Acoustically-driven cloud cavitation of coated microbubbles

声空化，即气泡在液体环境中的压力驱动行为，被广泛应用于各种工程应用中，从超声波清洗到涂层微泡作为医学成像中的超声造影剂(UCA)。尤其是覆盖了磷脂单分子层或蛋白质层的UCA微泡的声空化在诊断和治疗生物医学方面的应用稳步增加，包括靶向药物输送和新的癌症治疗。然而，尽管有大量关于微气泡云的声空化的文献，但对包覆的微气泡在声场中的行为的全面了解仍然是难以捉摸的。特别是，对气泡云破裂引起的压力、速度和温度分布的详细了解对于生物医学应用中的治疗安全和成功至关重要，但尚未得到系统的研究。考虑到这一点，拟议项目的主要目标是(I)详细分析坍塌的微泡云附近的压力和温度，以及(Ii)全面比较清洁和涂层微泡的声云空化，这将共同为在生物医学应用中更安全和更有效地利用声空化奠定基础。为了促进这项研究，我们将在欧拉-拉格朗日框架的背景下开发新的数值方法，通过消除目前关于气泡大小的限制和显著改进液体中的温度预测来扩展最新技术。特别是对于生物医学应用，我们期待这样的数值格式能够提供一个有价值的研究工具，可以补充实验。

Acoustic cavitation, i.e. the pressure-driven behaviour of bubbles in a liquid environment, is utilised in a large variety of engineering applications, ranging from ultrasonic cleaning to coated microbubbles as ultrasonic contrast agents (UCA) in medical imaging. Especially the acoustic cavitation of UCA microbubbles, which are coated with a phospholipid monolayer or protein layer, has seen a steadily increasing number of diagnostic and therapeutic biomedical applications, including targeted drug delivery and novel cancer treatments. However, despite a substantial body of literature on the acoustic cavitation of microbubble clouds, a comprehensive understanding of the behaviour of clouds of coated microbubbles in an acoustic field still remains elusive. In particular, a detailed understanding of the pressure, velocity and temperature distribution as a result of the collapse of the bubble cloud is critical for treatment safety and success in biomedical applications, but has not been studied systematically yet. With this in mind, the primary objectives of the proposed project are (i) a detailed analysis of the pressure and temperature in the vicinity of collapsing clouds of microbubbles, and (ii) a comprehensive comparison of the acoustic cloud cavitation of clean and coated microbubbles, which will together lay the foundation for a safer and more efficient use of acoustic cavitation in biomedical applications. To facilitate this research, we will develop new numerical methods in the context of an Euler-Lagrange framework, extending the state-of-the-art by eliminating current limitations regarding the bubble size and improving the temperature prediction in liquids significantly. Especially for biomedical applications, we expect such numerical schemes to provide a valuable research tool that can complement experiments.