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Vibration energy harvesting based on piezoelectric transducers is an attractive choice to replace single-use batteries in powering Wireless Sensor Nodes (WSNs). As of today, their widespread application is hindered due to low operational bandwidth and the conventional use of lead-based materials. The Restriction of Hazardous Substances legislation (RoHS) implemented in the European Union restricts the use of lead-based piezoelectric materials in future electronic devices. This paper investigates lithium niobate (LiNbO3) as a lead-free material for a high-performance broadband Piezoelectric Energy Harvester (PEH). A single-clamped, cantilever beam-based piezoelectric microgenerator with a mechanical footprint of 1 cm2, working at a low resonant frequency of 200 Hz, with a high piezoelectric coupling coefficient and broad bandwidth, was designed and microfabricated, and its performance was evaluated. The PEH device, with an acceleration of 1 g delivers a maximum output RMS power of nearly 35 μW/cm2 and a peak voltage of 6 V for an optimal load resistance at resonance. Thanks to a high squared piezoelectric electro-mechanical coupling coefficient (k2), the device offers a broadband operating frequency range above 10% of the central frequency. The Mason electro-mechanical equivalent circuit was derived, and a SPICE model of the device was compared with experimental results. Finally, the output voltage of the harvester was rectified to provide a DC output stored on a capacitor, and it was regulated and used to power an IoT node at an acceleration of as low as 0.5 g.

In the ever-evolving landscape of modern agriculture, the integration of advanced technologies has become indispensable for optimizing crop management and ensuring sustainable food production. This paper presents the development and implementation of a real-time AI-assisted push-broom hyperspectral system for plant identification. The push-broom hyperspectral technique, coupled with artificial intelligence, offers unprecedented detail and accuracy in crop monitoring. This paper details the design and construction of the spectrometer, including optical assembly and system integration. The real-time acquisition and classification system, utilizing an embedded computing solution, is also described. The calibration and resolution analysis demonstrates the accuracy of the system in capturing spectral data. As a test, the system was applied to the classification of plant leaves. The AI algorithm based on neural networks allows for the continuous analysis of hyperspectral data relative up to 720 ground positions at 50 fps.

Poly(lactic) acid (PLA) is a bio-compatible polymer widely used in additive manufacturing, and in the form of cellular foam it shows excellent mechanical and piezoelectric properties. This type of structure can be easily 3D-printed by Fusion Deposition Modelling (FDM) with commercially available composite filaments. In this work, we present mechanical and electrical investigations on 3D-printed low-cost and eco-friendly foamed PLA. The cellular microstructure and the foaming degree were tuned by varying extrusion temperature and flowrate. The maximum surface potential and charge stability of disk samples were found in correspondence of extrusion temperature between 230 and 240 °C with a flowrate of 53–44% when charging on a heated bed at 85 °C. The cells’ morphology and correlated mechanical properties were analyzed and the measured piezoelectric d33 coefficient was found to be 212 pC/N. These findings show the importance of printing parameters and thermal treatment during the charging process in order to obtain the highest charge storage, stability and material flexibility. These results suggest that 3D-printed cellular PLA is a promising sustainable material for sensing and energy-harvesting applications.

Summary: This paper addresses the design optimization process of an energy harvesting device for scavenging energy from an e-gadget, utilizing its ”rocking” motion. The plucking mechanism inspired by the frequency up-conversion technique provides initial displacement exciting piezoelectric beams and increases the total number of excitations multiple times. The harvester is designed in conjunction with the multidimensional surrogate optimization algorithm to maximize the device’s performance considering the geometrical features of the concept and the constrained operating environment. The established numerical model is validated first using a set of experimental data. The obtained numerical results demonstrate that the developed 10.2″ size device produces 55 mJ in half-period when inclined at 45°, which is equivalent to generating 0.3 W. Considering that an iPad of the same size consumes around 3 W, the proposed energy harvester is capable of extending its battery life by 10%.

The huge number of electronic devices called the Internet of Things requires miniaturized, autonomous and ecologically sustainable power sources. A viable way to power these devices is by converting mechanical energy into electrical through electro-active materials. The most promising and widely used electro-active materials for mechanical energy harvesting are piezoelectric materials, where the main one used are toxic or not biocompatible. In this work, we focus our attention on biocompatible and sustainable piezoelectric materials for energy harvesting. The aim of this work is to facilitate and expedite the effort of selecting the best piezoelectric material for a specific mechanical energy harvesting application by comprehensively reviewing and presenting the latest progress in the field. We also identify and discuss the characteristic property of each material for each class to which the material belong to, in terms of piezoelectric constants and achievable power.

In this paper, we present integrated lead-free energy converters based on a suitable MEMS fabrication process with an embedded layer of LiNbO3. The fabrication technology has been developed to realize micromachined self-generating transducers to convert kinetic energy into electrical energy. The process proposed presents several interesting features with the possibility of realizing smaller scale devices, integrated systems, miniaturized mechanical and electromechanical sensors, and transducers with an active layer used as the main conversion element. When the system is fabricated in the typical cantilever configuration, it can produce a peak-to-peak open-circuit output voltage of 0.208 V, due to flexural deformation, and a power density of 1.9 nW·mm−3·g−2 at resonance, with values of acceleration and frequency of 2.4 g and 4096 Hz, respectively. The electromechanical transduction capability is exploited for sensing and power generation/energy harvesting applications. Theoretical considerations, simulations, numerical analyses, and experiments are presented to show the proposed LiNbO3-based MEMS fabrication process suitability. This paper presents substantial contributions to the state-of-the-art, proposing an integral solution regarding the design, modelling, simulation, realization, and characterization of a novel transducer.

Wireless sensor nodes (WSNs) are the fundamental part of an Internet of Things (IoT) system for detecting and transmitting data to a master node for processing. Several research studies reveal that one of the disadvantages of conventional, battery-powered WSNs, however, is that they typically require periodic maintenance. This paper aims to contribute to existing research studies on this issue by exploring a new energy-autonomous and battery-free WSN concept for monitor vibrations. The node is self-powered from the conversion of ambient mechanical vibration energy into electrical energy through a piezoelectric transducer implemented with lead-free lithium niobate piezoelectric material to also explore solutions that go towards a greener and more sustainable IoT. Instead of implementing any particular sensors, the vibration measurement system exploits the proportionality between the mechanical power generated by a piezoelectric transducer and the time taken to store it as electrical energy in a capacitor. This helps reduce the component count with respect to conventional WSNs, as well as energy consumption and production costs, while optimizing the overall node size and weight. The readout is therefore a function of the time it takes for the energy storage capacitor to charge between two constant voltage levels. The result of this work is a system that includes a specially designed lead-free piezoelectric vibrational transducer and a battery-less sensor platform with Bluetooth low energy (BLE) connectivity. The system can harvest energy in the acceleration range [0.5 g–1.2 g] and measure vibrations with a limit of detection (LoD) of 0.6 g.