Acousto-Electric Conversion by the Piezoelectric Nanogenerator of a Molecular Copper(II) Complex

The conversion of sound waves into electrical energy holds immense potential in various real-life applications, particularly biomedical devices, smart security sensors, and noise pollution detectors. Yet, the field is largely underexplored, due to the limited availability of materials that operate efficiently at low frequencies of sound waves. Piezoelectric nanogenerators (PENGs), which generate electric charges through deformations caused by sound-induced pressure variations, emerge as promising candidates for acoustoelectric conversion. However, the rigidity and toxicity, of traditional piezoelectric bulk oxide-based PENGs make them unsuitable for wearable electronics and healthcare monitoring devices. As an alternative, we present an efficient, flexible PENG and acoustic nanogenerator (AcNG) based on a molecular ferroelectric [Cu₂(L-phe)₂(bpy)₂(H₂O)] (BF₄)₂.2H₂O (1) complex with an impressive output peak-to-peak voltage of 4.94 V and an acoustoelectric conversion of 40 mV from 60 Hz soundwave is disclosed. Leveraging the sensitive low-frequency detection limit of this AcNG combined with a Machine Learning (ML) approach, voices can be distinguished with a surprising accuracy of 95%. Additionally, these devices enable rapid capacitor charging (within 10 s), highly sensitive pressure sensing (low as 4 kPa), and detecting human physiological motion, holding promise for their applications in biometric voice recognition, enhanced national security (AI-driven voice-recognition), and biomedical diagnostics.