# Special Issue on Multiphase Flows in Microfluidics: Fundamentals and Applications
###### Abstract  
Microfluidics, a cutting-edge field involving various applications in advanced materials, new energy, single-cell/single-molecule studies, human health, biomedicine, and so forth, has advanced rapidly in the last two decades. Among the applications of microfluidics, multiphase flow is the fundamental element in various microfluidic subjects, such as those concerning emulsions, droplets, bubbles, micromixers/reactors, and microswimmers/robots. For example, microfluidic technology changes the motion of particles through varying the channel area of the diversion form, particle inertia, hydrophilicity, gravity characteristics, deterministic lateral displacement, viscoelastic separation, and zeta potential [1]. Controlling particle motion, the radial position, and the spacing between particles make them easier to capture, focus on, select, and separate, e.g., through cell separation and capture, bacterial selection, and DNA separation and focusing, to meet the needs of studies and fields such as biomedicine. On the other hand, microfluidics (adding nanoparticles to the fluid) has been widely used to enhance heat transfer [2]. The impact of particle size, concentration, shape, and distribution on enhanced heat transfer has always been a research focus. When the particle size, concentration, and shape are fixed, the optimal distribution of particles can be obtained through controlled methods in order to achieve a better heat transfer effect. For instance, the magnetic particles in the fluid will form a chain-like structure under the action of a high-intensity magnetic field, which can enhance heat transfer. When the volume concentration of particles is 6.3%, the maximum enhancement value of thermal conductivity can be 30  
of moments. They found that the nucleation of nanoparticles was inhibited with increasing background particle concentration by considering the effect of binary homogeneous nucleation, Brownian coagulation, condensation, and thermophoresis of nanoparticles. [PERSON] et al. [6] numerically simulated the nanoparticle settlement and pressure drop in a gas-solid two-phase flow in a pipe by solving the momentum equation of the two-fluid model. They found that the pressure drop increased with increasing inlet velocity, particle volume concentration, and mass, but with decreasing particle diameter, and derived an expression of the settlement index and pressure drop as functions of inlet velocity, particle volume concentration, mass, and particle diameter based on the numerical data. [PERSON] et al. [7] studied the collision rate of nanoparticle aggregations and aggregated structure with different particle volume fractions using the Langevin dynamics method, and showed that the self-preserving size distribution of particles broadened with increasing particle volume fraction; the radius of gyration was smaller with the same cluster size, i.e., the particle agglomerations were in a tighter coagulation when the particle volume fraction was higher. [PERSON] et al. [8] explored experimentally the effects of tracer fluid flow velocity and porous medium permeability on the dispersion phenomenon using natural and sand-filled cores, respectively, and found that a higher volumetric flow rate and lower permeability caused a delay in the tracer breakthrough time and an increase in the dispersion coefficient; the combination of high velocity and low permeability yielded a large dispersion coefficient. Most particles in the applications are non-spherical, and the transport and deposition of non-spherical particles are very complicated because particle rotation and orientation distribution are strongly coupled with the translation motion [9]. Some papers in this Special Issue are related to the motion characteristics of non-spherical particles. [PERSON] et al. [10] numerically simulated the distribution and deposition of rod-like nanoparticles in a turbulent pipe flow by considering the Brownian and turbulent diffusion of nanoparticles.