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.

Oxygen vacancy formation in CeO2 and Ce1-xZrxO2 solid solutions:electron localization, electrostatic potential and structural relaxation

Ceria (CeO2) and ceria-based composite materials, especially Ce1-xZrxO2 solid solutions, possess a wide range of applications in many important catalytic processes, such as three-way catalysts, owing to their excellent oxygen storage capacity (OSC) through the oxygen vacancy formation and refilling. Much of this activity has focused on the understanding of the electronic and structural properties of defective CeO2 with and without doping, and comprehending the determining factor for oxygen vacancy formation and the rule to tune the formation energy by doping has constituted a central issue in material chemistry related to ceria. However, the calculation on electronic structures and the corresponding relaxation patterns in defective CeO2-x oxides remains at present a challenge in the DFT framework. A pragmatic approach based on density functional theory with the inclusion of on-site Coulomb correction, i.e. the so-called DFT + U technique, has been extensively applied in the majority of recent theoretical investigations. Firstly, we review briefly the latest electronic structure calculations of defective CeO2(111), focusing on the phenomenon of multiple configurations of the localized 4f electrons, as well as the discussions of its formation mechanism and the catalytic role in activating the O-2 molecule. Secondly, aiming at shedding light on the doping effect on tuning the oxygen vacancy formation in ceria-based solid solutions, we summarize the recent theoretical results of Ce1-xZrxO2 solid solutions in terms of the effect of dopant concentrations and crystal phases. A general model on O vacancy formation is also discussed; it consists of electrostatic and structural relaxation terms, and the vital role of the later is emphasized. Particularly, we discuss the crucial role of the localized structural relaxation patterns in determining the superb oxygen storage capacity in kappa-phase Ce1-xZr1-xO2. Thirdly, we briefly discuss some interesting findings for the oxygen vacancy formation in pure ceria nanoparticles (NPs) uncovered by DFT calculations and compare those with the bulk or extended surfaces of ceria as well as different particle sizes, emphasizing the role of the electrostatic field in determining the O vacancy formation.

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

Assessment of Atomic Data: Problems and Solutions

For the reliable analysis and modeling of astrophysical, laser-produced, and fusion plasmas, atomic data are required for a number of parameters, including energy levels, radiative rates, and electron impact excitation rates. Such data are desired for a range of elements (H to W) and their many ions. However, measurements of atomic data, mainly for radiative and excitation rates, are not feasible for many species, and therefore, calculations are needed. For some ions (such as of C, Fe, and Kr), there is a variety of calculations available in the literature, but often, they differ significantly from one another. Therefore, there is a great demand from the user community to have data "assessed" for accuracy so that they can be confidently applied to the modeling of plasmas. In this paper we highlight the difficulties in assessing atomic data and offer some solutions for improving the accuracy of calculated results.

A comparative study on the thermophysical properties for two bis[(trifluoromethyl)sulfonyl]imide-based ionic liquids containing the trimethyl-sulfonium or the trimethyl-ammonium cation in molecular solvents

Herein, we present a comparative study of the thermophysical properties of two homologous ionic liquids, namely, trimethyl-sulfonium bis[(trifluoromethyl) sulfonyl]imide, [S₁₁₁][TFSI], and trimethyl-ammonium bis[(trifluoromethyl)sulfonyl]imide, [HN₁₁₁][TFSI], and their mixtures with propylene carbonate, acetonitrile, or gamma butyrolactone as a function of temperature and composition. The influence of solvent addition on the viscosity, conductivity, and thermal properties of IL solutions was studied as a function of the solvent mole fraction from the maximum solubility of IL, x_s, in each solvent to the pure solvent. In this case, x_s is the composition corresponding to the maximum salt solubility in each liquid solvent at a given temperature from 258.15 to 353.15 K. The effect of temperature on the transport properties of each binary mixture was then investigated by fitting the experimental data using Arrhenius' law and the Vogel-Tamman-Fulcher (VTF) equation. The experimental data shows that the residual conductivity at low temperature, e.g., 263.15 K, of each binary mixture is exceptionally high. For example, conductivity values up to 35 and 42 mS·cm^-1 were observed in the case of the [S ₁₁₁][TFSI] + ACN and [HN₁₁₁][TFSI] + ACN binary mixtures, respectively. Subsequently, a theoretical approach based on the conductivity and on the viscosity of electrolytes was formulated by treating the migration of ions as a dynamical process governed by ion-ion and solvent-ion interactions. Within this model, viscosity data sets were first analyzed using the Jones-Dole equation. Using this theoretical approach, excellent agreement was obtained between the experimental and calculated conductivities for the binary mixtures investigated at 298.15 K as a function of the composition up to the maximum solubility of the IL. Finally, the thermal characterization of the IL solutions, using DSC measurements, showed a number of features corresponding to different solid-solid phase transitions, T_S-S, with extremely low melting entropies, indicating a strong organizational structure by easy rotation of methyl group. These ILs can be classified as plastic crystal materials and are promising as ambient-temperature solid electrolytes. © 2013 American Chemical Society.

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.

Influence of phosphate on the arsenic uptake by wheat (Triticum durum L.) irrigated with arsenic solutions at three different concentrations

In this study we have investigated the uptake and distribution of arsenic (As) and phosphate (P_i) in roots, shoots, and grain of wheat grown in an uncontaminated soil irrigated with solutions containing As at three different concentrations (0.5, 1 and 2 mg l^-1) and in the presence or in the absence of P fertilization. Arsenic in irrigation water reduced plants growth and decreased grain yield. When P_i was not added (P-), plants were more greatly impacted compared to the plus P_i (P+) treatments. The differences in mean biomass between P- and P+ treatments at the higher As concentrations demonstrated the role of P_i in preventing As toxicity and growth inhibition. Arsenic concentrations in root, shoot and grain increased with increasing As concentration in irrigation water. It appears that P fertilization minimizes the translocation of As to the shoots and grain whilst enhancing P status of plant. The observation that P fertilization minimises the translocation of arsenic to the shoots and grain is interesting and may be useful for certain regions of the world that has high levels of As in groundwater or soils. © 2008 Springer Science+Business Media B.V.

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.