Holographic Thermal Mapping Using Acoustic Lenses

Abstract

Acoustic holographic lenses (AHLs) show great potential for sound manipulation. These lenses store the phase and amplitude profile of the desired wavefront when illuminated by a single acoustic source to reconstruct focused ultrasound (FUS) pressure fields, induce localized heating, and achieve temporal and spatial thermal effects in acousto-thermal materials like polymers. The ultrasonic energy is transmitted and focused by AHL from a transducer into a particular focal volume. It is then converted to heat by internal friction in the polymer chains, causing the temperature of the polymer to rise at the focus locations while having little to no effect elsewhere. This one-of-a-kind capability is made possible by the development of AHLs to make use of the translation of attenuated pressure fields into programmable heat patterns. However, the acousto-thermal dynamics of AHLs are largely unexplored. We use a machine learning-assisted single inverse problem approach for rapid and efficient AHL designs. The process involves the conversion of thermal information into a holographic representation through the utilization of two latent functions; pressure phase and amplitude. Experimental verification is performed for pressure and thermal measurements. The volumetric acousto-thermal analysis of experimental samples is performed to offer knowledge of the obtained pattern dynamics, as well as the applicability of holographic FUS thermal mapping for precise temperature control in complex volumes of heterogeneous media. The proposed framework provides a solid foundation for anticipating and assessing thermal changes within materials using only outer surface measurements since it can correlate with surface temperature data alone.