Biomechanics of Vertebroplasty: Effect of Cement Viscosity on Mechanical Behaviour

Vertebroplasty is a minimally invasive surgical procedure, which requires efficacious percutaneous cement delivery via a cannulated needle to restore the strength and stiffness in osteoporotic vertebral bodies. Cement viscosity is understood to influence the injectability, cohesion and cement retention within the vertebral body. Altering the liquid to powder ratio modifies the viscosity of bone cement; however, the cement viscosity-response association between cement fill and augmentation of strength and stiffness is unknown. The aim of this study was to determine the relationship between viscosity, cement fill and the potential augmentation of strength and stiffness in an open pore foam structure that was representative of osteoporotic cancellous bone using an in vitro prophylactic vertebroplasty model. The results showed a strong linear correlation between compressive strength and stiffness augmentation with percentage cement fill, the extent of which was strongly dependent on the cement viscosity. Significant forces were required to ensure maximum delivery of the high viscosity cement using a proprietary screw-driven cement delivery technology. These forces could potentially exceed the normal human physical limit. Similar trends were observed when comparing the results from this study and previously reported cadaveric and animal based in vitro models.

Comparative study on transport properties for LiFAP and LiPF6 in alkyl-carbonates as electrolytes through conductivity, viscosity and NMR self-diffusion measurements

We present in this work a comparative study on density and transport properties, such as the conductivity (sigma), viscosity (eta) and self-diffusion coefficients (D), for electrolytes based on the lithium hexafluorophosphate, LiPF6; or on the lithium tris(pentafluoroethane)-trifluorophosphate, LiFAP dissolved in a binary mixture of ethylene carbonate (EC) and dimethylcarbonate (DMC) (50:50 wt%). For each electrolyte, the temperature dependence on transport properties over a temperature range from 10 to 80 degrees C and 20 to 70 degrees C for viscosity and conductivity, respectively, exhibits a non-Arrhenius behavior. However, this dependence is correctly correlated by using the Vogel-Tamman-Fulcher (VTF) type fitting equation. In each case, the best-fit parameters, such as the pseudo activation energy and ideal glass transition temperature were then extracted. The self-diffusion coefficients (D) of the Li+ cation and PF6- or FAP(-) anions species, in each studied electrolyte, were then independently determined by observing Li-3, F-19 and P-31 nuclei with the pulsed-gradient spin-echo (PGSE) NMR technique over the same temperature range from 20 to 80 degrees C. Results show that even if the diffusion of the lithium cation is quite similar in both electrolytes, the anions diffusion differs notably. In the case of the LiPF6-based electrolyte, for example at T approximate to 75 degrees C (high temperature), the self-diffusion coefficients of Li+ cations in solution (D (Li+)approximate to 5 x 10(-19) m(2) s(-1)) is 1.6 times smaller than that of PF6- anions (D (PF6-) = 8.5 x 10(-19) m(2) s(-1)), whereas in the case of the LiFAP-based electrolyte, FAP(-) anions diffuse at same rate as the Li+ cations (D (FAP(-)) = 5 x 10(-1) m(2) s(-1)). Based on these experimental results, the transport mobility of ions were then investigated through Stokes-Einstein and Nernst-Einstein equations to determine the transport number of lithium t(Li)(+), effective radius of solvated Li+ and of PF6- and FAP(-) anions, and the degree of dissociation of these lithium salts in the selected EC/DMC (50:50 wt%) mixture over a the temperature range from 20 to 80 degrees C. This study demonstrates the conflicting nature of the requirements and the advantage of the well-balanced properties as ionic mobility and dissociation constant of the selected electrolytes. (C) 2013 Elsevier Ltd. All rights reserved.

