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Record W1992281869 · doi:10.1063/1.4885776

Electrically small particles combining even- and odd-mode currents for microwave energy harvesting

2014· article· en· W1992281869 on OpenAlexaff
Mohammed R. AlShareef, Omar M. Ramahi

Bibliographic record

VenueApplied Physics Letters · 2014
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversity of Waterloo
FundersKing Abdulaziz City for Science and Technology
KeywordsMicrowaveEnergy harvestingResonatorMaterials scienceSplit-ring resonatorSubstrate (aquarium)OptoelectronicsDielectricEnergy conversion efficiencyEnergy (signal processing)PhysicsTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

We present a structure composed of an ensemble of electrically small resonators for harvesting microwave energy. A flower-like structure composed of four electrically small split-ring resonators (SRRs) arranged in a cruciate pattern, each with a maximum dimension of less than λo/10, is shown to achieve more than 43% microwave-to-alternating current conversion efficiency at 5.67 GHz. Even- and odd-mode currents are realized in the proposed harvester to improve the efficiency and concurrently reduce the dielectric loss in the substrate. An experimental validation is conducted to prove the harvesting capability.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.492
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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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 designSimulation or modeling
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

Citations20
Published2014
Admission routes1
Has abstractyes

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