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Record W4403390273 · doi:10.1109/jsen.2024.3476431

A Feasibility Examination Using Microwave Stripline Resonators for Low-Temperature Sensing

2024· article· en· W4403390273 on OpenAlexaff
Brent Leier, Rashid Mirzavand, Masoud Baghelani, Ashwin K. Iyer

Bibliographic record

VenueIEEE Sensors Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsStriplineResonatorMicrowaveMaterials scienceAcousticsElectronic engineeringOptoelectronicsTemperature measurementElectrical engineeringEngineeringTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

A stripline transmission-line-based temperature sensor is designed and fabricated for examination of use in low-temperature environments. A custom-built chassis encloses the stripline, shielding the low-temperature sensor from environmental disturbances such as frost and condensation, which would otherwise disrupt temperature measurement. The base resonator geometry is a 6.05-mm ring, modified with a split and transmission lines (TLs) extended inward to operate at frequencies between 910 and 927 MHz over temperatures from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$- 70~^{\circ }$ </tex-math></inline-formula>C to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10~^{\circ }$ </tex-math></inline-formula>C. The one-port sensor exploits the thermal coefficient of dielectric constant (TCD) of −459 ppm/°C of a commercial dielectric substrate. As temperature changes, so does the dielectric constant of the substrate, correlating to a shift in resonant frequency. A series of thermal cycling and stability experiments demonstrate repeatable and stable resonant frequency and temperature measurements. Several independent temperature step experiments between <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$- 70~^{\circ }$ </tex-math></inline-formula>C and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10~^{\circ }$ </tex-math></inline-formula>C are performed, resulting in a repeatable linear sensitivity of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\approx ~199$ </tex-math></inline-formula> kHz/°C. The results confirm the feasibility of using microwave (MW) stripline resonant sensors on commercial substrates for low-temperature sensing.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.525
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.259
Teacher spread0.238 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

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