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Record W2069012346 · doi:10.1103/physrevb.82.214109

Doping and temperature-dependent optical properties of oxygen-reduced<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mtext>BaTiO</mml:mtext></mml:mrow><mml:mrow><mml:mn>3</mml:mn><mml:mo>−</mml:mo><mml:mi>δ</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math>

2010· article· lv· W2069012346 on OpenAlexaff
Jungseek Hwang, Taras Kolodiazhnyi, Jerry Zhijian Yang, Martin Couillard

Bibliographic record

VenuePhysical Review B · 2010
Typearticle
Languagelv
FieldMaterials Science
TopicElectronic and Structural Properties of Oxides
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDopingMaterials sciencePhononOxygenPhase (matter)Analytical Chemistry (journal)PhysicsCondensed matter physicsCrystallographyChemistry

Abstract

fetched live from OpenAlex

We report on optical properties of reduced ${\text{BaTiO}}_{3\ensuremath{-}\ensuremath{\delta}}$ at different doping levels including insulating and metallic samples. In all the samples, including metallic one, we observe structural phase transitions from the changes in the infrared-active phonon modes. Metallic ground state is confirmed by the Drude-type low-frequency optical reflectance. Similar to ${\text{SrTiO}}_{3\ensuremath{-}\ensuremath{\delta}}$ we find that the midinfrared-absorption band in ${\text{BaTiO}}_{3\ensuremath{-}\ensuremath{\delta}}$ appears and grows with an increase in the oxygen-vacancy concentration. Upon decrease in temperature from 300 K, the midinfrared band shifts slightly to higher frequency and evolves into two bands: the existing band and a new and smaller band at lower frequency. The appearance of the new and smaller band seems to be correlated with the structural phase transitions.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.019
GPT teacher head0.251
Teacher spread0.232 · 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 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

Citations54
Published2010
Admission routes1
Has abstractyes

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Same venuePhysical Review BSame topicElectronic and Structural Properties of OxidesFrench-language works237,207