki, Mohammed Bouachrıne, Françoise Serein‐Spirau, Jean‐Marc Sotiropoulos

Bibliographic record

VenueRSC Advances · 2020
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsCanadian Nautical Research Society
FundersCentre National pour la Recherche Scientifique et TechniqueCentre National de la Recherche Scientifique
KeywordsMaterials scienceOrganic solar cellPhotoactive layerEnergy conversion efficiencyPolymer solar cellPEDOT:PSSDensity functional theoryThiopheneIndium tin oxideAcceptorSolar cellElectron acceptorActive layerChemical engineeringAnodeCarbazoleOptoelectronicsHybrid solar cellPhotochemistryElectrodeLayer (electronics)Physical chemistryNanotechnologyChemistryComputational chemistryOrganic chemistryPolymerComposite material

Abstract

fetched live from OpenAlex

-butyric acid methyl ester (PCBM) as an electron acceptor. The optoelectronic properties of these dyes were investigated by using the Density Functional Theory DFT/B3LYP/6-31G(d,p) method. We studied the influence of the variation of the thickness of the active layer, the temperature, and the density of the effective states of the electrons and the holes in the conduction and valence bands respectively on the performance of the solar cells based on [(Cbz-Mth)-BT]2-PCBM as a photoactive material, sandwiched between a transparent indium tin oxide (ITO) and an aluminum (Al) electrode. The addition of other thiophene units in the copolymer or the deposition of a layer of PEDOT between the anode (ITO) and the active layer, improves the performances of the cell, especially resulting in a remarkable increase in the value of the power conversion efficiency (PCE).

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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 designSimulation or modeling
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

Citations10
Published2020
Admission routes1
Has abstractyes

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