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 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.

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.

LiNbO₃ has been little studied for the piezoelectric energy harvesting applications. Although it is a cheap piezoelectric material without lead and toxic elements, it beneficiates of technological maturity in single crystal fabrication for optical and acoustic applications. In this Letter, we propose to investigate a (YXlt)/128°/90° LiNbO₃ cut as it offers a transverse piezoelectric coupling of k₂₃ = 0.49, which is comparable to that of commonly used PZT ceramics. A flexible beam of 65 mm length and a tip mass made of a LiNbO₃ thick film bonded on silicon were studied under 0.1 g sinusoidal acceleration. The beam presented an open-circuit resonance frequency of 105.9 Hz and a displacement up to 1.5 mm. In the frame of a single degree of freedom lumped model with a rectifying bridge, the electromechanical coupling of the device (k_m²), the figure of merit ${k_m}^{2}Q$ , and the normalized average power density were compared to both Pb-based and Pb-free current devices. The generated power density by our device was 965 μW/cm²/g², which is among the highest reported values compared to both Pb- and Pb-free vibrational harvesting devices.

The need for sustainable and long-term environmental monitoring has driven the development of energy-autonomous sensors, which either operate passively or integrate energy harvesting (EH) solutions. In many applications, the energy cost of data transmission is a critical factor in autonomous sensing systems. To address this challenge, optical passive sensors, which exploit changes in reflectivity to monitor physical parameters, offer self-sustained operation without requiring an external power source. Similarly, RF-based passive sensors, both chipless and with minimal circuitry, enable wireless monitoring with low power consumption. When more energy is available, EH techniques can be combined with active optical sensors. Infrared laser-based CO₂ sensors, as well as drone-mounted optical systems, demonstrate how EH can power precise environmental measurements. Beyond optics, other sensing modalities also benefit from EH, further expanding the range of self-powered environmental monitoring technologies. This review discusses the trade-offs between passive and EH-assisted sensing strategies, with a focus on optical implementations. The outlook highlights emerging solutions to enhance sensor autonomy while minimizing the energy cost of data transmission, paving the way for sustainable and scalable environmental monitoring.

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 $d_{33}$ 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.