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By combining the rigidity of inorganic components with the flexibility of organic components, molecule-based ferroelectrics emerge as promising candidates for flexible, self-powered piezoelectric sensors. While it is well known that the performance of piezoelectric sensor devices depends not only on the materials' piezoelectric properties but also on the device architecture, research into enhancing molecule-based piezoelectric sensor performance through microstructure optimization has never been investigated. Here, we report the synthesis of a molecule-based ferroelectric, [(2-bromoethyl) trimethylammonium][GaBr] ([(CH)NCHCHBr][GaBr]) (1), which exhibits a piezoelectric coefficient ( ) of up to 331 pC N. Our investigation reveals that the power density of a composite piezoelectric sensor device made from 1@S-PDMS(800#) (with microstructures) is twelve times that of 1-Flat-PDMS (without microstructures), due to a synergistic combination of piezoelectric and triboelectric effects. Interestingly, this flexible piezoelectric sensor can effectively detect human physiological signals, such as finger bending, breathing, and speech recognition, without the need for an external power supply.
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http://dx.doi.org/10.1039/d4sc05442c | DOI Listing |
Prog Mol Biol Transl Sci
September 2025
Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada. Electronic address:
Monitoring skeletal muscle contraction provides valuable information about the muscle mechanical properties, which can be helpful in various biomedical applications. This chapter presents a single-element flexible and wearable ultrasonic sensor (WUS) developed by our research group and its application for continuously monitoring and characterizing skeletal muscle contraction. The WUS is made from a 110-µm thick polyvinylidene fluoride piezoelectric polymer film.
View Article and Find Full Text PDFIEEE Trans Biomed Eng
September 2025
Objective: Transcranial ultrasound (US) stimulation (TUS) has emerged as a promising technique for minimally invasive, localized, deep brain stimulation. However, indirect auditory effects during neuromodulation require careful consideration, particularly in experiments with rodents. One method to prevent auditory responses involves applying tapered envelopes to US bursts.
View Article and Find Full Text PDFACS Appl Mater Interfaces
September 2025
Core Manufacturing Technology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba Central 5, 1-1-1 Higashi, Tsukuba, Ibaraki 305-8565, Japan.
The direct deposition of piezoelectric ceramic thin films onto metal foils has become a significant challenge due to the increasing demand for embedded decoupling capacitors, nanogenerators, and flexible piezo-sensors. However, traditional thermal sintering (TS) methods present several issues for metal foils, including alterations in mechanical properties, the formation of wrinkles, and the need for precise control over the sintering atmosphere to prevent oxidation. In this study, we successfully crystallized BaTiO on a Ni foil under atmospheric conditions, mitigating thermal damage to the foil through a hybrid-solution-incorporated photoassisted chemical solution deposition (HS-PCSD) method.
View Article and Find Full Text PDFAdv Sci (Weinh)
September 2025
State Key Laboratory of Powder Metallurgy, Central South University, Changsha, 410083, China.
Digital light processing (DLP) presents a promising approach for fabricating intricately designed piezoelectric components, which are essential for developing high-sensitivity piezoelectric sensor systems. However, the inherent layer-by-layer stacking nature of DLP induces interlayer cracking in printed ceramics, which severely deteriorates their performance. This work introduces an innovative interfacial engineering strategy to print superlattice components with exceptional piezoelectric performance.
View Article and Find Full Text PDFComput Methods Programs Biomed
August 2025
School of Electronic Science and Engineering (School of Microelectronics), South China Normal University, Foshan, 528225, China. Electronic address:
Background And Objectives: Ballistocardiography (BCG) has emerged as a promising modality for home-based heart failure (HF) monitoring, yet existing single-dimensional manual feature analyses fail to adequately characterize left ventricular ejection fraction (LVEF < 40%) dynamics. We address this limitation by developing a hybrid feature fusion framework that synergizes manual feature engineering with deep learning for improved HF diagnosis and LVEF classification.
Methods: 83 participants were recruited from a hospital, with their samples categorized into two (healthy and HF) and three classes (healthy, LVEF ≥ 40% HF, and LVEF < 40% HF) based on clinical diagnosis.