EPJ B Highlight - Simulating better performance in piezoelectric energy harvesters

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Published on 21 October 2025

Analysis explains how nonlinear piezoelectric devices are far better than their linear counterparts at harvesting energy from noisy vibrations across a broad range of frequencies

Over the past few decades, the capabilities of piezoelectric energy harvesters have steadily improved, paving the way for micro- and nano-electronic devices which can be powered directly from the energy of ambient, noisy vibrations in their surrounding environments. So far, however, these devices have only been able to harvest from vibrations within a narrow frequency range, severely limiting their performance in real-world scenarios.

Through new analysis published in EPJ B, Martín Giuliano and Alejandro Sánchez at the National University of Mar del Plata, Argentina, show how this performance could be improved by integrating nonlinear dynamics into piezoelectric energy harvesters – allowing them to capture the inherently broad spectrum of frequencies associated with noisy vibrations. The duo’s findings could help guide the development of next-generation energy harvesters, making them far more autonomous than existing designs.

Traditionally, random vibrations are modelled using a Gaussian distribution, which predicts the probability of certain frequencies using a bell-shaped normal distribution curve, with the highest-probability frequencies at the centre. When distributed in this way, the energy contained in vibrations can be captured using linear piezoelectric harvesters, which respond most efficiently at a single resonant frequency.

In reality, random fluctuations mean that the frequencies of noisy vibrations will jump far from the centre of the distribution more often than a Gaussian curve would suggest. This behaviour can be described far more accurately using a Lévy distribution, now used to study the influence of random noise in scenarios ranging from pacemakers to aircraft wings.

Through their simulations, Giuliano and Sánchez show how the vibrations described by Lévy noise can be captured far more efficiently using nonlinear piezoelectric energy harvesters, which add a degree of complexity to the devices compared with their linear counterparts. With this approach, the devices could respond to a far greater proportion of frequencies predicted by the Lévy distribution.