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Record W2562949325 · doi:10.1088/1361-6463/50/3/035103

Transport of electrons in lead oxide studied by CELIV technique

2016· article· en· W2562949325 on OpenAlexafffund
Oleksii Semeniuk, G. Juška, J. O. Oelerich, K. Jandieri, S. D. Baranovskiǐ, A. Reznik

Bibliographic record

VenueJournal of Physics D Applied Physics · 2016
Typearticle
Languageen
FieldMaterials Science
TopicTransition Metal Oxide Nanomaterials
Canadian institutionsLakehead UniversityThunder Bay Regional Research Institute
FundersCanadian Institutes of Health ResearchLietuvos Mokslo Taryba
KeywordsLead (geology)ElectronMaterials scienceOxideLead oxideCondensed matter physicsPhysicsGeologyMetallurgyNuclear physics

Abstract

fetched live from OpenAlex

Abstract Although polycrystalline lead oxide (PbO) has a long history of application in optoelectronics and imaging, the transport mechanism for electrons in this material has not yet been clarified. Using the photo-generated charge extraction by linear increasing voltage (photo-CELIV) technique, we provide the temperature- and field-dependences of electron mobility in poly-PbO. It is found that electrons undergo dispersive transport, i.e. their mobility decreases in the course of time. Multiple trapping of electrons from the conduction band into the developed band tail is revealed as the dominant transport mechanism. This differs dramatically from the dispersive transport of holes in the same material, dominated by topological factors and not by 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)0.001
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 score0.088
Threshold uncertainty score0.750

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.233
Teacher spread0.222 · 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

Citations13
Published2016
Admission routes2
Has abstractyes

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