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Record W2070008786 · doi:10.1002/mop.22657

Tunable (Ba, Sr)TiO<sub>3</sub> interdigital capacitor onto Si wafer for reconfigurable radio

2007· article· en· W2070008786 on OpenAlexaff
Ki‐Byoung Kim, Tae‐Soon Yun, Jong‐Chul Lee, Mohamed Chaker, Ke Wu

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor materials and interfaces
Canadian institutionsInstitut National de la Recherche ScientifiquePolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceWaferSubstrate (aquarium)Layer (electronics)MicrowaveCapacitorOptoelectronicsSiliconNanotechnologyElectrical engineeringTelecommunications

Abstract

fetched live from OpenAlex

Abstract In this article, the potential feasibility of integrating BST films into Si wafer by adopting tunable interdigital capacitor (IDC) with TiO 2 thin film buffer layer is suggested. TiO 2 as buffer layer is grown onto Si substrate by atomic layer deposition and the coplanar IDC on Ba x Sr 1−x TiO 3 (500 nm)/TiO 2 (50 nm)/high resistivity Si (HR‐Si) is fabricated. BST interdigital tunable capacitors integrated on HR‐Si substrate with high tunability and low loss tangent are characterized for their microwave performances. BST/HR‐Si and BST/TiO 2 /HR‐Si IDCs show much enhanced tunability values of 31% and 40%, respectively as compared to the value of 21% obtained with BST film on MgO single crystal substrate at the bias of 5 kV/cm. BST/TiO 2 /HR‐Si structure shows much improved figure of merit of 504.4 as compared to 418.53 and 101.68 of BST/MgO and BST/HR‐Si structure, respectively. © 2007 Wiley Periodicals, Inc. Microwave Opt Technol Lett 49: 2144–2148, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.22657

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 score0.014
Threshold uncertainty score0.954

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 head0.009
GPT teacher head0.217
Teacher spread0.208 · 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

Citations2
Published2007
Admission routes1
Has abstractyes

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