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In this paper we study an impact of viscosity on DNA behaviour. We investigate a so-called big viscosity using extended Peyrard-Bishop model to describe nonlinear DNA dynamics.

Structural and dynamical properties of Pd, Ag pure liquid metals and especially Pd_xAg_1-x alloys are studied by the molecular dynamics simulation. The effects of temperature and concentration on the liquid properties of Pd_xAg_1-x are analyzed. Sutton–Chen (SC) and Quantum Sutton–Chen (Q–SC) many-body potentials are used as interatomic interactions. The calculated diffusion constants and viscosities are in good agreement with the available experimental data and theoretical calculations. The coefficients of Arrhenius equation are also presented to calculate the self-diffusion coefficient and shear viscosity of Pd–Ag alloys at the desired temperature and concentration. We have shown that Q–SC potential parameters are more reliable in determining physical properties of metals and their alloys studied in this work.

The interrelation between apparent viscosity in steady shear flow and complex viscosity in oscillatory shear flow for magnetorheological (MR) suspensions is investigated. Series of experiments have been conducted using a MR rheometer. An extended Rutgers–Delaware rule is proposed, in which an effective shear rate for oscillatory shear flow is defined as ωΔ_h. Here ωΔ_h is the shift factor dependent on strain amplitude (γ₀), which was found to be similar for different MR suspensions under different magnetic fields. At high strain amplitudes (γ₀≥100%), Δ_h≈γ₀, the Rutgers–Delaware rule is approximately obeyed. At low strain amplitudes (γ₀<100%), the curves of Δ_h fall between the line of the Cox–Merz rule and that of the Rutgers–Delaware rule. The curve of Δ_h at low strain amplitudes depends on the ingredients of the MR suspension. For samples with the same ingredients, a unified curve of Δ_h can be identified in a range of magnetic fields and/or for a range of volume fraction of magnetic particles.

Reducing the viscosity of liquid suspensions is vital in science and engineering. This paper explores the physical mechanism for the viscosity reduction method in liquid suspension by pulsed electric or magnetic field. The key is that the maximum volume fraction to be available for the suspended particles in the suspension increases with the particle size and the polydispersity in the particle size distribution. Positive experimental results with various liquid suspensions indicate that this method, developed from the basic mechanism of viscosity, is universal and powerful for all liquid suspensions with broad applications.

The paper deals with the effect of two conductive polymers (polyaniline, PANI, and polypyrrole, PPy) in combination with inorganic particles on the response of silicone-oil suspensions. Conductive polymers cause a significant increase in electrorheological response. PANI combined with silica is much more efficient when in the form of a thin layer on the particle surface than if the two components are simply mixed. All combinations are followed from the viewpoint of viscosity and yield stress.

The modification of liquid metal by electric pulse (EP) is a novel method for grain refinement. In this work, based on the reported structural heredity of EP-modified liquid aluminum, we investigated its viscosity change by using torsional oscillation viscometer. The results validate the viscosity of EP-modified liquid aluminum also decreases with increasing temperature and meets approximately exponential correlation on the whole. Moreover, it is especially important that the EP-modified liquid aluminum has the higher viscosity and possesses the bigger viscous-flow cluster in a certain temperature range, which should be associated with the increase of the order degree of its liquid structure. Differential scanning calorimetry (DSC) measurement also confirms that viewpoint. These coupling results experimentally testify the proposed mechanism of electric pulse modification (EPM) modeled merely by postulation.

Recently, Haj-Kacem et al. proposed an equation modeling the relationship between the two parameters of viscosity Arrhenius-type equations [Fluid Phase Equilibria383, 11 (2014)]. The authors found that the two parameters are dependent upon each other in an exponential function form. In this paper, we reconsidered their ideas and calculated the two parameter values for 49 saturated pure fluids by using the experimental data in the NIST WebBook. Our conclusion is different with the ones of Haj-Kacem et al. We found that (the linearity shown by) the Arrhenius equation stands strongly only in low temperature range and that the two parameters of the Arrhenius equation are independent upon each other in the whole temperature range from the triple point to the critical point.

