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Sensitivity-Enhanced CSRR-Loaded SIW Chipless Tag for Real-Time Coating Assessment on Medical Implants

2024· article· en· W4402978338 on OpenAlexaff
Amirhossein Yazdanicherati, Maryam Badv, Zahra Abbasi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCoatingSensitivity (control systems)Materials scienceOptoelectronicsComputer scienceElectronic engineeringNanotechnologyEngineering

Abstract

fetched live from OpenAlex

In this study, a new chipless Complementary Split-ring Resonators (CSRR) loaded Substrate Integrated Waveguide (SIW) tag is coupled with a coplanar antenna for real-time sensing and detection. This sensor was created for real-time monitoring of lubricant evaporation on surfaces that have been infused with lubricant. The stability of the lubricating layer is a crucial determinant for the efficient operation of these coatings. The proposed sensor consists of an ultrawide-band antenna as a reader to couple power to the CSSR-loaded SIW sensing tag. The sensor design and operation have been carefully confirmed using both simulation and measurements, confirming its capacity to detect lubricant evaporation with high sensitivity. With 0.1 MHz frequency shift in resonance frequency per 1 µL of lubricant, this sensor stands as a significant advancement in the field of medical implant technology, offering a real-time solution for ensuring the effectiveness of lubricant-infused coatings since their assessment is necessary to minimize complications associated with medical implants, such as the non-specific adhesion of blood components and bacteria.

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 categoriesInsufficient payload (model declined to judge)
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 score0.148
Threshold uncertainty score1.000

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)0.0010.000

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 head0.013
GPT teacher head0.276
Teacher spread0.263 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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