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Record W2859775017 · doi:10.1021/acs.jpcc.8b04931

Effects of Surface Passivation on Trap States, Band Bending, and Photoinduced Charge Transfer in P3HT/TiO<sub>2</sub> Hybrid Inverse Opals

2018· article· en· W2859775017 on OpenAlexafffund
Christopher S. Kerr, Artem Kryukovskiy, Jennifer I. L. Chen

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsBand bendingPassivationMaterials scienceOxidePhotoluminescencePolaronNanoparticleOptoelectronicsBioelectronicsNanorodNanotechnologyChemical physicsChemical engineeringChemistryPhysics

Abstract

fetched live from OpenAlex

We investigate the effect of a common TiO2 passivation reagent, TiCl4, on the photoinduced charge transfer of poly(3-hexylthiophene) (P3HT) to TiO2 in the inverse opal structure. Treating the inorganic oxide framework with TiCl4 leads to an increase in the size of the TiO2 nanoparticles, a thickening of the inverse opal framework, and a decrease in the trap-state photoluminescence. These changes lead to different energy alignments at the interface. In comparison to the unpassivated P3HT/TiO2 inverse opal, we measured a larger polaron yield, by as high as ninefold, and significantly shorter and more uniformly distributed polaron lifetimes in TiCl4-treated samples. We show that downward band bending in the polymer can be circumvented by tuning the trap states on the metal oxide using TiCl4, thereby eliminating the energetic barrier for photoelectron injection from the polymer to the metal oxide. The findings suggest a way to overcome a potential factor that has plagued the performance of metal oxide–polymer hybrid photovoltaics.

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 score0.002
Threshold uncertainty score0.378

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 head0.006
GPT teacher head0.226
Teacher spread0.220 · 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

Citations6
Published2018
Admission routes2
Has abstractyes

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