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Record W2519281984 · doi:10.1038/srep33359

Charge transport mechanism in lead oxide revealed by CELIV technique

2016· article· en· W2519281984 on OpenAlexafffund
Oleksii Semeniuk, G. Juška, J. O. Oelerich, M. Wiemer, S. D. Baranovskiǐ, A. Reznik

Bibliographic record

VenueScientific Reports · 2016
Typearticle
Languageen
FieldMaterials Science
TopicTransition Metal Oxide Nanomaterials
Canadian institutionsThunder Bay Regional Research InstituteLakehead University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchDeutsche Forschungsgemeinschaft
KeywordsMaterials scienceCharge (physics)Charge carrierElectric fieldCrystalliteDispersion (optics)Lead oxideOxideOptoelectronicsChemical physicsCondensed matter physicsPhysicsOpticsComposite material

Abstract

fetched live from OpenAlex

Although polycrystalline lead oxide (PbO) belongs to the most promising photoconductors for optoelectronic and large area detectors applications, the charge transport mechanism in this material still remains unclear. Combining the conventional time-of-flight and the photo-generated charge extraction by linear increasing voltage (photo-CELIV) techniques, we investigate the transport of holes which are shown to be the faster carriers in poly-PbO. Experimentally measured temperature and electric field dependences of the hole mobility suggest a highly dispersive transport. In order to analyze the transport features quantitatively, the theory of the photo-CELIV is extended to account for the dispersive nature of charge transport. While in other materials with dispersive transport the amount of dispersion usually depends on temperature, this is not the case in poly-PbO, which evidences that dispersive transport is caused by the spatial inhomogeneity of the material and not by the energy disorder.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.011
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.227
Teacher spread0.216 · 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.

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

Citations26
Published2016
Admission routes2
Has abstractyes

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