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Record W2780660461 · doi:10.1117/1.jpe.7.035504

Zr-doped TiO2 as a thermostabilizer in plasmon-enhanced dye-sensitized solar cells

2017· article· en· W2780660461 on OpenAlex
Anastasia Pasche, Bernd Grohe, Silvia Mittler, Paul A. Charpentier

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Photonics for Energy · 2017
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsWestern University
Fundersnot available
KeywordsDye-sensitized solar cellPlasmonMaterials scienceDopingSurface plasmon resonancePhotovoltaic systemPlasmonic solar cellOptoelectronicsNanotechnologyPhotovoltaicsSolar cellAbsorption (acoustics)Solar energyHybrid solar cellNanoparticleChemistryPolymer solar cellComposite material

Abstract

fetched live from OpenAlex

Harvesting solar energy is a promising solution toward meeting the world’s ever-growing energy demand. Dye-sensitized solar cells (DSSCs) are hybrid organic–inorganic solar cells with tremendous potential for commercial application, but they are plagued by inefficiency due to their poor sunlight absorption. Plasmonic silver nanoparticles (AgNPs) have been shown to enhance the absorptive properties of DSSCs, but their plasmonic resonance can cause thermal damage resulting in cell deterioration. Hence, the influence of Zr-doped TiO2 on the efficiency of plasmon-enhanced DSSCs was studied, showing that 5 mol.% Zr-doping of the photoactive TiO2 material can improve the photovoltaic performance of DSSCs by 44%. By examining three different DSSC designs, it became clear that the efficiency enhancing effect of Zr strongly depends on the proximity of the Zr-doped material to the plasmonic AgNPs.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.118
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.264
Teacher spread0.250 · 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