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Record W4392635208 · doi:10.1134/s0040579523330138

Computational Explanation of the Photovoltaic Cells Properties of the PCBM and PC71BM Derivatives using the Density Functional Theory

2023· article· en· W4392635208 on OpenAlexaff
Zair Mohammed El Amine, Derbal Habak Hassina, Hafida Chemouri, Jean‐Michel Nunzi

Bibliographic record

VenueTheoretical Foundations of Chemical Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsQueen's University
Fundersnot available
KeywordsDensity functional theoryPhotovoltaic systemMaterials scienceFunctional theoryComputational chemistryChemistryEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Abstract Organic photovoltaic cells are electronic devices that convert sunlight into electricity. To this end, the number of studies on organic photovoltaic cells (OVCs) is growing, and this trend is expected to continue. Computational studies are still needed to verify and prove the capability of CVOs, specifically the nanometer molecule PCBM, based on successful experimental results. In this paper, we present a theoretical and computational investigation of PCBM and PC71BM derivatives using the DFT method. On this basis, we employ independent and time-dependent density theories. HOMO, LUMO and GAPH-L energies, ionization potentials and electronic affinity are determined and found to be in agreement with experiments. Using DFT theory based on B3LYP and M062X methods with bases 6-31G (d,p) and 6-311G (d), calculations show that the most efficient acceptors are presented in the group of PC71BM derivatives and are in substantial agreement with experiments. The geometries of the structures are optimized by Gaussian 09.

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 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 score0.188
Threshold uncertainty score0.249

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 head0.193
Teacher spread0.182 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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