Deriving acoustic properties for perfluoropentane droplets with viscoelastic cellulose nanofiber shell via numerical simulations

Dimensional analysis meets AI for non-Newtonian droplet generation

Non-Newtonian droplets are used across various applications, including pharmaceuticals, food processing, drug delivery and material science. However, predicting droplet formation using such complex fluids is challenging due to the intricate multiphase interactions between fluids with varying viscosities, elastic properties and geometrical constraints. In this study, we introduce a novel hybrid machine-learning architecture that integrates dimensional analysis with machine learning to predict the flow rates required to generate droplets with specified sizes in systems involving non-Newtonian fluids. Unlike previous approaches, our model is designed to accommodate shear-rate-dependent viscosities and a simple estimate of the elastic properties of the fluids. It provides accurate predictions of the dispersed and continuous phases flow rates for given droplet length, height, and viscosity curves, even when the fluid properties deviate from those used during training. Our model demonstrates strong predictive power, achieving R2 values of up to 0.82 for unseen data. The significance of our work lies in its ability to generalize across a broad range of non-Newtonian systems having different viscosity curves, offering a powerful tool for optimizing droplet generation. This model represents a significant advancement in the application of machine learning to microfluidics, providing new opportunities for efficient experimental design in complex multiphase systems.

Cellulose Nanofiber-Coated Perfluoropentane Droplets: Fabrication and Biocompatibility Study

Purpose

To study the effect of cellulose nanofiber (CNF)-shelled perfluoropentane (PFP) droplets on the cell viability of 4T1 breast cancer cells with or without the addition of non-encapsulated paclitaxel.

Methods

The CNF-shelled PFP droplets were produced by mixing a CNF suspension and PFP using a homogenizer. The volume size distribution and concentration of CNF-shelled PFP droplets were estimated from images taken with an optical microscope and analyzed using Fiji software and an in-house Matlab script. The thermal stability was qualitatively assessed by comparing the size distribution and concentration of CNF-shelled PFP droplets at room temperature (~22°) and 37°C. The cell viability of 4T1 cells was measured using a 3-[4,5-dimethylthiazol-2yl]-2,5-diphenyltetrazolium bromide (MTT) assay. Additionally, a hemolysis assay was performed to assess blood compatibility of CNF-shelled PFP droplets.

Results

The droplet diameter and concentration of CNF-shelled PFP droplets decreased after 48 hours at both room temperature and 37°C. In addition, the decrease in concentration was more significant at 37°C, from 3.50 ± 0.64×10⁶ droplets/mL to 1.94 ± 0.10×10⁶ droplets/mL, than at room temperature, from 3.65 ± 0.29×10⁶ droplets/mL to 2.56 ± 0.22×10⁶ droplets/mL. The 4T1 cell viability decreased with increased exposure time and concentration of paclitaxel, but it was not affected by the presence of CNF-shelled PFP droplets. No hemolysis was observed at any concentration of CNF-shelled PFP droplets.

Conclusion

CNF-shelled PFP droplets have the potential to be applied as drug carriers in ultrasound-mediated therapy.