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Record W4206415496 · doi:10.1109/mwsym.2010.5515965

Battery-free RFID-enabled wireless sensors

2010· article· en· W4206415496 on OpenAlexaff
Li Yang, Giulia Orecchini, George Shaker, Ho-Seon Lee, Manos M. Tentzeris

Bibliographic record

Venue2010 IEEE MTT-S International Microwave Symposium · 2010
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsWirelessUltra high frequencyMaterials scienceSubstrate (aquarium)Realization (probability)Computer scienceCarbon nanotubeElectrical engineeringNanotechnologyTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

This paper introduces the realization of batter-free RFID-enable wireless sensors by integrating conformal RFID antennas with inkjet-printed carbon nanotubes (CNT) composites in a chipless RFID fashion for gas detection. The whole module is realized by inkjet printing on a low-cost paper-based substrate and the RFID tag is designed for the European UHF RFID band. The electrical conductivity of the CNT film changes in the presence of very small quantities of gases like ammonia, methanol, ethanol, acetone and nitrogen oxide (NOx), resulting in the variation of the backscattered power level which can be easily detected by the RFID reader to realize reliable wireless toxic gas sensing. The electrical performance characterization of the inkjet-printed CNT film is also reported in the UHF band.

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: none
Teacher disagreement score0.002
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 communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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

Citations15
Published2010
Admission routes1
Has abstractyes

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