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Abstract Focused ultrasound (FUS) presents unique advantages for noninvasive localized heating, crucial for controlled shape recovery in shape memory polymers (SMPs), especially in biomedical applications. To enhance FUS-driven actuation efficiency, we propose boron nitride (BN)-infused SMP composites (SMPCs) tailored for targeted biomedical interventions. Using tert-butyl acrylate (tBA) and di(ethylene glycol) dimethacrylate as base materials, we integrated BN fillers at varying concentrations (1, 5, and 10 wt.%). A thorough characterization was carried out, including dynamic mechanical analysis, scanning electron microscopy, uniaxial tensile testing, and swelling study. These results show that increasing the BN content improves shape recovery efficiency significantly. Specifically, the 10 wt.% BN composites outperformed plain SMP in terms of shape recovery ratio when activated with FUS, and the highest shape recovery ratio can achieve 75%. However, higher BN content decreases crosslinking density and stiffness, as shown by a lower Young’s modulus and glass transition temperature. This study demonstrates the promise of BN-infused SMPCs for advanced applications in biomedical application, where noninvasive spatiotemporal actuation of SMPs is required. 

Abstract Acoustic holographic lenses (AHLs) show great potential as a straightforward, inexpensive, and reliable method of sound manipulation. These lenses store the phase and amplitude profile of the desired wavefront when illuminated by a single acoustic source to reconstruct ultrasound 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 impact of acousto-thermal dynamics on the generation of AHLs is largely unexplored. We use a machine learning-assisted single inverse problem approach for rapid and efficient AHLs’ design to generate thermal patterns. 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 analyses of experimental samples are performed to offer a knowledge of the obtained pattern dynamics, as well as the applicability of holographic thermal mapping for precise volumetric temperature control. Finally, the proposed framework aims to provide a solid foundation for volumetric analysis of acousto-thermal patterns within thick samples and for assessing thermal changes with outer surface measurements. 

Acoustic holographic lenses, also known as acoustic holograms, can change the phase of a transmitted wavefront in order to shape and construct complex ultrasound pressure fields, often for focusing the acoustic energy on a target region. These lenses have been proposed for transcranial focused ultrasound (tFUS) to create diffraction-limited focal zones that target specific brain regions while compensating for skull aberration. Holograms are currently designed using time-reversal approaches in full-wave time-domain numerical simulations. Such simulations need time-consuming computations, which severely limits the adoption of iterative optimization strategies. In the time-reversal method, the number and distribution of virtual sources can significantly influence the final sound field. Because of the computational constraints, predicting these effects and determining the optimal arrangement is challenging. This study introduces an efficient method for designing acoustic holograms using a volumetric holographic technique to generate focused fields inside the skull. The proposed method combines a modified mixed-domain method for ultrasonic propagation with a gradient descent iterative optimization algorithm. The findings are further validated in underwater experiments with a realistic 3D-printed skull phantom. This approach enables substantially faster holographic computation than previously reported techniques. The iterative process uses explicitly defined loss functions to bias the ultrasound field’s optimization parameters to specific desired characteristics, such as axial resolution, transversal resolution, coverage, and focal region uniformity, while eliminating the uncertainty associated with virtual sources in time-reversal techniques. The proposed techniques enable more rapid hologram computation and more flexibility in tailoring ultrasound fields for specific therapeutic requirements. 

ABSTRACT In therapeutic focused ultrasound (FUS), such as thermal ablation and hyperthermia, effective acousto‐thermal manipulation requires precise targeting of complex geometries, sound wave propagation through irregular structures, and selective focusing at specific depths. Acoustic holographic lenses (AHLs) provide a distinctive capability to shape acoustic fields into precise, complex, and multifocal FUS‐thermal patterns. Acknowledging the under‐explored potential of AHLs in shaping ultrasound‐induced heating patterns, this study introduces a roadmap for acousto‐thermal modeling in the design of AHLs. Three primary modeling approaches are studied and contrasted using four distinct shape groups for the imposed target field. They include pressure‐based time reversal (TR) (basic (BSC‐TR) and iterative (ITER‐TR)), temperature‐based (inverse heat transfer optimization (IHTO‐TR)), and machine learning (ML)‐based (generative adversarial network (GaN) and GaN with feature (Feat‐GAN)) methods. Novel metrics, including image quality, thermal efficiency, thermal control, and computational time, are introduced, providing each method's strengths and weaknesses. The importance of evaluating target pattern complexity, thermal and pressure requirements, and computational resources is highlighted. As a further step, two case studies: (1) transcranial FUS and (2) liver hyperthermia, demonstrate the practical use of acoustic holography in therapeutic settings. This paper offers a practical reference for selecting modeling approaches based on therapeutic goals and modeling requirements. Alongside established methods like BSC‐TR and ITER‐TR, new techniques IHTO‐TR, GaN, and Feat‐GaN are introduced. BSC‐TR serves as a baseline, while ITER‐TR enables refinement based on target shape characteristics. IHTO‐TR supports thermal control, GaN offers rapid solutions under fixed conditions, and Feat‐GaN provides adaptability across varying application settings. 

Abstract High-intensity focused ultrasound (HIFU) has been investigated as a remote and controlled activation method to noninvasively actuate shape memory polymers (SMPs), specifically in biomedical applications. However, the effects of aqueous environment on shape recoverability ofin vivoHIFU-actuated SMPs have yet to be explored. HIFU directs sound waves into a millimeter-sized tightly focused region. In this study, the response of hydrophilic and hydrophobic photopolymerized thermoset SMP networks under HIFU activation in an aqueous environment was investigated. Acrylate-based SMP networks were copolymerized in specific ratios to produce networks with independently adjusted glass transition temperatures ranging from 40 to 80 °C and two distinct water uptake behaviors. The results link the polymer swelling behavior to shape recoverability in various acoustic fields. The presence of absorbed water molecules enhances the performance of SMPs in terms of their shape memory capabilities when activated by HIFU. Overall, understanding the interplay between water uptake and HIFU-actuated shape recovery is essential for optimizing the performance of SMPs in aqueous environments and advancing their use in various medical applications. 

Abstract The study of the impedance mismatch between the device and its surroundings is crucial when building an acoustic device to obtain optimal performance. In reality, a high impedance mismatch would prohibit energy from being transmitted over the interface, limiting the amount of energy that the device could treat. In general, this is solved by using acoustic impedance matching layers, such as gradients, similar to what is done in optical coatings. The simplest form of such a gradient can be considered as an intermediate layer with certain qualities resting between the two media to impedance match, and requiring a minimum thickness of at least one quarter wavelength of the lowest frequency under consideration. The desired combination(s) of the (limited) available elastic characteristics and densities has traditionally determined material selection. Nature, which is likewise limited by the use of a limited number of materials in the construction of biological structures, demonstrates a distinct approach in which the design space is swept by modifying certain geometrical and/or material parameters. The middle ear of mammals and the lateral line of fishes are both instances of this method, with the latter already incorporating an architecture of distributed impedance matched underwater layers. In this paper, we develop a resonant mechanism whose properties can be modified to give impedance matching at different frequencies by adjusting a small set of geometrical parameters. The mechanism in question, like the lateral line organ, is intended to serve as the foundation for the creation of an impedance matching meta-surface. A computational study and parameter optimization show that it can match the impedance of water and air in a deeply sub-wavelength zone.