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A Performance Analysis of Schottky Diode to support RF Energy Harvesting

2019· article· en· W2982598450 on OpenAlexaff
Alex Mouapi, Nadir Hakem, Nahi Kandil

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsRectennaSchottky diodeRectifier (neural networks)DiodeElectrical engineeringEnergy conversion efficiencyPrecision rectifierUSableOptoelectronicsRadio frequencyVoltageElectronic engineeringElectronic circuitMaterials scienceComputer scienceEngineeringPower factorRectification

Abstract

fetched live from OpenAlex

Given the low density of the surrounding RF powers, the rectifying stage is the one on which the designers of the rectenna (rectifying antenna) carry the most attention. Rectifier circuits must be of high efficiency to have usable DC output powers. Since the conversion efficiency is directly related to the electrical parameters of the used rectifying diode, this paper proposes a comparative study of the RF/DC conversion efficiency of an RF rectifier for the commonly considered Schottky diodes. In addition to the electrical parameters of the used diode, the operating frequency, as well as the desired level of DC output voltage, are considered in the comparison. Five diodes manufactured by AVAGO (HSMS 2820, HSMS 2850, HSMS 2860) and two Skyworks diodes (SMS 7621 and SMS 7630) are treated in this paper. This study will then provide designers with useful information in the selection of the rectifier diode and associated design parameters.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.198
Teacher spread0.190 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations13
Published2019
Admission routes1
Has abstractyes

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