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Record W2005463398 · doi:10.1116/1.2162561

On-chip inductors incorporating porous-Si and intrinsic-amorphous-Si films for rf integrated circuits

2006· article· en· W2005463398 on OpenAlexaff
Stella Chang, Siva Sivoththaman

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2006
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceInductorOptoelectronicsSubstrate (aquarium)Amorphous solidSiliconEquivalent series resistanceElectrical resistivity and conductivityElectronic circuitElectrical engineeringChemistry

Abstract

fetched live from OpenAlex

The quality factor (Q) of inductors on silicon (Si) is limited by the series resistance of the metal at low frequency and by the substrate resistivity at high frequency. Oxide is generally used to isolate the useful signal of the inductor from the lossy Si substrate. However, stoichiometric silica (SiO2) is processed at high temperature which restricts the possibility of post-complementary metal-oxide semiconductor integration, and due to the large thermal mismatch with Si, thick oxide films introduce considerable stress. In this work, we apply electrochemically formed porous Si (PS) and intrinsic amorphous Si (i-a-Si:H) deposited at low temperature (250°C) in an approach asan isolation bilayer for planar inductors on Si for rf integrated circuits. An improvement of morethan 45% in Q was measured at a frequency of 6.4GHz for 1.6nH inductor incorporating PS andi-a-Si:H films. The experimental results presented indicate that these low-temperature materials are promising for the isolation of rf devices on low-resistivity Si.

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 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 score0.091
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.222
Teacher spread0.211 · 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

Citations3
Published2006
Admission routes1
Has abstractyes

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