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Record W4240144136 · doi:10.32920/ryerson.14643711

Fabrication and optimization of dye-sensitized solar cells

2021· preprint· en· W4240144136 on OpenAlexaff

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDye-sensitized solar cellFabricationMaterials scienceElectrolyteTransparency (behavior)Flexibility (engineering)TriphenylamineNanotechnologyBODIPYComputer scienceOptoelectronicsChemistryElectrodeOptics

Abstract

fetched live from OpenAlex

Dye-Sensitized Solar Cells (DSSCs) have garnered considerable attention given their desirable design properties including, transparency and flexibility. A considerable amount of research has been done in all facets of the DSSC permitting significant progress in device development. However, there is still much improvement needed to make DSSCs a viable alternative energy option. The I-/ I3 - electrolyte has been used extensively in DSSCs but has inherent drawbacks including its absorption range and corrosiveness to DSSC components. Recently, cobalt based electrolytes and hole transport materials (HTMs) have shown promise of improved performance, especially in combination with metal free dyes. This thesis aims to develop a mastery of device fabrication and then study and compare various electrolytes paired with triphenylamine (TPA) and BODIPY based dyes with the aim of improving DSSC efficiency and long-term stability.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.663
Threshold uncertainty score0.769

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 head0.012
GPT teacher head0.220
Teacher spread0.208 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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