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Record W1881362968 · doi:10.1063/1.4927238

Complementary split ring resonator arrays for electromagnetic energy harvesting

2015· article· en· W1881362968 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Physics Letters · 2015
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSplit-ring resonatorEnergy harvestingResonatorEnergy conversion efficiencyMetamaterialBandwidth (computing)Electrical impedanceOptoelectronicsMicrostripPower (physics)Materials sciencePhysicsOpticsTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

This work demonstrates the viability of Ground-backed Complementary Split-Ring Resonator (G-CSRR) arrays with significant power conversion efficiency and bandwidth enhancement in comparison to the technology used in current electromagnetic energy harvesting systems. Through numerical full-wave analysis, we demonstrated correlation between either the resonance frequency or the input impedance of G-CSRR cells with the periodicity of the array. A comparative study of power harvesting efficiency through numerical analysis and laboratory measurement was presented where an array of G-CSRRs is compared to an array of microstrip patch antennas. We demonstrated that a G-CSRR array yields power conversion efficiency of 92%, which represents a significant improvement in comparison to the single G-CSRR reported in our earlier work.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.454
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)0.0000.000

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 head0.019
GPT teacher head0.208
Teacher spread0.189 · 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