Centrifugal spinning of viscoelastic nanofibres

The centrifugal spinning method is a recently invented technique to extrude polymer melts/solutions into ultra-fine nanofibres. Here, we present a superior integrated string-based mathematical model, to quantify the nanofibre fabrication performance in the centrifugal spinning process. Our model enables us to analyse the critical flow parameters covering an extensive range, by incorporating the angular momentum equations, the Giesekus viscoelastic constitutive model, the air-to-fibre drag effects and the energy equation into the string model equations. Using the model, we can analyse the dynamic behaviour of polymer melt/solution jets through the dimensionless flow parameters, namely, the Rossby ( $Rb$ ), Reynolds ( $Re$ ), Weissenberg ( $Wi$ ), Weber ( $We$ ), Froude ( $Fr$ ), air Péclet ( $Pe^*$ ) and air Reynolds ( $Re^*$ ) numbers as well as the viscosity ratio ( $\delta _s$ ), corresponding to rotational, inertial, viscous, viscoelastic, surface tension, gravitational, air thermal diffusivity, aerodynamic and viscosity ratio effects. We find that the nonlinear rheology remarkably affects the fibre trajectory, radius and normal stresses. Increasing $Wi$ leads to a thicker fibre, whereas increasing $\delta _s$ shows an opposite trend. In addition, by increasing $Wi$ , the fibre curvature is enhanced, causing the fibre to spiral closer to the rotation centre.

Experimental investigation on the nanoindentation viscoelastic constitutive model of quartz and kaolinite in mudstone

The creep behaviors in deep underground engineering structures, especially in soft rocks, have a remarkable impact on the long-term stability of the excavations, which finally leads to the high risk and failure of it. Accordingly, it is essential to recognize the time-dependent deformation through the investigation of this phenomenon. In this study, the creep behaviors of soft rocks were examined to help understand the underlying mechanism of the extended time-dependent deformation. Due to the limited results about the time-dependent properties of the constituents of the rock that reveal their heterogeneity, the targeting nanoindentation technique (TNIT), was adopted to investigate the viscoelastic characteristics of kaolinite and quartz in a two-constituent mudstone sample. The TNIT consists of identifications of mineralogical ingredients in mudstone and nanoindentation experiments on each identified constituent. After conducting experiments, the unloading stages of the typical indentation curves were analyzed to calculate the hardness and elastic modulus of both elements in mudstone. Additionally, the 180 s load-holding stages with the peak load of 50 mN were transformed into the typical creep strain–time curves for fitting analysis by using the Kelvin model, the standard viscoelastic model, and the extended viscoelastic model. Fitting results show that the standard viscoelastic model not only can perfectly express the nanoindentation creep behaviors of both kaolinite and quartz but also can produce suitable constants used to measure their creep parameters. The creep parameters of kaolinite are much smaller than that of quartz, which causes the considerable time-dependent deformation of the soft mudstone. Eventually, the standard viscoelastic model was also verified on the quartz in a sandstone sample.

An active finite viscoelastic model for gastric smooth muscle contraction

A coupled electromechanical model to describe the transduction process of cellular electrical activity into mechanical deformation has been presented. The model consolidates a biophysical smooth muscle cell model, a biophysical actin-myosin interaction model, a sliding filament model and a viscoelastic constitutive model to construct an active finite viscoelastic model. The key input to this model is an electrical pulse which then estimates the resulting stress and deformation in the cell. The proposed model was used to recreate experimental observations performed on canine and porcine gastric tissue strips. In all cases, the simulation results were well matched with the experimental data (R2> 0.9).

Insights into the Microstructural Origin of Brain Viscoelasticity

Mechanical aspects play an important role in brain development, function, and disease. Therefore, continuum-mechanics-based computational models are a valuable tool to advance our understanding of mechanics-related physiological and pathological processes in the brain. Currently, mainly phenomenological material models are used to predict the behavior of brain tissue numerically. The model parameters often lack physical interpretation and only provide adequate estimates for brain regions which have a similar microstructure and age as those used for calibration. These issues can be overcome by establishing advanced constitutive models that are microstructurally motivated and account for regional heterogeneities through microstructural parameters.In this work, we perform simultaneous compressive mechanical loadings and microstructural analyses of porcine brain tissue to identify the microstructural mechanisms that underlie the macroscopic nonlinear and time-dependent mechanical response. Based on experimental insights into the link between macroscopic mechanics and cellular rearrangements, we propose a microstructure-informed finite viscoelastic constitutive model for brain tissue. We determine a relaxation time constant from cellular displacement curves and introduce hyperelastic model parameters as linear functions of the cell density, as determined through histological staining of the tested samples. The model is calibrated using a combination of cyclic loadings and stress relaxation experiments in compression. The presented considerations constitute an important step towards microstructure-based viscoelastic constitutive models for brain tissue, which may eventually allow us to capture regional material heterogeneities and predict how microstructural changes during development, aging, and disease affect macroscopic tissue mechanics.