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

Characterisation and modelling of the thermorheological properties of pharmaceutical polymers and their blends using capillary rheometry: Implications for hot melt processing of dosage forms.

Given the growing interest in thermal processing methods, this study describes the use of an advanced rheological technique, capillary rheometry, to accurately determine the thermorheological properties of two pharmaceutical polymers, Eudragit E100 (E100) and hydroxypropylcellulose JF (HPC) and their blends, both in the presence and absence of a model therapeutic agent (quinine, as the base and hydrochloride salt). Furthermore, the glass transition temperatures (Tg) of the cooled extrudates produced using capillary rheometry were characterised using Dynamic Mechanical Thermal Analysis (DMTA) thereby enabling correlations to be drawn between the information derived from capillary rheometry and the glass transition properties of the extrudates. The shear viscosities of E100 and HPC (and their blends) decreased as functions of increasing temperature and shear rates, with the shear viscosity of E100 being significantly greater than that of HPC at all temperatures and shear rates. All platforms were readily processed at shear rates relevant to extrusion (approximately 200–300 s−1) and injection moulding (approximately 900 s−1). Quinine base was observed to lower the shear viscosities of E100 and E100/HPC blends during processing and the Tg of extrudates, indicative of plasticisation at processing temperatures and when cooled (i.e. in the solid state). Quinine hydrochloride (20% w/w) increased the shear viscosities of E100 and HPC and their blends during processing and did not affect the Tg of the parent polymer. However, the shear viscosities of these systems were not prohibitive to processing at shear rates relevant to extrusion and injection moulding. As the ratio of E100:HPC increased within the polymer blends the effects of quinine base on the lowering of both shear viscosity and Tg of the polymer blends increased, reflecting the greater solubility of quinine within E100. In conclusion, this study has highlighted the importance of capillary rheometry in identifying processing conditions, polymer miscibility and plasticisation phenomena.

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.

The microtubule targeting agent PBOX-15 inhibits integrin-mediated cell adhesion and induces apoptosis in acute lymphoblastic leukaemia cells

Although recent decades have seen an improved cure rate for newly diagnosed paediatric acute lymphoplastic leukaemia (ALL), the treatment options for adult ALL, T-cell ALL (T-ALL) and relapsed disease remain poor. We have developed a novel series of pyrrolo-1,5-benzoxazepine (PBOX) compounds and established their anticancer efficacy in a variety of human tumour cell types. Here, we demonstrate that PBOX-15 inhibits cell growth, and induces G2/M cell cycle arrest and apoptosis in both T-ALL and B-cell ALL (B-ALL) cells. In addition, prior to PBOX-15-induced apoptosis, PBOX-15 decreases ALL cell adhesion, spreading and migration. Concurrently, PBOX-15 differentially down-regulates β1-, β2- and α4-integrin expression in ALL cells and significantly decreases integrin-mediated cell attachment. PBOX-15 interferes with the lateral mobility and clustering of integrins in both B-ALL and T-ALL cells. These data suggest that PBOX-15 is not only effective in inducing apoptosis in ALL cells, but also has the potential to disrupt integrin-mediated adhesion of malignant lymphocytes, which represents a novel avenue for regulating leukaemic cell homing and migration.

The vascular targeting agent combretastatin-A4 and a novel cis-Restricted {beta}-Lactam Analogue, CA-432, induce apoptosis in human chronic myeloid leukemia cells and ex vivo patient samples including those displaying multidrug resistance

Combretastatin-A4 (CA-4) is a natural derivative of the African willow tree Combretum caffrum. CA-4 is one of the most potent antimitotic components of natural origin, but it is, however, intrinsically unstable. A novel series of CA-4 analogs incorporating a 3,4-diaryl-2-azetidinone (β-lactam) ring were designed and synthesized with the objective to prevent cis -trans isomerization and improve the intrinsic stability without altering the biological activity of CA-4. Evaluation of selected β-lactam CA-4 analogs demonstrated potent antitubulin, antiproliferative, and antimitotic effects in human leukemia cells. A lead β-lactam analog, CA-432, displayed comparable antiproliferative activities with CA-4. CA-432 induced rapid apoptosis in HL-60 acute myeloid leukemia cells, which was accompanied by depolymerization of the microtubular network, poly(ADP-ribose) polymerase cleavage, caspase-3 activation, and Bcl-2 cleavage. A prolonged G(2)M cell cycle arrest accompanied by a sustained phosphorylation of mitotic spindle checkpoint protein, BubR1, and the antiapoptotic proteins Bcl-2 and Bcl-x(L) preceded apoptotic events in K562 chronic myeloid leukemia (CML) cells. Molecular docking studies in conjunction with comprehensive cell line data rule out CA-4 and β-lactam derivatives as P-glycoprotein substrates. Furthermore, both CA-4 and CA-432 induced significantly more apoptosis compared with imatinib mesylate in ex vivo samples from patients with CML, including those positive for the T315I mutation displaying resistance to imatinib mesylate and dasatinib. In summary, synthetic intrinsically stable analogs of CA-4 that display significant clinical potential as antileukemic agents have been designed and synthesized.