Real time measurement and control of viscosity for extrusion processes using recycled materials

The aim of this paper is to develop a new generation of extruder control system for recycled materials which has ability to automatically maintain constant a polymer melt viscosity of mixed recycled polymers during extrusion, regardless of variations in the Melt Flow Index (MFI) of recycled mixed grade high density polyethylene (HDPE) feedstock. The variations in MFI are due to differences in the source of the recycled material used. The work describes how melt viscosity for specific extruder/die system is calculated in real time using the rheological properties of the materials, the pressure drop through the extruder die and the actual throughput measurements using a gravimetric loss-in-weight hopper feeder. A closed-loop controller is also developed to automatically regulate screw speed and barrel temperature profile to achieve constant viscosity and enable consistent processing of variable grade recycled HDPE materials. Such a system will improve processability of mixed MFI polymers may also reduce the risk of polymer melt degradation, reduce producing large volumes of scrap/waste and lead to improvement in product quality. The experimental results of real time viscosity measurement and control using a 38 mm single screw extruder with different recycled HDPEs with widely different MFIs are reported in this work.

Viscosity and Carbon Dioxide Solubility for LiPF6, LiTFSI, and LiFAP in Alkyl Carbonates: Lithium Salt Nature and Concentration Effect

A Soft Sensor for Viscosity Control of Polymer Extrusion

Viscosity represents a key indicator of product quality in polymer extrusion but has traditionally been difficult to measure in-process in real-time. An innovative, yet simple, solution to this problem is proposed by a Prediction-Feedback observer mechanism. A `Prediction' model based on the operating conditions generates an open-loop estimate of the melt viscosity; this estimate is used as an input to a second, `Feedback' model to predict the pressure of the system. The pressure value is compared to the actual measured melt pressure and the error used to correct the viscosity estimate. The Prediction model captures the relationship between the operating conditions and the resulting melt viscosity and as such describes the specific material behavior. The Feedback model on the other hand describes the fundamental physical relationship between viscosity and extruder pressure and is a function of the machine geometry. The resulting system yields viscosity estimates within 1% error, shows excellent disturbance rejection properties and can be directly applied to model-based control. This is of major significance to achieving higher quality and reducing waste and set-up times in the polymer extrusion industry.

Viscosity Control for Extrusion Processes Using Recycled Polymers

The aim of this paper is to develop a new extruder control system for recycled materials which has ability to automatically maintain constant a polymer melt viscosity of mixed recycled polymers during extrusion, regardless of variations in the Melt Flow Index (MFI) of recycled mixed grade high density polyethylene (HDPE) feedstock. A closed-loop controller is developed to automatically regulate screw speed and barrel temperature profile to achieve constant viscosity and enable consistent processing of variable grade recycled HDPE materials. The experimental results of real time viscosity measurement and control using a 38mm single screw extruder with different recycled HDPEs with widely different MFIs are reported in this work

The effect of melt viscosity on thermal efficiency for single screw extrusion of HDPE

In this work, a highly instrumented single screw extruder has been used to study the effect of polymer rheology on the thermal efficiency of the extrusion process. Three different molecular weight grades of high density polyethylene (HDPE) were extruded at a range of conditions. Three geometries of extruder screws were used at several set temperatures and screw rotation speeds. The extruder was equipped with real-time quantification of energy consumption; thermal dynamics of the process were examined using thermocouple grid sensors at the entrance to the die. Results showed that polymer rheology had a significant effect on process energy consumption and thermal homogeneity of the melt. Highest specific energy consumption and poorest homogeneity was observed for the highest viscosity grade of HDPE. Extruder screw geometry, set extrusion temperature and screw rotation speed were also found to have a direct effect on energy consumption and melt consistency. In particular, specific energy consumption was lower using a barrier flighted screw compared to single flighted screws at the same set conditions. These results highlight the complex nature of extrusion thermal dynamics and provide evidence that rheological properties of the polymer can significantly influence the thermal efficiency of the process.

