4.7 Article

Characterization of hybrid piezoelectric nanogenerators through asymptotic homogenization

Journal

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
Volume 355, Issue -, Pages 1148-1186

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.cma.2019.06.040

Keywords

Energy scavenging; Hybrid piezoelectric nanodevices; ZnO nanorods; Periodic microstructure; Multi-field homogenization; Bloch wave propagation

Funding

  1. Regione Puglia under the Future in Research Program Development of next generation NEMS for energy harvesting [NSUX1F1]
  2. National Group of Mathematical Physics (GNFM-INdAM)
  3. Ministry of Education, Universities and Research, through the PRIN 2015 funding scheme [2015JW9NJT]

Ask authors/readers for more resources

In the framework of energy scavenging for applications in flexible/stretchable electronics, hybrid piezoelectric nanogenerators are investigated. They are made up with zinc oxide (ZnO) nanorods, embedded in a polymeric matrix, and grown on a flexible polymeric support. The ZnO nanorods are arranged in clusters, forming nearly regular distributions, so that periodic topologies can be realistically assumed. Focus is on a dynamic multi-field asymptotic homogenization approach, proposed to grasp the overall constitutive behaviour of such complex microstructures. A set of applications, both in static and dynamic regime, is proposed to explore different design paradigms, related to nanogenerators based on three working principles. Both extension and bending nanogenerators are, indeed, analysed, considering either extension along the nanorods axis, or orthogonally to it. The study of the wave propagation is, also, exploited to comprehend the main features of such piezoelectric devices in the dynamic regime. (C) 2019 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available