2020
DOI: 10.1016/j.ijmecsci.2020.105670
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Designing a phononic crystal with a defect for energy localization and harvesting: Supercell size and defect location

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Cited by 98 publications
(30 citation statements)
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“…Note that among the five defect mode shapes, we focus on the certain defect band frequency of 59.65 kHz because the out-of-plane monopole-like defect mode shape at this frequency, as shown in Additional file 1: Fig. S4, was found to be most advantageous for minimizing voltage cancellation [58,59] when incorporating defect modes of phononic crystals into energy harvesting applications, as addressed in previous studies [39,40,51,60].…”
Section: Resultsmentioning
confidence: 99%
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“…Note that among the five defect mode shapes, we focus on the certain defect band frequency of 59.65 kHz because the out-of-plane monopole-like defect mode shape at this frequency, as shown in Additional file 1: Fig. S4, was found to be most advantageous for minimizing voltage cancellation [58,59] when incorporating defect modes of phononic crystals into energy harvesting applications, as addressed in previous studies [39,40,51,60].…”
Section: Resultsmentioning
confidence: 99%
“…When a single defect is created in a phononic crystal by locally breaking the periodicity of unit cells, such as by replacing a unit cell with another structure having different material or geometry, flat passbands (i.e., defect bands) are generated within a phononic band gap [37,38]. When acoustic or elastic waves are generated in a phononic crystal system near a defect band frequency, they can become localized inside the defect while representing a certain defect mode shape [39,40]. Defect-mode-enabled energy localization has proven highly desirable for several potential applications, such as energy harvesting [20,41], wave filtering [42,43], and sensors [44,45].…”
Section: Introductionmentioning
confidence: 99%
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“…These SNs are mostly deployed in external environments, which motivates the use of energy harvesting [ 106 , 107 ]. In this context, a few energy harvesting techniques for the prolonging of network lifetime have been presented in the literature [ 108 , 109 , 110 , 111 ]. Furthermore, machine learning (ML) algorithms integrated with energy harvesting technology are also candidates for improving network lifetime and performance by predicting the amount of energy to be harvested from ambient in a specific duty cycle [ 112 , 113 ].…”
Section: Future Directionsmentioning
confidence: 99%
“…The acoustic energy is localized in the unit cell due to the reverse vibration of the matrix as well as the local resonator and finally the BG is opened in the low frequency range. By combining the BG characteristics and defect state characteristics of PnCs or introducing functional materials and designing special structures, etc., PnCs can have a wider application prospect in acoustic device design and acoustic signal processing, such as the optimization of acoustic device design including sound insulation and vibration reduction structure 14 , acoustic waveguide 15 as well as acoustic filter 16 and improvement of acoustic collimation 17 , acoustic focusing 18 , 19 , acoustic energy recovery 20 , 21 as well as other technologies.…”
Section: Introductionmentioning
confidence: 99%