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Dual-Band Multilayer Energy Harvesting Surface

2020· article· en· W3131379209 on OpenAlexaff
Ahmed Z. Ashoor, Omar M. Ramahi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversity of WaterlooCarleton University
Fundersnot available
KeywordsEnergy harvestingMulti-band deviceRectificationRectennaFrequency bandDipoleOptoelectronicsPolarization (electrochemistry)Energy (signal processing)Electronic engineeringElectrical engineeringMaterials sciencePhysicsComputer scienceVoltageEngineeringBandwidth (computing)Telecommunications

Abstract

fetched live from OpenAlex

An efficient dual-band energy harvesting surface (EHS) array is presented using two stacked-layer of cross-dipole elements for efficient harvesting at two frequency bands for multiple polarizations. The proposed EHS array introduces the concept of stacked surfaces that can be directly integrated and matched with rectification circuitries. Each layer of the EHS array is dedicated to harvesting at a particular frequency band with its own directly matched rectifying circuity allowing better AC to DC matching and harvesting efficiency at each frequency band. The simulation results of the dual-band EHS energy harvesting array show overall radiation to AC harvesting efficiencies of 95% and 93%, respectively, at various polarization angles at the desired operating frequencies of 2.7 GHz and 3.4 GHz.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.183
Teacher spread0.166 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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