Langmuir. 2023 Oct 27. doi: 10.1021/acs.langmuir.3c02272. Online ahead of print.
ABSTRACT
Droplets made of liquid perfluorocarbon undergo a phase transition and transform into microbubbles when triggered by ultrasound of intensity beyond a critical threshold; this mechanism is called acoustic droplet vaporization (ADV). It has been shown that if the intensity of the signal coming from high ultrasonic harmonics are sufficiently high, superharmonic focusing is the mechanism leading to ADV for large droplets (>3 μm) and high frequencies (>1.5 MHz). In such a scenario, ADV is initiated due to a nucleus occurring at a specific location inside the droplet volume. But the question on what induces ADV in the case of nanometer-sized droplets and/or at low ultrasonic frequencies (<1.5 MHz) still remains. We investigated ADV of perfluorohexane (PFH) nano- and microdroplets at a frequency of 1.1 MHz and at conditions where there is no superharmonic focusing. Three types of droplets produced by microfluidics were studied: plain PFH droplets, PFH droplets containing many nanometer-sized water droplets, and droplets made of a PFH corona encapsulating a single micron-sized water droplet. The probability to observe a vaporization event was measured as a function of acoustic pressure. As our experiments were performed on droplet suspensions containing a population of monodisperse droplets, we developed a statistical model to extrapolate, from our experimental curves, the ADV pressure thresholds in the case where only one droplet would be insonified. We observed that the value of ADV pressure threshold decreases as the radius of a plain PFH droplet increases. This value was further reduced when a PFH droplet encapsulates a micron-sized water droplet, while the encapsulation of many nanometer-sized water droplets did not modify the threshold. These results cannot be explained by a model of homogeneous nucleation. However, we developed a heterogeneous nucleation model, where the nucleus appears at the surface in contact with PFH, that successfully predicts our experimental ADV results.
PMID:37889478 | DOI:10.1021/acs.langmuir.3c02272
