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Record W2922366618 · doi:10.1109/jsen.2019.2904025

Nonlinear Multi-Mode Wideband Piezoelectric MEMS Vibration Energy Harvester

2019· article· en· W2922366618 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Sensors Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of NewfoundlandResearch and Development Corporation of Newfoundland and LabradorCanada Foundation for InnovationCMC Microsystems
KeywordsBandwidth (computing)Nonlinear systemEnergy harvestingWidebandMicroelectromechanical systemsPiezoelectricityVoltageVibrationProof massPower densityComputer sciencePhysicsElectrical engineeringAcousticsElectronic engineeringEnergy (signal processing)Power (physics)EngineeringOptoelectronicsTelecommunications

Abstract

fetched live from OpenAlex

The conventional micro-electromechanical system (MEMS) energy harvesters can only generate voltage disadvantageously in a narrow bandwidth at higher frequencies. In this paper, we propose a piezoelectric MEMS harvester with the capability of vibrating in multi-degrees-of-freedom, whose operational bandwidth is enhanced by taking the advantage of both the multimodal and nonlinear mechanisms. The proposed harvester has a symmetric structure with a doubly-clamped configuration enclosing three proof masses in distinct locations. Thanks to the uniform mass distribution, the energy harvesting efficiency can be considerably enhanced. To determine the optimum geometry for the preferred nonlinear behavior, we propose an automated design and optimization methodology based on the genetic algorithm (GA). By using the micromachining process, our optimized harvester with a total volume of 4.1 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> has been fabricated and measured. The prototype measurements demonstrate that our proposed piezoelectric MEMS harvester is able to generate voltage with a frequency bandwidth of 59 Hz, ranging from 227 to 286 Hz. When the device operates at its second-mode resonant frequency, the nonlinear behavior can be obtained with an extremely small magnitude of the base excitation (i.e., 0.2 m/s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ). Its normalized power density (NPD) of 595.12 (μW·cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> ·m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> ·s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> ) is found to be superior to any previously reported wideband aluminum nitride (AlN) piezoelectric MEMS harvesters in the literature.

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 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 score0.137
Threshold uncertainty score0.923

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.232
Teacher spread0.218 · 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