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Perfluorocarbon nanodroplets (PFCnDs) are ultrasound contrast agents that phase-transition from liquid nanodroplets to gas microbubbles when activated by laser irradiation or insonated with an ultrasound pulse. The dynamics of PFCnDs can vary drastically depending on the nanodroplet composition, including the lipid shell properties. In this paper, we investigate the effect of varying the ratio of PEGylated to non-PEGylated phospholipids in the outer shell of PFCnDs on the acoustic nanodroplet vaporization (liquid to gas phase transition) and inertial cavitation (rapid collapse of the vaporized nanodroplets) dynamics in vitro when insonated with focused ultrasound. Nanodroplets with a high concentration of PEGylated lipids had larger diameters and exhibited greater variance in size distribution compared to nanodroplets with lower proportions of PEGylated lipids in the lipid shell. PFCnDs with a lipid shell composed of 50:50 PEGylated to non-PEGylated lipids yielded the highest B-mode image intensity and duration, as well as the greatest pressure difference between acoustic droplet vaporization onset and inertial cavitation onset. We demonstrate that slight changes in lipid shell composition of PFCnDs can significantly impact droplet phase transitioning and inertial cavitation dynamics. These findings can help guide researchers to fabricate PFCnDs with optimized compositions for their specific applications. 

Acoustic metasurfaces are two-dimensional materials that impart non-trivial amplitude and phase shifts on incident acoustic waves at a predetermined frequency. While acoustic metasurfaces enable extraordinary wavefront engineering capabilities, they are not developed well enough to independently control the amplitude and phase of reflected and transmitted acoustic waves simultaneously, which are governed by their geometry. We aim to solve the inverse design problem of finding a geometry to achieve a specified set of acoustic properties. The geometry is modeled by discretizing the continuous space into a finite number of elements, where each element can either be filled with air or solid material. Full wave simulations are performed to obtain the acoustic properties for a given geometry. It is computationally infeasible to simulate all geometries. To address this challenge, we develop an experimental design-based algorithm to efficiently perform the simulations. The algorithm starts with a few geometries and adaptively adds geometries to the set, such that they fill the entire space of the desired acoustic properties using a small fraction of the possible geometries. We find that the geometry needs to have at least 7 × 7 elements to obtain any given acoustic property with a tolerance of 5.4% of its maximum range. This is achieved by simulating 24 000 geometries using the proposed algorithm, which is only [Formula: see text] of the 563 × 10 12 possible geometries. The method provides a general solution to the inverse design problem that can be extended to control more acoustic properties.