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Record W2019863190 · doi:10.1039/c0cp01304h

Computational studies on the interactions among redox couples, additives and TiO2: implications for dye-sensitized solar cells

2010· article· en· W2019863190 on OpenAlexafffund
Abu Asaduzzaman, Georg Schreckenbach

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2010
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaWestern Canada Research GridCanarie
KeywordsDye-sensitized solar cellTriiodideIodideChemistryRedoxMoleculeSolar cellPhotochemistryBromideInorganic chemistryAdsorptionElectrodeMaterials scienceElectrolytePhysical chemistryOrganic chemistryOptoelectronics

Abstract

fetched live from OpenAlex

One of the major and unique components of dye-sensitized solar cells (DSSC) is the iodide/triiodide redox couple. Periodic density-functional calculations have been carried out to study the interactions among three different components of the DSSC, i.e. the redox shuttle, the TiO(2) semiconductor surface, and nitrogen containing additives, with a focus on the implications for the performance of the DSSC. Iodide and bromide with alkali metal cations as counter ions are strongly adsorbed on the TiO(2) surface. Small additive molecules also strongly interact with TiO(2). Both interactions induce a negative shift of the Fermi energy of TiO(2). The negative shift of the Fermi energy is related to the performance of the cell by increasing the open voltage of the cell and retarding the injection dynamics (decreasing the short circuit current). Additive molecules, however, have relatively weaker interaction with iodide and triiodide.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.278
Teacher spread0.258 · 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

Citations35
Published2010
Admission routes2
Has abstractyes

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