arXiv subjects

Samuele Fiorini

Publications and source records attributed to Samuele Fiorini.

6 recordsLinked to original sources

arXiv2026

Bubble jetting in acoustic microdroplet vaporization

Acoustic droplet vaporization denotes the phase-change of micron- and sub-micron-sized droplets upon the application of high-amplitude ultrasound. The asymmetric collapse of the incepted vapor bubbles within the droplets can give rise to high-speed liquid microjets. Here, we describe acoustically-driven and bubble-pair jetting arising within the vaporizing droplet, observed experimentally with ultra-high-speed imaging at the microscale. The existence of complex pressure fields due to the continued acoustic wave-droplet interaction and the nucleation of multiple bubbles within the droplet leads to rich dynamics, with the jets presenting behavioral self-similarity to millimetric bubbles under comparable conditions. Evaporative instabilities that develop during bubble growth impede jet formation during bubble collapse. Furthermore, the ability of the jets to pierce the droplet interface and penetrate into the surrounding fluid is discussed. These powerful microjets could be harnessed to induce cell permeabilization for targeted drug delivery and treatment of cancerous tissue.

physics.flu-dyn↗

arXiv2026

Measurement of traveling pressure waves inside a droplet

Shock wave-droplet interactions have been receiving increasing attention due to their relevance in aviation fuel combustion and minimally invasive medical treatments, yet quantifying them experimentally remains a challenge. In this study, we propose a background-oriented schlieren (BOS) technique for quantitative spatiotemporal measurements of shock wave-droplet interaction, employing a novel ray-tracing correction, a synchronization system, and a projected background. Underwater shock waves propagating both inside and outside a millimetric perfluorohexane droplet immersed in water are experimentally measured. The quantified density-gradient and pressure fields are compared with numerical simulations, and the BOS measurements-including sound speeds, the shock-focusing location, and the maximum pressure-are found to be in close agreement with the numerical results. Notably, the technique successfully captures the phase shift before and after shock focusing that had previously only been hypothesized.

physics.flu-dyn↗

arXiv2026

Cavitation by phase shift of focused shock waves inside a droplet

Localized cavitation in liquids and soft tissues, typically initiated by the rarefaction phase of high-amplitude ultrasound waves, is leveraged in several biomedical applications such as ablation techniques and drug delivery with vaporizing agents. However, safety considerations aimed at avoiding unwanted bubble activity outside the targeted region pose a limit to the maximum allowed peak rarefaction pressure, which on the other hand can hinder the therapeutic efficacy of these techniques. This study shows that a purely compressive shock wave can generate localized, negative pressure and initiate cavitation inside a sub-millimetric perfluorohexane droplet, without requiring any externally applied rarefaction wave. The Gouy phase shift is identified as the physical mechanism responsible for the conversion of positive pressure into tension during shock focusing, and its occurrence is demonstrated through numerical simulations and direct experimental measurements. Comparison of the regions affected by cavitation, visualized \emph{in-situ} by means of high-speed x-ray phase-contrast imaging, with prediction from Classical Nucleation Theory suggests homogeneous nucleation as the underlying mechanism behind bubble formation. The presented findings offer valuable insights into the physics of shock wave propagation which can inspire the development of novel acoustic driving strategies for cavitation generation, facilitating the reduction of negative pressures outside the target region and improving the safety and precision of biomedical treatments.

physics.flu-dyn↗

arXiv2025

Shock compression-based equation of state for perfluorohexane

Perfluorohexane is a biocompatible material that serves as a liquid core for acoustically-responsive agents in biomedical applications. Despite its relatively widespread usage, there is a lack of experimental data determining its thermodynamic properties. This challenges numerical simulations to predict the acoustic response of agents developed using this material. In this study, we employ the well-established method of shock compression of materials at relatively high pressures (100--400 MPa) to estimate a kinematic equation of state for perfluorohexane. We use multi-objective optimization to obtain the Noble-Abel Stiffened-Gas equation of state, which is suitable for hydrodynamic numerical simulations. We then apply the extrapolated equation of state to simulate shock-wave propagation within a perfluorohexane droplet showing excellent agreement with equivalent experiments. This validates the equation of state and promotes the use of numerical simulations as a valuable tool for understanding the complex acoustic interactions involved in these biomedical agents, ultimately facilitating their translation for clinical purposes.

physics.flu-dyn↗

arXiv2024

Positive pressure matters in acoustic droplet vaporization

Acoustically vaporizable droplets are phase-change agents that can improve the effectiveness of ultrasound-based therapies. In this study, we demonstrate that the compression part of an acoustic wave can generate tension that initiates the vaporization. This counter-intuitive process is explained by the occurrence of Gouy phase shift due to the focusing of the acoustic wave inside the droplet. Our analysis unifies the existing theories for acoustic droplet vaporization under a single framework and is supported by experiments and simulations. We use our theory to identify governing parameters that allow to vaporize droplets using predominantly compression waves, which are safer in medical use.

physics.flu-dyn↗

arXiv2016

A temporal model for multiple sclerosis course evolution

Multiple Sclerosis is a degenerative condition of the central nervous system that affects nearly 2.5 million of individuals in terms of their physical, cognitive, psychological and social capabilities. Researchers are currently investigating on the use of patient reported outcome measures for the assessment of impact and evolution of the disease on the life of the patients. To date, a clear understanding on the use of such measures to predict the evolution of the disease is still lacking. In this work we resort to regularized machine learning methods for binary classification and multiple output regression. We propose a pipeline that can be used to predict the disease progression from patient reported measures. The obtained model is tested on a data set collected from an ongoing clinical research project.

stat.ML↗