The accurate predicted viscosities near the melting point $T_m$ have been searched. In order to find the temperature ranges, where the measured viscosity data applied to obtain the accurate fitting viscosity data and the accurate fitting expressions near $T_m$ lie, the measured data in 15 different temperature ranges (a)–(o) are applied to obtain the fitting viscosity data and the fitting expressions by the Vogel–Fulcher–Tammann (VFT) relation. The accuracy of the fitting viscosity near $T_m$ will varies when the measured data in different temperature ranges are applied to obtain the fitting viscosity data by VFT relation. It is found that the accurate fitting viscosity data with the coefficients of determination $(\mathrm{\text{CD}}>0.998)$ in temperature range 397.3–583.6 K (0.84–1.24$T_m$) near $T_m$ can be acquired using the measured data in temperature ranges (g)–(h) and (k) by the VFT relation. In other words, we found the temperature ranges (namely, temperature ranges (g)–(h) and (k)), in which the measured viscosity data applied to obtain the accurate fitting viscosity data and the accurate fitting expressions near $T_m$ exist.

One of the interesting topics of recent research is the study of the Weibel electromagnetic instability growth rate in the interaction of high-intensity lasers with the dense plasma of fusion fuel pellets. In this paper, the effect of stresses caused by laser ponderomotive force on the growth rate of Weibel instability in the nonlinear phase is investigated. The growth of the nonlinear phase of Weibel instability growth rate, which is the saturation phase of Weibel instability, in the presence of stress leads to viscosity turbulence. The results show that the coefficient of reduction of fuel viscosity in the presence of the stress flow is about 0.0014 due to the anomalous transfer mechanism caused by the nonlinear growth of the Weibel instability.

The nanofiltration (NF) process becomes the most recently used technologies for the desalination of seawater and brackish water. The porous media transport properties are first related to the geometrical complexity of the product. However, the membrane transport models used in desalination process constitute approximatively the less understood process. The objective of this work is to address modeling and numerical study of the desalination process of the water and ions fluxes by using a porous membrane with nanoparticles. Our filtration system used is constituted by two different zones that the membrane sheets are sandwiched. The fluid undergoes a first simple filtration and a second NF process by the injected nanoparticles. The impacts of the permeability K and porosity S of the membrane under the effect of a pressure $P_0$ were discussed. Our findings are obtained in the framework of the dynamic Langevin approach based on the competitiveness between the stochastic process and dissipation. The results show that the performance of the rejection membrane is significant as the nanoparticle concentration decreases, and increases as a power law with the ratio of the viscosity of the salty fluid to the pure fluid.

Ice accretion on aircraft is studied by a numerical method. By solving governing equations, the flow field is obtained for analyzing the icing zone and calculating the ice quantity on different parts. Influence of the fluid viscosity and compressibility on icing characters is extensively studied. And it can be found that the results agree well with those calculated by LEWICE program. This achievement could be helpful to further research on ice accretion.

We have proposed and investigated a model of drying colloidal suspension drop placed onto a horizontal substrate in which the sol to gel phase transition occurs. The temporal evolution of volume fraction of the solute and the gel phase dynamics were obtained from numerical simulations. Our model takes into account the fact that some physical quantities are dependent on volume fraction of the colloidal particles.

The nature of excitations in liquids has been a subject of debate for a long time. In liquids, phonons are extremely short-lived and marginalized. Instead, recent research results indicate that local topological or configurational excitations (anankeons) are the elementary excitations in high temperature metallic liquids. Local topological excitations are those which locally alter the atomic connectivity network by cutting or forming atomic bonds, and are directly tied to the atomistic origin of viscosity in the liquid. The local potential energy landscape (PEL) of anankeons represents the probability weighted projection of the global PEL to a single atom. The original PEL is an insightful concept, but is highly multi-dimensional and difficult to characterize or even to visualize. A description in terms of the local PEL for anankeons appears to offer a simpler and more effective approach toward this complex problem. At the base of these advances, is the recognition that atomic discreteness and the topology of atomic connectivity are the most crucial features of the structure in liquids, which current nonlinear continuum theories cannot fully capture. These discoveries could open the way to the explanation of various complex phenomena in liquids, such as atomic transport, fragility, and the glass transition, in terms of these excitations.

