Nano-reactors for controlling the selectivity of the free radical grafting of maleic anhydride onto polypropylene in the melt

This paper reports on a successful application of the concept of nanoreactors to effectively controlling the selectivity of the free radical grafting of maleic anhydride (MAH) onto polypropylene (PP) in the melt, an industrially relevant process. More specifically, a free radical initiator of type ROOR was first confined into (or encapsulated by) the galleries of an organically modified montmorillonite (o-MMT) whose interdistance was 2.4 nm. Primary free radicals (RO center dot) formed inside the o-MMT galleries had to diffuse out before they could react with the PP backbone. The controlled release of the primary free radicals significantly increased the grafting degree of MAH onto PP and greatly reduced the level of the chain scission of the latter. Those results were better understood by electron spin resonance studies on model systems and by Monte Carlo simulations.

The rheological and extrusion behaviour of blends based on phenolphthalein poly(ether-ether-sulfone) and thermotropic liquid crystalline polymer

A novel engineering thermoplastic, phenolphthalein poly (ether-ether-sulfone) (PES-C) was blended with a commercial thermotropic liquid crystalline polymer(TLCP), Vectra A950, up to 30 weight percent of TLCP. A rheometrics dynamic spectrometer (RDS-I) and a CEAST capillary rheometer, a rheoscope 1000 were employed to investigate the melt rheology and extrusion behaviour at both the low and high shearing rates. The morphologies of the blends under different shearing were observed with a scanning electron microscope(SEM) and correlated to the observed rheology. The principal normal stress differences measured with cone-and-plate geometry give a temperature-independent correlation for both blend and PES-C when they are plotted against shear stress. But the extrudate swell of the blends showed a strong temperature dependence at each shear stress. The concentration dependence of extrudate swell shows a contrary behaviour to that of the inorganic filled system. A reasonable hypothesis based on the relaxation and disorientation of TLCP during flowing in the capillary and exiting was given to explain it. The melt fracture was checked after extrusion from capillary and was discussed.

The inferential monitoring of the screw disturbance torque to predict process fluctuations in polymer extrusion

Polymer extrusion is one of the major methods of processing polymer materials and advanced process monitoring is important to ensure good product quality. However, commonly used process monitoring devices, e.g. temperature and pressure sensors, are limited in providing information on process dynamics inside an extruder barrel. Screw load torque dynamics, which may occur due to changes in solids conveying, melting, mixing, melt conveying, etc., are believed to be a useful indicator of process fluctuations inside the extruder barrel. However, practical measurement of the screw load torque is difficult to achieve. In this work, inferential monitoring of the screw load torque signal in an extruder was shown to be possible by monitoring the motor current (armature and/or field) and simulation studies were used to check the accuracy of the proposed method. The ability of this signal to aid identification and diagnosis of process issues was explored through an experimental investigation. Power spectral density and wavelet frequency analysis were implemented together with a covariance analysis. It was shown that the torque signal is dominated by the solid friction in the extruder and hence it did not correlate well with melting fluctuations. However, it is useful for online identification of solids conveying issues.

Extruder Melt Temperature Control with Fuzzy Logic

In polymer extrusion, the delivery of a melt which is homogenous in composition and temperature is paramount for achieving high quality extruded products. However, advancements in process control are required to reduce temperature variations across the melt flow which can result in poor product quality. The majority of thermal monitoring methods provide only low accuracy point/bulk melt temperature measurements and cause poor controller performance. Furthermore, the most common conventional proportional-integral-derivative controllers seem to be incapable of performing well over the nonlinear operating region. This paper presents a model-based fuzzy control approach to reduce the die melt temperature variations across the melt flow while achieving desired average die melt temperature. Simulation results confirm the efficacy of the proposed controller.

A new model based approach for the prediction and optimisation of thermal homogeneity in single screw extrusion

In polymer extrusion, delivery of a melt which is homogenous in composition and temperature is important for good product quality. However, the process is inherently prone to temperature fluctuations which are difficult to monitor and control via single point based conventional thermo- couples. In this work, the die melt temperature profile was monitored by a thermocouple mesh and the data obtained was used to generate a model to predict the die melt temperature profile. A novel nonlinear model was then proposed which was demonstrated to be in good agreement with training and unseen data. Furthermore, the proposed model was used to select optimum process settings to achieve the desired average melt temperature across the die while improving the temperature homogeneity. The simulation results indicate a reduction in melt temperature variations of up to 60%.

