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The miniaturization and integration of electronic circuitry has not only made the enormous increase in performance of semiconductor devices possible but also spawned a myriad of new products and applications ranging from a cellular phone to…
Diffusion MRI (dMRI) is an important neuroimaging technique with high acquisition costs. Deep learning approaches have been used to enhance dMRI and predict diffusion biomarkers through undersampled dMRI. To generate more comprehensive raw…
Molecular-scale interactions between solvated macromolecules and solid surfaces govern a large number of processes, from biology to engineering. Yet, despite extensive characterization at the macroscopic level, our molecular understanding…
We present a computational investigation of the mechanism governing size-based particle separation in microfluidic pinched flow fractionation. We study the behavior of particles moving through a pinching gap (i.e., a constriction in the…
Our growing ability to tailor healthcare to the needs of individuals has the potential to transform clinical treatment. However, the measurement of multiple biomarkers to inform clinical decisions requires rapid, effective, and affordable…
Though ubiquitous in many engineering applications, including drug delivery, the compound droplet hydrodynamics in confined geometries have been barely surveyed. For the first time, this study thoroughly investigates the hydrodynamics of a…
Magnetic resonance imaging (MRI) is the method of choice for noninvasive studies of micrometer-scale structures in biological tissues via their effects on the time/frequency-dependent ("restricted") and anisotropic self-diffusion of water.…
Minimally invasive interventions performed inside brain vessels with the synergistic use of microcatheters pushed over guidewires have revolutionized the way aneurysms, stroke, arteriovenous malformations, brain tumors and other…
Phase field crystal (PFC) models constitute central tools for a microscopic understanding of the dynamics of complex systems in soft matter physics. They have found widespread application in the modeling of the uniaxial orientational…
Fluid ferroelectrics, a recently discovered class of liquid crystals that exhibit switchable, long-range polar order, offer opportunities in ultrafast electro-optic technologies, responsive soft matter, and next-generation energy materials.…
Understanding the complexity of fragmentation processes is essential for regulating intercellular communication in mechanistic biology and developing novel bottom-up approaches in a large range of multiphase flow processes. In this context,…
In this review, we propose a summary of the most recent advances in the first-principles study of ferroelectric oxide epitaxial thin films and multilayers. We discuss in detail the key roles of mechanical and electrical boundary conditions,…
Dielectric environment engineering is an efficient and general approach to manipulating polaritons. Liquids serving as surrounding media of polaritons have been used to shift polariton dispersions and tailor polariton wavefronts. However,…
Microfluidic chips provide unparalleled control over droplets and jets, which have advanced all natural sciences. However, microfluidic applications could be vastly expanded by increasing the per-channel throughput and directly exploiting…
The transport of Brownian particles in a slit geometry in the presence of an arbitrary two-dimensional periodic energy landscape and driven by an external force or convected by a flow field is investigated by means of macrotransport theory.…
We exploit magnetostriction in polydisperse ferrofluids in order to generate nonlinear responses, and apply a thermodynamical method to derive the desired nonlinear magnetic susceptibility. For an ideal gas, this method has been…
We investigate the transport dynamics of elongated microparticles in microchannel flows. While smooth-walled channels preserve the dependence of particle trajectories on initial orientation and lateral position, we show that introducing…
The particle-in-cell approach has proven effective at modeling neutron star and black hole magnetospheres from first principles, but global simulations are plagued with an unrealistically small separation between the scales where…
Accurate physical modeling with 3D-printing techniques could lead to new approaches to study structure and dynamics of biological systems complementing computational methods. Computational biology has become an important part of research…