Integration of Semi-Empirical and Artificial Neural Network (ANN) for Modeling Lithium-Ion Electrolyte Systems Dynamic Viscosity

Dynamic viscosity is a key characteristic of electrolyte performance in lithium-ion battery. This work introduces a one parameter semi-empirical model and artificial neural network (ANN) to predict the viscosity of salt-free solvent mixtures and relative viscosity of Li-ion electrolyte solutions (lithium salt + solvent mixture), respectively. Data used in this study were obtained experimentally, in addition to data extracted from literature. There are seven inputs of the ANN model: salt concentration, electrolyte temperature, salt anion size, solvent melting and boiling temperatures, solvent dielectric constant, and solvent dipole moment. Different configuration of the ANN was tested and the configuration with least error was chosen. The results show the capability of the semi-empirical model to predict the viscosity with an overall mean absolute percentage error (MAPE) of 2.05% and 3.17% for binary and tertiary mixtures, respectively. The ANN model predicted the relative viscosity of electrolyte solutions with MAPE of 4.86%. The application of both models in series, resulted predicted the viscosity with MAPE 2.3%, although the ANN MAPE alone is higher than this value. Thus, this work highlights the promise of using predictive models to complement physical approaches and to provide an effective way to perform initial screening on Li-ion electrolytes.

Rise of a bubble through a self-rewetting fluid under the combined influence of gravity-driven convection and Marangoni convection

In this study, the influence of gravity-driven convection and Marangoni convection due to the temperature-dependent surface tension gradient on the rise of an axisymmetric bubble moving in another fluid in a self-rewetting system inside a rectangular tube is studied in the presence and absence of a magnetic field. The axisymmetric bubble (fluid 1) moving in another fluid (fluid 2) is considered immiscible. A two-dimensional cylindrical polar coordinate system has been chosen to present the sketch of the problem. Partial differential equations governing the mentioned flow situations are written and converted into non-dimensional forms and their analytical solutions have been obtained. The deformation in the bubble in the form of its radius and length is simulated. The motion of the droplet is also analysed in the microgravity region by graphing the position of the bubble. The graphical results show that there is a decrease in the contribution of the Marangoni effect and gravitational effect when the magnetic field is increased. In the absence of a magnetic field, the contribution of both the Marangoni effect and gravitational effect decrease on increasing the relative viscosity.

Rheology of three-phase suspensions determined via dam-break experiments

Three-phase suspensions, of liquid that suspends dispersed solid particles and gas bubbles, are common in both natural and industrial settings. Their rheology is poorly constrained, particularly for high total suspended fractions (≳0.5). We use a dam-break consistometer to characterize the rheology of suspensions of (Newtonian) corn syrup, plastic particles and CO 2 bubbles. The study is motivated by a desire to understand the rheology of magma and lava. Our experiments are scaled to the volcanic system: they are conducted in the non-Brownian, non-inertial regime; bubble capillary number is varied across unity; and bubble and particle fractions are 0 ≤ ϕ gas ≤ 0.82 and 0 ≤ ϕ solid ≤ 0.37, respectively. We measure flow-front velocity and invert for a Herschel–Bulkley rheology model as a function of ϕ gas , ϕ solid , and the capillary number. We find a stronger increase in relative viscosity with increasing ϕ gas in the low to intermediate capillary number regime than predicted by existing theory, and find both shear-thinning and shear-thickening effects, depending on the capillary number. We apply our model to the existing community code for lava flow emplacement, PyFLOWGO, and predict increased viscosity and decreased velocity compared with current rheological models, suggesting existing models may not adequately account for the role of bubbles in stiffening lavas.

Molecular interaction investigation of some alkaline earth metal salts in aqueous citric acid at various temperatures by physiochemical studies

