Search

Alkali-activated aluminosilicate (N-A-S–H) gels are models for understanding structure formation in sustainable cement alternatives known as geopolymers. Temporal measurements of elastic shear moduli development of these aluminosilicate gels show systematic trends in kinetics with respect to silicon to aluminum (Si/Al) ratio. This behavior can be reduced to a single master curve when nondimensionalized with the Si/Al-dependent gel time and equilibrium modulus. An autocatalytic reaction model and Avrami model fit the master curve well. The Avrami exponent is 1.5, consistent with the nucleation and growth steps separately modeled in the autocatalytic reaction model, and further is within the expected values for diffusion-limited growth suggested from independent measurements of the structural fractal dimension by neutron scattering. These results unifying rheokinetic behavior over a range of gel compositions suggest a common underlying microstructure development in such gels and the possibility of developing predictive models for property development in geopolymers more broadly. An autocatalytic reaction kinetic model describing nucleation and growth is fit to the evolution of the storage modulus, G', of alkali-activated aluminosilicate gels with varying concentration of aluminum ( S i / A l / N a = 2 / n Al / 1.5 ). A master curve is constructed by nondimensionalizing the timescale and storage modulus of each dataset. [ABSTRACT FROM AUTHOR]

Hemorheology is the study of blood flow and the mechanical stresses and kinematics involved. The Casson constitutive equation is a popular and simple model used to describe the steady shear rheology of blood, with only two parameters that specify an infinite shear viscosity and a yield stress that depend on blood physiology. Previous literature has identified hematocrit and fibrinogen concentration as the two most important physiological factors that affect blood flow, but previous parameterizations of the Casson model may not be reliable due to the use of non-standardized data sets. This study uses machine learning and the largest standardized dataset to improve the parameterization of the Casson model with respect to hematocrit and fibrinogen concentration for healthy individuals. The study also employs machine learning to identify a potential additional factor, the mean corpuscular hemoglobin (MCH), that may affect blood rheology. The proposed approach demonstrates the potential for machine learning to improve the connection between physiology and blood rheology with possible implications in cardiovascular diagnostics. [ABSTRACT FROM AUTHOR]

The split Hopkinson pressure bar (SHPB) technique is implemented to evaluate the transient response of a colloidal suspension exhibiting shear thickening at strain rates and timescales never before explored in a laboratory instrument. These suspensions are shown to exhibit a discontinuous transition from fluid-like (shear thinning) to solid-like (shear thickening) behavior when evaluated using rotational rheometry. The effect of loading rate on this transition time is studied for a particle volume fraction of 0.54 using the SHPB technique. It is shown that the time required for transition to occur decreases logarithmically with loading rate. From these results, we conclude that transition is not triggered by a characteristic shear rate, but rather a critical shear strain is required. Results from SHPB experiments performed up to Peclet numbers of order 107 are presented and discussed for 0.50, 0.52, and 0.54 particle volume fraction suspensions. [ABSTRACT FROM AUTHOR]

Dense colloidal suspensions are processed in a wide variety of industries. Challenges for pumping suspensions and slurries at high concentrations include shear thickening and dilation, which can have deleterious consequences. These systems are shear sensitive close to the jamming point, meaning that a significant increase in high shear viscosity can be observed with just a few percent change in volume fractions. Therefore, accurate and rapid determination of the jamming point can greatly aid formulation. Typically, conventional rheometry identifies the jamming point by a time-consuming process, whereby multiple flow curves of suspensions of different volume fraction are measured and extrapolated to the volume fraction where the viscosity diverges. We present an alternative approach for rapid, one-step, experimental determination of the jamming point for aqueous suspensions. The procedure monitors the shear stress under constant shear stress or shear rate as the sample is dewatered using immobilization cell rheometry, until the viscosity diverges. The method is validated by comparing the results of this work with conventional rheometry for a model suspension. Then it is applied to examine the effect of grafting a short-chain polymer to particles, comprising an industrial suspension of silica-coated titania. Polymeric coating of the particles increases the jamming concentration and mitigates shear thickening, qualitatively consistent with predictions from simulations. [ABSTRACT FROM AUTHOR]

Experimental measurements of non-colloidal multimodal suspension viscosities are performed over a wide range of mixing ratios and used to test the robustness and predictive capability of a recent viscosity model (Mwasame et al. in Phys Fluids 28:061701, 2016b), subsequently referred to as the MWB model. Three unimodally distributed particle suspensions with narrow size distributions are blended to make the bimodal and trimodal suspensions used in the rheological experiments. We demonstrate how predictions for mixture viscosities can be made using the MWB model only requiring the volume-weighted average particle sizes and viscosity correlations of the individual unimodal suspensions comprising the blend. The resultant model predictions are found to be in good agreement with measured bimodal and trimodal viscosity data to within expected experimental uncertainty. The datasets provided here can be used to validate future modeling efforts, and the MWB model can be used to optimize the viscosity of multimodal suspension mixtures for specific performance criteria. [ABSTRACT FROM AUTHOR]

The rheological characterization of a model, nearly ideal thixotropic carbon black suspension first proposed by Dullaert and Mewis (JNNFM 139: 21-30, 2006) is extended to include large amplitude oscillatory shear (LAOS) flow, shear flow reversal, and unidirectional LAOS flow (UD-LAOS). We show how this broader data set is useful for validating and improving constitutive models of thixotropy. We apply this new data to further test a recently developed structure-kinetics model, the Modified Delaware Thixotropy Model (Armstrong et al., J Rheol. 60: 433-450, 2016a), as well as to better understand the microstructural basis and validity of strain-rate superposition methods proposed for soft solids. This comparison identifies the limitations of models based on a scalar description of microstructure, which cannot fully capture the reversal of flow directionality inherent in LAOS flow. Further, we use the model to identify a possible microstructural justification for the hypothesized technique of strain-rate frequency superposition in soft solids. [ABSTRACT FROM AUTHOR]