Based on the recent progress on both the temperature dependence of surface tension [H. L. Yi, J. X. Tian, A. Mulero and I. Cachading, J. Therm. Anal. Calorim.126 (2016) 1603, and the correlation between surface tension and viscosity of liquids [J. X. Tian and A. Mulero, Ind. Eng. Chem. Res.53 (2014) 9499], we derived a new multiple parameter correlation to describe the temperature-dependent viscosity of liquids. This correlation is verified by comparing with data from NIST Webbook for 35 saturated liquids including refrigerants, hydrocarbons and others, in a wide temperature range from the triple point temperature to the one very near to the critical temperature. Results show that this correlation predicts the NIST data with high accuracy with absolute average deviation (AAD) less than 1% for 21 liquids and more than 3% for only four liquids, and is clearly better than the popularly used Vogel–Fulcher–Tamman (VFT) correlation.

The Vogel–Fulcher–Tamman (VFT) correlation is the known most accurate equation used to estimate and predict temperature-dependent viscosity of fluids. But its accuracy analysis for saturated liquids is still unknown. In this paper, we checked its ability for 49 saturated liquids by using the data in the National Institute of Standards and Technology (NIST) Webbook. Through detailed accuracy analysis, we found that the VFT correlation works qualitatively but does not work well quantitavely. We shown the temperature ranges in which the VFT correlation holds for absolute average deviations (AADs) of $\sim$1%, $\sim$2% and $\sim$5%. The corresponding coefficients are also obtained for engineers to use it directly. We also proposed a new four-parameter correlation to improve the predictive ability. We show that the new correlation holds for 5 fluids with AAD $<$ 1%, 37 fluids with AAD $<$ 2%, 43 fluids with AAD $<$ 3% and 48 fluids with AAD $<$ 4%.

The properties of nanoconfined fluid are critical for the design and precise control of nanofluidic devices. To understand the fundamental details of the viscosity of nanoconfined aqueous NaCl solution, we investigated the impact of the thermal motion of silicon atoms on the viscosity of nanoconfined aqueous NaCl solution using molecular dynamic simulations. The results show that thermal motion of silicon atoms can decrease the viscosity of NaCl solution, and this impact is significant when the shear rate is small.

Cells actively modify their behavior in on account of changes in their environment. The most important intrinsic parameter related to the intracellular environment is the temperature, the variations of which modify the dynamical behaviors of biomolecules. Indeed, an increase in temperature leads to an increase in fluidity which can damage the proteinous membrane and induce cellular death. If the temperature is extremely high, the proteins can be broken down or denatured as a consequence. However, concerning microtubules (MTs), we show that by their intrinsic behavior of self-organization, they are able to modulate temperature variations in order to avoid denaturation for values of temperature up to $T=50^{\circ }\mathrm{\text{C}}$. Above this temperature, there is a critical point at $T=57^{\circ }\mathrm{\text{C}}$ where the wave function completely disappears which is indicative of denaturation as the biological activity of the neuronal MTs is lost. We show that temperature variations change the viscosity of the cytosol which modifies the wave function and give rise to hybrid soliton structures. These hybrid solitons come from the collision of waves propagating along MTs. We also show that the supersonic velocity of these hybrid structures can be decreasing or increasing functions of environmental temperature.