Densities, ultrasonic velocity, conductance and viscosity of some alkaline earth metal chlorides such as magnesium chloride (MgCl2) and calcium chloride (CaCl2) were calculated in the concentration range (0.01–0.12 mol kg−1) in 0.01 mol kg−1 aqueous solution of citric acid (CA + H2O) at four varying temperatures T 1 = 303.15 K, T 2 = 308.15 K, T 3 = 313.15 K and T 4 = 318.15 K. The parameters like apparent molar volume (ϕ v ), limiting apparent molar volume ( ϕ v o ${\phi }_{v}^{o}$ ) and transfer volume (Δtr ϕ v o ${\phi }_{v}^{o}$ ) were calculated from density data. Viscosity data have been employed to calculate Falkenhagen coefficient (A), Jone–Dole’s coefficient (B), relative viscosity (η r ), and relaxation time (τ) whereas limiting molar conductance ( Λ m o ${{\Lambda}}_{m}^{o}$ ) has been evaluated from conductance studies. Using these parameters, various type of interactions occurred in the molecules have been discussed. Values of Hepler’s constant (d 2 ϕ v o ${\phi }_{v}^{o}$ /dT 2) p , (dB/dT) and d( Λ m o ${{\Lambda}}_{m}^{o}$ η o )/dT suggests that both MgCl2 and CaCl2 behave as structure breaker in (CA + H2O) system. The positive value of transfer volume exclusively tells about solute–solvent interactions which further indicate that both metal chlorides distort the structure of water and act as structure breaker. These studies are helpful in understanding the nature of interactions occurs in biological systems as CA and metal salts are essential for normal functioning of body.

Thixotropic Behavior in Defining Particle Packing Density of Highly Filled AP/HTPB-Based Propellant

An alarming, asymmetric flame in rocket combustion originates from a composite solid propellant (CSP) containing defects. The defects are the result of a composition that exceeds the maximum particle packing density. Based on the structure analysis of CSP, the addition of plasticizer causes the correlation between the viscosity of CSP slurry and particle packing density to become uncertain. This work aims to investigate the influence of thixotropic behavior on the maximum particle packing density of CSP. A CSP with different thixotropic behavior was successfully produced using aluminum/plasticizer dioctyl adipate (DOA) of 12–24. During the curing process, viscosity and stress–growth were investigated. The structure of the CSP was defined using X-ray radiography. It is remarkably observed that the peak of thixotropy occurred at the 15th minute of the curing process. The particle packing density of CSP can be decisive for the relative viscosity at the peak time of thixotropic behavior. The CSP with the highest relative viscosity at the peak time was revealed to have voids in the upper part of the CSP. Thus, this parameter was proven to change the preceding parameter, viscosity that was measured at the end of mixing. Based on the stress–growth analysis, it is conceivable that the mechanism involves the time-dependent diffusion of DOA in weakening aluminum agglomerates.

A versatile capillaric microfluidics viscometer platform for bar-graph type point-of-care diagnostics

A novel capillary action microfluidic viscometer has been designed that can measure the relative viscosity of a sample compared to a control liquid. Using capillary action circuits, the viscosity of a sample is transformed into a microfluidic bar-graph format without the use of external instrumentation. The bars in this case are represented by the distance that a liquid has flown through a microfluidic channel, relative to another liquid in an identical channel. As the device does not require external instrumentation, its use is targeted at point-of-care (PoC) situations. This implementation is made practical through capillaric Field Effect Transistors, and the conditional flow paths they enable. In this paper, we report on the design, operation, and performance of a two-channel version viscometer device exclusively based on capillary action circuits. Using poly-ethylene glycol solutions as viscous samples, we demonstrate that the device can transduce the relative viscosity consistently to within 2%. Enabled by the flexibility of the capillary action circuits, we additionally present a modified device which can measure transparent liquids without the need to add colorants to the sample. The forms of the device presented in this work have applications in both medical care and scientific measurements—particularly for PoC measurements.

Abstract P422: Sanal Flow Choking Leads To Hemorrhagic Stroke And Other Neurological Disorders In Earth And Human Spaceflight

