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Integrated Microwave and Mechanical Energy Harvesting Based on a Metasurface Perfect Absorber Incorporating Piezoelectric Material

2025· article· W4417131993 on OpenAlexaff
Mahsa Zabetiakmal, Güneş Karabulut Kurt, Mohammad S. Sharawi, Elham Baladi

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsEnergy harvestingMiniaturizationPiezoelectricityResonatorMicrowaveVoltageAbsorption (acoustics)Vibration

Abstract

fetched live from OpenAlex

This study introduces a novel metasurface perfect absorber (MPA) designed for simultaneous RF and vibration energy harvesting, representing a significant advancement in the development of sustainable power sources. The proposed structure combines two energy harvesting methods—radiofrequency (RF) and vibration—by utilizing a piezoelectric substrate within the metasurface design. The metasurface elements act as electrodes for the piezoelectric harvester, collecting the voltage generated by vibrations, while the entire structure operates as a cantilever, a well-known mechanical resonator for vibration energy harvesting. The interdigitated shape of the metasurface elements increases the total capacitance, while the high-dielectric-constant piezoelectric material enables miniaturization of the metasurface elements, lowering the absorption frequency and achieving an absorption efficiency of over 96%. The design not only presents polarization-insensitive RF energy harvesting across various incident angles, but also enhances the efficiency through hybridization of two ambient sources. This innovative approach positions the proposed metasurface as a sustainable and versatile hybrid energy harvester with considerable potential for real-world impact.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.516
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.216
Teacher spread0.205 · 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 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
Published2025
Admission routes1
Has abstractyes

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