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Record W3198922774 · doi:10.32920/ryerson.14643711.v1

Fabrication and optimization of dye-sensitized solar cells

2021· preprint· en· W3198922774 on OpenAlexaff
Benjamin Fischer

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDye-sensitized solar cellFabricationElectrolyteMaterials scienceFlexibility (engineering)Transparency (behavior)TriphenylamineNanotechnologyComputer scienceOptoelectronicsChemistryElectrode

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 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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