Background: Evidences are escalating on the diverse neurological disorders associated with COVID-19pandemic due to the nanoscale Sanal-flow-choking (PMC7267099) . The Sanal-flow-chokingoccurs at relatively high and low blood viscosity. Sanal-flow-choking leads to aneurysm andhemorrhagic-stroke and other neurological-disorders if the vessel geometry is having divergence,bifurcation, stenosis and/or occlusion regions (PMC7933821) . Nanoscale Sanal flow choking ismore susceptible at microgravity condition due to altered variations of blood viscosity, turbulenceand the blood pressure ratio (BPR). Astronauts/Cosmonauts experienced neurological disordersduring human spaceflight and thereafter. Methods: Closed-form analytical, in vitro and in silico studies have been carried out for establishing thephenomenon of Sanal-flow-choking. Biofluid/blood heat capacity ratio (BHCR) of various healthysubjects are estimated. Results: The closed-form analytical models reveal that the relatively high and low blood viscosity arerisk factors of Sanal-flow-choking. In vitro study shows that N2, O2, and CO2 gases arepredominant in fresh-blood samples of the healthy human-being and Guinea-pig at a temperaturerange of 37-40 0 C (98.6-104 0 F), which increases the risk of Sanal-flow-choking. In silico resultsshows the Sanal-flow-choking followed by shock-waves and pressure-overshoot in a simulatedartery with the divergence region. Conclusions: As the pressure of the nanoscale biofluid/non-continuum-flows rises, fluid viscosityincreases and average-mean-free-path diminishes and thus, the Knudsen number lowers headingto a zero-slip wall-boundary condition with the compressible flow regime, which increases the riskof Sanal-flow-choking and the shock wave generation causing asymptomatic cardiovasculardisease. Microgravity environment decreases plasma volume and increases the hematocritcompared with the situation on the earth surface, which increases the relative viscosity of bloodcausing an early Sanal-flow-choking. Herein we established that the disproportionate blood-thinning treatment increases the risk of the nanoscale Sanal-flow-choking due to the enhancedboundary-layer-blockage factor. The risk could be diminished by concurrently reducing theviscosity of biofluid/blood and flow-turbulence by increasing thermal-tolerance-level in terms ofBHCR and/or by decreasing the BPR through new drug discovery or using companion medicinewith the traditional blood thinners or other health care management. We recommend allastronauts/cosmonauts should wear ambulatory blood pressure and thermal level monitoringdevices similar to a wristwatch throughout the space travel for the diagnosis, prognosis andprevention of internal flow choking leading to asymptomatic cardiovascular disease includingneurological disorders.

An optimal feed-forward artificial neural network model and a new empirical correlation for prediction of the relative viscosity of Al2O3-engine oil nanofluid

This study presents the design of an artificial neural network (ANN) to evaluate and predict the viscosity behavior of Al2O3/10W40 nanofluid at different temperatures, shear rates, and volume fraction of nanoparticles. Nanofluid viscosity ($${\mu }_{nf}$$ μ nf ) is evaluated at volume fractions ($$\varphi$$ φ =0.25% to 2%) and temperature range of 5 to 55 °C. For modeling by ANN, a multilayer perceptron (MLP) network with the Levenberg–Marquardt algorithm (LMA) is used. The main purpose of this study is to model and predict the $${\mu }_{nf}$$ μ nf of Al2O3/10W40 nanofluid through ANN, select the best ANN structure from the set of predicted structures and manage time and cost by predicting the ANN with the least error. To model the ANN, $$\varphi$$ φ , temperature, and shear rate are considered as input variables, and $${\mu }_{nf}$$ μ nf is considered as output variable. From 400 different ANN structures for Al2O3/10W40 nanofluid, the optimal structure consisting of two hidden layers with the optimal structure of 6 neurons in the first layer and 4 neurons in the second layer is selected. Finally, the R regression coefficient and the MSE are 0.995838 and 4.14469E−08 for the optimal structure, respectively. According to all data, the margin of deviation (MOD) is in the range of less than 2% < MOD < + 2%. Comparison of the three data sets, namely laboratory data, correlation output, and ANN output, shows that the ANN estimates laboratory data more accurately.

Studies on the Interactions of Paracetamol in Water and Binary Solvent Mixtures at T = (298.15–313.15) K: Viscometric and Surface Tension Approach

Temperature, concentration, and solvent conditions have consequences on the formation and dissolution of the drug. Viscometric measurements of paracetamol solutions of different concentrations in 5, 10, and 15% methanol have been made at 298.15, 303.15, 308.15, and 313.15K. Surface tension values (γ) of the solutions were obtained experimentally by using a stalagmometer as well as were derived from the ultrasonic velocity (U) and density (d) values at 298.15 K. The surface tension data have been analyzed using the Gibbs equation to evaluate surface excess (Γ_2). The surface tension and surface excess data obtained by the two different methods are well in accordance. The viscosity (ɳ) data were used to calculate relative viscosity (ɳ_(r ) ), Falkenhagen coefficients (A_(F )), Jone-Dole’s coefficients (B_(J ) ) and chemical potential (μ). The obtained data have been analyzed based on the Jones-Dole equation to know the molecular interactions.