STI-571 (imatinib mesylate) enhances the apoptotic efficacy of pyrrolo-1,5-benzoxazepine-6, a novel microtubule-targeting agent, in both STI-571-sensitive and -resistant Bcr-Abl-positive human chronic myeloid leukemia cells

Interactions between the Bcr-Abl kinase inhibitor STI-571 (imatinib mesylate) and a novel microtubule-targeting agent (MTA), pyrrolo-1,5-benzoxazepine (PBOX)-6, were investigated in STI-571-sensitive and -resistant human chronic myeloid leukemia (CML) cells. Cotreatment of PBOX-6 with STI-571 induced significantly more apoptosis in Bcr-Abl-positive CML cell lines (K562 and LAMA-84) than either drug alone (P < 0.01). Cell cycle analysis of propidium iodide-stained cells showed that STI-571 significantly reduced PBOX-6-induced G2M arrest and polyploid formation with a concomitant increase in apoptosis. Similar results were obtained in K562 CML cells using lead MTAs (paclitaxel and nocodazole) in combination with STI-571. Potentiation of PBOX-6-induced apoptosis by STI-571 was specific to Bcr-Abl-positive leukemia cells with no cytoxic effects observed on normal peripheral blood cells. The combined treatment of STI-571 and PBOX-6 was associated with the down-regulation of Bcr-Abl and repression of proteins involved in Bcr-Abl transformation, namely the antiapoptotic proteins Bcl-x(L) and Mcl-1. Importantly, PBOX-6/STI-571 combinations were also effective in STI-571-resistant cells. Together, these findings highlight the potential clinical benefits in simultaneously targeting the microtubules and the Bcr-Abl oncoprotein in STI-571-sensitive and -resistant CML cells.

Selecting the best targeted agent in first-line treatment of unresectable liver metastases from colorectal cancer:does the bench have the answers?

For physicians facing patients with organ-limited metastases from colorectal cancer, tumor shrinkage and sterilization of micrometastatic disease is the main goal, giving the opportunity for secondary surgical resection. At the same time, for the majority of patients who will not achieve a sufficient tumor response, disease control remains the predominant objective. Since FOLFOX or FOLFIRI have similar efficacies, the challenge is to define which could be the most effective targeted agent (anti-EGFR or anti-VEGF) to reach these goals. Therefore, a priori molecular identification of patients that could benefit from anti-EGFR or anti-VEGF monoclonal antibodies (i.e. the currently approved targeted therapies for metastatic colorectal cancer) is of critical importance. In this setting, the KRAS mutation status was the first identified predictive marker of response to anti-EGFR therapy. Since it has been demonstrated that tumors with KRAS mutation do not respond to anti-EGFR therapy, KRAS status must be determined prior to treatment. Thus, for KRAS wild-type patients, the choices that remain are either anti-VEGF or anti-EGFR. In this review, we present the most updated data from translational research programs dealing with the identification of biomarkers for response to targeted therapies.

Shape stabilised phase change materials based on a high melt viscosity HDPE and paraffin waxes

Shape stabilised phase change materials (SSPCMs) based on a high density poly(ethylene)(hv-HDPE) with high (H-PW, Tm = 56–58 °C) and low (L-PW, Tm = 18–23 °C) melting point paraffin waxes were readily prepared using twin-screw extrusion. The thermo-physical properties of these materials were assessed using a combination of techniques and their suitability for latent heat thermal energy storage (LHTES) assessed. The melt processing temperature (160 °C) of the HDPE used was well below the onset of thermal decomposition of H-PW (220 °C), but above that for L-PW (130 °C), although the decomposition process extended over a range of 120 °C and the residence time of L-PW in the extruder was <30 s. The SSPCMs prepared had latent heats up to 89 J/g and the enthalpy values for H-PW in the respective blends decreased with increasing H-PW loading, as a consequence of co-crystallisation of H-PW and hv-HDPE. Static and dynamic mechanical analysis confirmed both waxes have a plasticisation effect on this HDPE. Irrespective of the mode of deformation (tension, flexural, compression) modulus and stress decreased with increased wax loading in the blend, but the H-PW blends were mechanically superior to those with L-PW.

Automating fault tolerance in high-performance computational biological jobs using multi-agent approaches

Background: Large-scale biological jobs on high-performance computing systems require manual intervention if one or more computing cores on which they execute fail. This places not only a cost on the maintenance of the job, but also a cost on the time taken for reinstating the job and the risk of losing data and execution accomplished by the job before it failed. Approaches which can proactively detect computing core failures and take action to relocate the computing core's job onto reliable cores can make a significant step towards automating fault tolerance. Method: This paper describes an experimental investigation into the use of multi-agent approaches for fault tolerance. Two approaches are studied, the first at the job level and the second at the core level. The approaches are investigated for single core failure scenarios that can occur in the execution of parallel reduction algorithms on computer clusters. A third approach is proposed that incorporates multi-agent technology both at the job and core level. Experiments are pursued in the context of genome searching, a popular computational biology application. Result: The key conclusion is that the approaches proposed are feasible for automating fault tolerance in high-performance computing systems with minimal human intervention. In a typical experiment in which the fault tolerance is studied, centralised and decentralised checkpointing approaches on an average add 90% to the actual time for executing the job. On the other hand, in the same experiment the multi-agent approaches add only 10% to the overall execution time