Biblio
The fingerprint sensor based on pMUTs was reported [1]. Spatial resolution of the image depends on the size of the acoustic source when a plane wave is used. If the size of the acoustic source is smaller, piezoelectric films with high dielectric constant are required. In this study, in order to obtain small acoustic source, we proposed Pb(Zrx Th-x)O3 (PZT) epitaxial transducers with high dielectric constant. PbTiO3 (PTO) epitaxial films were grown on conductive La-SrTiO3 (STO) substrate by RF magnetron sputtering. Longitudinal wave conversion loss of PTO transducers was measured by a network analyzer. The thermoplastic elastomer was used instead of real fingerprint. We confirmed that conversion loss of piezoelectric film/substrate structure was increased by contacting the elastomer due the change of reflection coefficient of the substrate bottom/elastomer interface. Minimum conversion loss images were obtained by mechanically scanning the soft probe on the transducer surface. We achieved the detection of the fingerprint phantom based on the elastomer in the GHz.
In this work, a measurement system is developed based on acoustic resonance which can be used for classification of materials. Basically, the inspection methods based on acoustic, utilized for containers screening in the field, identification of defective pills hold high significance in the fields of health, security and protection. However, such techniques are constrained by costly instrumentation, offline analysis and complexities identified with transducer holder physical coupling. So a simple, non-destructive and amazingly cost effective technique in view of acoustic resonance has been formulated here for quick data acquisition and analysis of acoustic signature of liquids for their constituent identification and classification. In this system, there are two ceramic coated piezoelectric transducers attached at both ends of V-shaped glass, one is act as transmitter and another as receiver. The transmitter generates sound with the help of white noise generator. The pick up transducer on another end of the V-shaped glass rod detects the transmitted signal. The recording is being done with arduino interfaced to computer. The FFTs of recorded signals are being analyzed and the resulted resonant frequency observed for water, water+salt and water+sugar are 4.8 KHz, 6.8 KHz and 3.2 KHz respectively. The different resonant frequency in case different sample is being observed which shows that the developed prototype model effectively classifying the materials.
Conventional photoacoustic microscopy (PAM) involves detection of optically induced thermo-elastic waves using ultrasound transducers. This approach requires acoustic coupling and the spatial resolution is limited by the focusing properties of the transducer. We present an all-optical PAM approach that involved detection of the photoacoustically induced surface displacements using an adaptive, two-wave mixing interferometer. The interferometer consisted of a 532-nm, CW laser and a Bismuth Silicon Oxide photorefractive crystal (PRC) that was 5×5×5 mm3. The laser beam was expanded to 3 mm and split into two paths, a reference beam that passed directly through the PRC and a signal beam that was focused at the surface through a 100-X, infinity-corrected objective and returned to the PRC. The PRC matched the wave front of the reference beam to that of the signal beam for optimal interference. The interference of the two beams produced optical-intensity modulations that were correlated with surface displacements. A GHz-bandwidth photoreceiver, a low-noise 20-dB amplifier, and a 12-bit digitizer were employed for time-resolved detection of the surface-displacement signals. In combination with a 5-ns, 532-nm pump laser, the interferometric probe was employed for imaging ink patterns, such as a fingerprint, on a glass slide. The signal beam was focused at a reflective cover slip that was separated from the fingerprint by 5 mm of acoustic-coupling gel. A 3×5 mm2 area of the coverslip was raster scanned with 100-μm steps and surface-displacement signals at each location were averaged 20 times. Image reconstruction based on time reversal of the PA-induced displacement signals produced the photoacoustic image of the ink patterns. The reconstructed image of the fingerprint was consistent with its photograph, which demonstrated the ability of our system to resolve micron-scaled features at a depth of 5 mm.