Effects of Composition Segregation in PMN-PT Crystals on Ultrasound Transducer Performance.

This study investigates the relationship between the composition segregation in lead magnesium niobate-lead titanate (PMN-PT; PMN-29%PT, PMN-29.5%PT, PMN-30%PT, PMN-30.5%PT, and PMN-31%PT) single crystals within morphotropic phase boundary (MPB) and the corresponding ultrasonic transducer performance through PiezoCAD modeling and real transducer testing. For five crystals with compositions distributed across the main body of a crystal ingot, the piezoelectric coefficient and free relative permittivity values were measured to vary by over 30%, whereas the transducer bandwidth and center frequency values were modeled to change by less than 10%. For the single-element ultrasonic transducers fabricated using those crystals without matching layers, the variations of -6-dB bandwidth, insertion loss, receiver-free field voltage response, and center frequency were measured to be 9.61%, -15.23%, 9.76%, and 1.41%, respectively, confirming the modeling results. Using the Mason and Krimholtz, Leedom, and Matthaei (KLM) models, it is found that the relatively stable transducer performance can be attributed to the relatively consistent electromechanical coupling coefficient, acoustic impedance, and clamped relative permittivity originated from the stable elastic compliance properties among the crystals of various compositions. It is expected that the relatively stable performance could be extended to multielement transducers with matching layers for the same contributing mechanisms. Our results suggest that it is possible to use crystal plates of different compositions within the MPB region, obtained from one and the same ingot, to fabricate a batch of ultrasonic transducers that will exhibit a similar performance, significantly reducing the cost of materials.

High-speed, sparse-sampling three-dimensional photoacoustic computed tomography in vivo based on principal component analysis.

Photoacoustic computed tomography (PACT) has emerged as a unique and promising technology for multiscale biomedical imaging. To fully realize its potential for various preclinical and clinical applications, development of systems with high imaging speed, reasonable cost, and manageable data flow are needed. Sparse-sampling PACT with advanced reconstruction algorithms, such as compressed-sensing reconstruction, has shown potential as a solution to this challenge. However, most such algorithms require iterative reconstruction and thus intense computation, which may lead to excessively long image reconstruction times. Here, we developed a principal component analysis (PCA)-based PACT (PCA-PACT) that can rapidly reconstruct high-quality, three-dimensional (3-D) PACT images with sparsely sampled data without requiring an iterative process. In vivo images of the vasculature of a human hand were obtained, thus validating the PCA-PACT method. The results showed that, compared with the back-projection (BP) method, PCA-PACT required ∼50% fewer measurements and ∼40% less time for image reconstruction, and the imaging quality was almost the same as that for BP with full sampling. In addition, compared with compressed sensing-based PACT, PCA-PACT had approximately sevenfold faster imaging speed with higher imaging accuracy. This work suggests a promising approach for low-cost, 3-D, rapid PACT for various biomedical applications.