Artificial Neural Network for Compositional Ionic Liquid Viscosity Prediction

Being a new generation of green solvents and high-tech reaction media of the future, ionic liquids have increasingly attracted much attention. Of particular interest in this context are room temperature ionic liquids (in short as ILs in this paper). Due to the relatively high viscosity, ILs is expected to be used in the form of solvent diluted mixture with reduced viscosity in industrial application, where predicting the viscosity of IL mixture has been an important research issue. Different IL mixture and many modelling approaches have been investigated. The objective of this study is to provide an alternative model approach using soft computing technique, i.e., artificial neural network (ANN) model, to predict the compositional viscosity of binary mixtures of ILs [C _n-mim][NTf ₂] with n=4, 6, 8, 10 in methanol and ethanol over the entire range of molar fraction at a broad range of temperatures from T=293.0-328.0K. The results show that the proposed ANN model provides alternative way to predict compositional viscosity successfully with highly improved accuracy and also show its potential to be extensively utilized to predict compositional viscosity taking account of IL alkyl chain length, as well as temperature and compositions simultaneously, i.e., more complex intermolecular interactions between components in which it would be hard or impossible to establish the analytical model. This illustrates the potential application of ANN in the case that the physical and thermodynamic properties are highly non-linear or too complex. © 2012 Copyright the authors.

Artificial neural network model to predict compositional viscosity over a broad range of temperatures

The objective of this study is to provide an alternative model approach, i.e., artificial neural network (ANN) model, to predict the compositional viscosity of binary mixtures of room temperature ionic liquids (in short as ILs) [C _n-mim] [NTf ₂] with n=4, 6, 8, 10 in methanol and ethanol over the entire range of molar fraction at a broad range of temperatures from T=293.0328.0K. The results show that the proposed ANN model provides alternative way to predict compositional viscosity successfully with highly improved accuracy and also show its potential to be extensively utilized to predict compositional viscosity over a wide range of temperatures and more complex viscosity compositions, i.e., more complex intermolecular interactions between components in which it would be hard or impossible to establish the analytical model. © 2010 IEEE.

A Correlation between the Dynamic Viscosity and Crystallisation of Felodipine from its Amorphous Polymer Solid Dispersion

Purpose Previously, it has been reported that molecular mobility determines the rate of molecular approach to crystal surfaces, while entropy relates to the probability of that approaching molecule having the desirable configuration for further growth of the existing crystal; and the free energy dictates the probability of that molecule not returning to the liquid phase1. If we plot the crystal growth rate and viscosity of a supercooled liquid in a log-log format, the relationship between the two is linear, indicating the influence viscosity has upon crystal growth rate. However, such approximation has been derived from pure drug compounds and it is apparent that further understanding of crystallization from drug-polymer solid dispersion is required in order to stabilise drugs embedded within amorphous polymeric solid dispersions. Methods Mixtures of felodipine and polymer (HPMCAS-HF, PVPK15 and Soluplus®) at specified compositions were prepared using a Restch MM200 ball mill. To examine crystal growth within amorphous solid dispersions, samples were prepared by melting 5-10 mg of ball milled mixture at 150°C for 3-5 minutes on a glass slip pre-cleaned with methanol and acetone. All prepared samples were confirmed to be crystal free by visual observation using a polarised light microscope (Olympus BX50). Prepared samples were stored at 0% RH (P2O5), inside desiccators, maintained in ovens at 80°C. For the dynamic viscosity measurement, approximately 100-200mg ball milled mixture was heated on the base plate of a rotational rheometer at 150°C for 5 minutes and the top plate was lowered to a defined gap to form a good contact with the material. The sandwiched amorphous material was heated to 80°C and the viscosity was measured. Results The equation was used to probe the correlation of viscosity to crystal growth rate. In comparison to the value of xi in log-log equation reported from pure drug compound, a value of 1.63 was obtained for FD-polymer solid dispersions irrespective of the polymer involved. &#8733 Conclusion The high xi value suggests stronger viscosity dependence may exist for amorphous FD once incorporated with amorphous polymer.