Rare-earth Doped Nanoparticles with Narrow NIR-II Emission for Optical Imaging with Reduced Autofluorescence

Fluorescence imaging in the second near-infrared region(900-1700 nm, NIR-II) with a high resolution and penetration depth due to the significantly reduced tissue scattering and autofluorescence has emerged as a useful tool in biomedical fields. Recently, many efforts have been devoted to the development of fluorophores with an emission band covering the long-wavelength end of NIR-II region(1500-1700 nm) to eliminate the autofluorescence. Alternatively, we believe imaging with a narrow bandwidth could also reduce the autofluorescence. As a proof of concept, NaYF₄:Yb,Nd@NaYF₄ downconversion nanoparticles(DCNPs) with sharp NIR-II emission were synthesized. The luminescence of DCNPs showed a half-peak width of 49 nm centered at 998 nm, which was perfectly matched with a (1000±25) nm bandpass filter. With this filter, we were able to retain most of the emissions from the nanoparticles, while the autofluorescence was largely reduced. After PEGylation, the DCNPs exhibited great performance for blood vessel and tumor imaging in living mice with significantly reduced autofluorescence and interference signals. This work provided an alternative way for the low-autofluorescence imaging and emphasized the importance of narrow emitting rare-earth doped nanoparticles for NIR-II imaging.     

Direct resolution of differential pressure fluctuations to characterize multi-scale dynamics in a gas fluidized bed

A direct resolution approach was proposed to decompose differential pressure signals from a gas fluidized bed into macro- and super-imposing components, which were further subjected to structure density function analysis (SDF analysis) to study dynamics of multi-scale structures in flow. Direct resolution performed well in extracting feature information of multi-scale structures, especially macro- and meso-scale structures whose dynamic behaviors majorly affected hydrodynamics in bed, from measured differential pressure fluctuations. With the assistance of Gaussian fitting and Kolmogorov–Smirnov test, SDF analysis divided the probability distribution of multiple structures with respect to their amplitude scale r into four feature regions (Regions B-I, B-II, B-III and Region A). Parameter K_SDF derived from slope of Region B-II quantified frequency of various meso-scale structures in flow, and well followed the tendency of flow patterns transition after being normalized by bubble (slug) rising velocity U_b(sl). Frequency of macro-scale structures in slugging flow depended greatly on rising velocity of slugs, so SDF_macro increased with increased fluidization velocity. Developed turbulent flow had a high SDF_macro exceeded 0.8 Hz due to the fast passage and split/integration of large voids. Structures localized in Region A mainly represented noise from measurements, other measurable micro-scale disturbances in single phases or phase-interfaces, and had an occurring frequency increased with increase of fluidization velocity.     

A fourth-order approximate projection method for the incompressible Navier–Stokes equations on locally-refined periodic domains

In this follow-up of our previous work [30], the author proposes a high-order semi-implicit method for numerically solving the incompressible Navier–Stokes equations on locally-refined periodic domains. Fourth-order finite-volume stencils are employed for spatially discretizing various operators in the context of structured adaptive mesh refinement (AMR). Time integration adopts a fourth-order, semi-implicit, additive Runge–Kutta method to treat the non-stiff convection term explicitly and the stiff diffusion term implicitly. The divergence-free condition is fulfilled by an approximate projection operator. Altogether, these components yield a simple algorithm for simulating incompressible viscous flows on periodic domains with fourth-order accuracies both in time and in space. Results of numerical tests show that the proposed method is superior to previous second-order methods in terms of accuracy and efficiency. A major contribution of this work is the analysis of a fourth-order approximate projection operator.     

A fluid–structure interaction solver for the study on a passively deformed fish fin with non-uniformly distributed stiffness

Research on fish locomotion has made extensive progress towards a better understanding of how fish control their flexible body and fin for propulsion and maneuvering. Although the biologically flexible fish fins are believed to be one of the most important features to achieve optimal swimming performance, due to the limitations of the existing numerical modeling tool, studies on a deformable fin with a non-uniformly distributed stiffness are rare. In this work, we present a fully coupled fluid–structure interaction solver which can cope with the dynamic interplay between flexible aquatic animal and the ambient medium. In this tool, the fluid is resolved by solving Navier–Stokes equations based on the finite volume method with a multi-block grid system. The solid dynamics is solved by a nonlinear finite element method. A sophisticated improved IQN-ILS coupling algorithm is employed to stabilize solution and accelerate convergence. To demonstrate the capability of the developed Fluid–Structure-Interaction solver, we investigated the effect of five different stiffness distributions on the propulsive performance of a caudal peduncle-fin model. It is shown that with a non-uniformly distributed stiffness along the surface of the caudal fin, we are able to replicate similar real fish fin deformation. Consistent with the experimental observations, our numerical results also indicate that the fin with a cupping stiffness profile generates the largest thrust and efficiency whereas a heterocercal flexible fin yields the least propulsion performance but has the best maneuverability.