Dynamic grey-box modeling for online monitoring of extrusion viscosity

Melt viscosity is a key indicator of product quality in polymer extrusion processes. However, real time monitoring and control of viscosity is difficult to achieve. In this article, a novel “soft sensor” approach based on dynamic gray-box modeling is proposed. The soft sensor involves a nonlinear finite impulse response model with adaptable linear parameters for real-time prediction of the melt viscosity based on the process inputs; the model output is then used as an input of a model with a simple-fixed structure to predict the barrel pressure which can be measured online. Finally, the predicted pressure is compared to the measured value and the corresponding error is used as a feedback signal to correct the viscosity estimate. This novel feedback structure enables the online adaptability of the viscosity model in response to modeling errors and disturbances, hence producing a reliable viscosity estimate. The experimental results on different material/die/extruder confirm the effectiveness of the proposed “soft sensor” method based on dynamic gray-box modeling for real-time monitoring and control of polymer extrusion processes. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers

Low-cost Process monitoring for polymer extrusion

Polymer extrusion is regarded as an energy-intensive production process, and the real-time monitoring of both energy consumption and melt quality has become necessary to meet new carbon regulations and survive in the highly competitive plastics market. The use of a power meter is a simple and easy way to monitor energy, but the cost can sometimes be high. On the other hand, viscosity is regarded as one of the key indicators of melt quality in the polymer extrusion process. Unfortunately, viscosity cannot be measured directly using current sensory technology. The employment of on-line, in-line or off-line rheometers is sometimes useful, but these instruments either involve signal delay or cause flow restrictions to the extrusion process, which is obviously not suitable for real-time monitoring and control in practice. In this paper, simple and accurate real-time energy monitoring methods are developed. This is achieved by looking inside the controller, and using control variables to calculate the power consumption. For viscosity monitoring, a ‘soft-sensor’ approach based on an RBF neural network model is developed. The model is obtained through a two-stage selection and differential evolution, enabling compact and accurate solutions for viscosity monitoring. The proposed monitoring methods were tested and validated on a Killion KTS-100 extruder, and the experimental results show high accuracy compared with traditional monitoring approaches.

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.

Synthesis by extrusion: continuous, large-scale preparation of MOFs using little or no solvent

Grinding solid reagents under solvent-free or low-solvent conditions (mechanochemistry) is emerging as a general synthetic technique which is an alternative to conventional solvent-intensive methods. However, it is essential to find ways to scale-up this type of synthesis if its promise of cleaner manufacturing is to be realised. Here, we demonstrate the use of twin screw and single screw extruders for the continuous synthesis of various metal complexes, including Ni(salen), Ni(NCS)(2)(PPh3)(2) as well as the commercially important metal organic frameworks (MOFs) Cu-3(BTC)(2) (HKUST-1), Zn(2-methylimidazolate)(2) (ZIF-8, MAF-4) and Al(fumarate)(OH). Notably, Al(fumarate)(OH) has not previously been synthesised mechanochemically. Quantitative conversions occur to give products at kg h(-1) rates which, after activation, exhibit surface areas and pore volumes equivalent to those of materials produced by conventional solvent-based methods. Some reactions can be performed either under completely solvent-free conditions whereas others require the addition of small amounts of solvent (typically 3-4 mol equivalents). Continuous neat melt phase synthesis is also successfully demonstrated by both twin screw and single screw extrusion for ZIF-8. The latter technique provided ZIF-8 at 4 kg h(-1). The space time yields (STYs) for these methods of up to 144 x 10(3) kg per m(3) per day are orders of magnitude greater than STYs for other methods of making MOFs. Extrusion methods clearly enable scaling of mechanochemical and melt phase synthesis under solvent-free or low-solvent conditions, and may also be applied in synthesis more generally.