Resonance dispersion mixing technology is a new process developed in recent years. The main function of the technology is each scale vortex caused by the vibration, which is a multiscale phenomenon that includes macroscopic vortices and mesoscopic vortices. For mesoscopic vortices, due to the lack of sufficient resolution, current commercial software filter and average these vortices, so it is difficult to meet the needs of research. Based on this, the paper proposes a lattice Boltzmann Method (LBM) to simulate the mesoscopic vortices. The LBM is a mesoscale research method, so it has sufficient resolution to study mesoscopic vortices. The paper mainly simulated the process of splitting and evolution of mesoscopic vortices, studied the effects of parameters such as simulation interval, viscosity, vibration frequency on mesoscopic vortices. The results show that the selection of the simulation interval has a certain influence on the evolution of the vortices. The viscosity of the flow field plays a decisive role in the vortices, for there is no vortex generation when the viscosity exceeds a certain threshold. The excitation frequency controls the development process of the vortices, larger frequency can significantly reduce the micro-mixing characteristic time to increase mixing efficiency. Different from the previous theoretical analysis literature, this paper gives visual numerical simulation results.

Geometric similarity ratio is one of the important factors that affects the disturbance amplitude of shock-wave front in viscosity measurement. In this paper, the Euler difference scheme of two-dimensional (2D) equations of viscous fluid mechanics is used to simulate the disturbance amplitude damping curves under different geometric similarity ratios, and the corresponding numerical solutions are shown. The samples of aluminum shocked to 80 GPa are taken as an example. The simulation results show that the initial conditions, material viscosity, wavelength, and sample geometric similarity ratio affect the evolution of the shock front sine wave disturbance. For flyer-impact flow field, the phase shift increases from 0 to a certain value with the viscosity coefficient for sample with wavelength $\lambda =6$ mm and geometric similarity ratio $h/\lambda =0.05$, 0.1. So, the geometric similarity method can be used to measure the viscosity of material. But it is found that the phase shift is sensitive to the geometric similarity ratio, which should be considered in Zaidel’s equation. So, some flyer-impact experiments will be carried out to determine the simulation results, and find the quantity relation of phase shift and viscosity of material in the future investigation.

The growing popularity of artificial intelligence approaches has led to their application in a wide range of engineering fields. The most widely used artificial intelligence tool, artificial neural networks, can be used to predict data with high accuracy. An artificial neural network approach is being used to predict effective and accurate thermal conductivity and viscosity models for hybrid nanofluid systems. Here, new types of correlations relating to the thermophysical properties of Fly Ash–Cu nanoparticles with diameter sized 15.2nm and which are temperature-dependent are developed. The highest thermal conductivity and viscosity values were obtained for hybrid nanofluids with a mixture ratio of 20:80, with maximum amplification exceeding 83.2% and 65%, respectively, over the base fluid. The Fly Ash–Cu/water hybrid nanofluid’s viscosity and thermal conductivity are evaluated for a concentration range of 0–4%. The evaluation of the Fly Ash–Cu/water hybrid nanofluids system at concentrations ranging from 0 to 4% most likely entails a scientific or engineering study aimed at understanding the behavior and properties of this nanofluid mixture. Nanoparticles can agglomerate or settle in the base fluid over time, compromising the stability of the nanofluids. Researchers may be interested in determining how varied quantities of Fly Ash and Cu nanoparticles affect the nanofluid’s stability and sedimentation behavior. The heat transfer potential is examined within the optimistic range of temperatures of 30–80^∘C. Many fruitful results for turbulence and solar energy have been drawn. The Mouromtseff number achieved an optimal value for all concentration levels. The heat transfers of turbulent flow and thermal conductivity of hybrid nanofluids increase with the augmented values of concentrations and temperature. Researchers found an increase in thermal conductivity of hybrid nanofluids at 0–4% concentrations, potentially impacting heat transfer applications. The conclusion explores the potential integration of the developed correlations and neural network model into practical engineering or industrial applications involving solar energy and turbulence appliances. In this work, we extend the work of Kanti et al. [Sol. Energy Mater. Sol. Cells 234 (2022) 111423] which is on the properties of water-based fly ash-copper hybrid nanofluid for solar energy applications.