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Record W2783381685 · doi:10.1002/pssr.201870403

Surface State‐Induced Anomalous Negative Thermal Quenching of Multiferroic BiFeO<sub>3</sub> Nanowires (Phys. Status Solidi RRL 1/2018)

2018· article· en· W2783381685 on OpenAlexaff
K. Prashanthi, Željka Antić, Garima Thakur, Miroslav D. Dramićanin, Thomas Thundat

Bibliographic record

Venuephysica status solidi (RRL) - Rapid Research Letters · 2018
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Thermoelectric Materials and Devices
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceNanowireQuenching (fluorescence)SemiconductorMultiferroicsCondensed matter physicsSurface statesNanotechnologyBand gapLuminescenceOptoelectronicsSurface (topology)FluorescenceFerroelectricityOpticsPhysicsDielectric

Abstract

fetched live from OpenAlex

The multiferroic wide-bandgap semiconductor material BiFeO3 (BFO) has attracted intense research interests due to its multifunctional properties and broad range of potential applications in optoelectronic devices. However, in onedimensional BFO nanostructures, because of the high surfaceto- volume ratio, surface states play a crucial role in their optical and electrical properties offering extraordinary functionalities. In their Letter (article no. 1700352), Kovur Prashanthi and coworkers report surface state induced anomalous negative thermal quenching of semiconductor BFO nanowires. The BFO nanowires show a rare phenomenon of negative thermal quenching (NTQ) of emission, where the emission intensity of certain peaks shows an increase as a function of temperature instead of the routinely observed decrease in luminescence intensity. A possible mechanism for the observed NTQ behaviour is proposed using electron trapping and de-trapping at higher temperatures. The authors' studies reveal that the defect emission behaviour of the nanowires is due to the presence of localized surface states in the band gap caused by the oxygen vacancies. This phenomenon has neither been observed in thin-film nor in bulk BiFeO3. Therefore, this effect is enhanced in the nanowires because of their high surface-to-volume ratio.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.039
GPT teacher head0.318
Teacher spread0.279 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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