Melt Processing and Properties of Polyamide 6/Graphene Nanoplatelet Composites

Graphene, due to its outstanding properties, has become the topic of much research activity in recent years. Much of that work has been on a laboratory scale however, if we are to introduce graphene into real product applications it is necessary to examine how the material behaves under industrial processing conditions. In this paper the melt processing of polyamide 6/graphene nanoplatelet composites via twin screw extrusion is investigated and structure–property relationships are examined for mechanical and electrical properties. Graphene nanoplatelets (GNPs) with two aspect ratios (700 and 1000) were used in order to examine the influence of particle dimensions on composite properties. It was found that the introduction of GNPs had a nucleating effect on polyamide 6 (PA6) crystallization and substantially increased crystallinity by up to 120% for a 20% loading in PA6. A small increase in crystallinity was observed when extruder screw speed increased from 50 rpm to 200 rpm which could be attributed to better dispersion and more nucleation sites for crystallization. A maximum enhancement of 412% in Young's modulus was achieved at 20 wt% loading of GNPs. This is the highest reported enhancement in modulus achieved to date for a melt mixed thermoplastic/GNPs composite. A further result of importance here is that the modulus continued to increase as the loading of GNPs increased even at 20 wt% loading and results are in excellent agreement with theoretical predictions for modulus enhancement. Electrical percolation was achieved between 10–15 wt% loading for both aspect ratios of GNPs with an increase in conductivity of approximately 6 orders of magnitude compared to the unfilled PA6.

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

Structure, mechanical, and electrical properties of high-density polyethylene/multi-walled carbon nanotube composites processed by compression molding and blown film extrusion

The structure and properties of melt mixed high-density polyethylene/multi-walled carbon nanotube (HDPE/MWCNT) composites processed by compression molding and blown film extrusion were investigated to assess the influence of processing route on properties. The addition of MWCNTs leads to a more elastic response during deformations that result in a more uniform thick-ness distribution in the blown films. Blown film composites exhibit better mechanical properties due to the enhanced orientation and disentanglement of MWCNTs. At a blow up ratio (BUR) of 3 the breaking strength and elongation in the machine direction of the film with 4 wt % MWCNTs are 239% and 1054% higher than those of compression molded (CM) samples. Resistivity of the composite films increases significantly with increasing BURs due to the destruction of conductive pathways. These pathways can be recovered partially using an appropriate annealing process. At 8 wt % MWCNTs, there is a sufficient density of nanotubes to maintain a robust network even at high BURs.

Characterization and structure–property relationship of melt-mixed high density polyethylene/multi-walled carbon nanotube composites under extensional deformation

Melt-mixed high density polyethylene (HDPE)/multi-walled carbon nanotube (MWCNT) nanocomposites with 1–10 wt% MWCNTs were prepared by twin screw extrusion and compression moulded into sheet form. The compression moulded nanocomposites exhibit a 112% increase in modulus at a MWCNT loading of 4 wt%, and a low electrical percolation threshold of 1.9 wt%. Subsequently, uniaxial, sequential (seq-) biaxial and simultaneous (sim-) biaxial stretching of the virgin HDPE and nanocomposite sheets was conducted at different strain rates and stretching temperatures to investigate the processability of HDPE with the addition of nanotubes and the influence of deformation on the structure and final properties of nanocomposites. The results show that the processability of HDPE is improved under all the uniaxial and biaxial deformation conditions due to a strengthened strain hardening behaviour with the addition of MWCNTs. Extensional deformation is observed to disentangle nanotube agglomerates and the disentanglement degree is shown to depend on the stretching mode, strain rate and stretching temperatures applied. The disentanglement effectiveness is: uniaxial stretching < sim-biaxial stretching < seq-biaxial stretching, under the same deformation parameters. In sim-biaxial stretching, reducing the strain rate and stretching temperature can lead to more nanotube agglomerate breakup. Enhanced nanotube agglomerate disentanglement exhibits a positive effect on the mechanical properties and a negative effect on the electrical properties of the deformed nanocomposites. The ultimate stress of the composite containing 4 wt% MWCNTs increased by ∼492% after seq-biaxial stretching, while the resistivity increased by ∼1012 Ω cm.

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.