Real Time Monitoring of Morphologic and Mechanical Properties of Polymer Nanocomposites During Extrusion by near Infrared and Ultrasonic Spectroscopy

Extrusion is one of the most applied technologies for the processing of polymer nanocomposites for applications in automotive, electrical and packaging industrial sectors. These nanostructured materials have advantages in comparison to traditional polymer materials, so that properties like tensile strength and modulus, barrier and surface properties, electrical properties and flame retardancy will be improved. There is a need to control amount and dispersion of the nanofillers in the polymer matrix during melt processing and to control the influence of the processing conditions on the nanocomposite formation. For an adequate real time characterization it is necessary to measure directly in the extruder. Spectroscopic methods and Ultrasonic measurements are outstanding methods for this kind of in-line monitoring. This paper deals with the real time determination of the dispersion and the impact strength of polymer nanocomposites in the melt during extrusion by Ultrasonic measurements and NIR spectroscopy. These in-line measurements were correlated with off-line rheological measurements, transmission electron microscopy and mechanical test measurements by multivariate data analysis. The polymers used are polypropylene and polyamide 6. As nanofillers we used different modified layered silicates. We determined the degree of exfoliation as an indicator for the dispersion of the nanofiller in the polymer matrix for different layered silicates and at different process conditions.     

In-line process monitoring on polymer melts by NIR-spectroscopy

The application of near-infrared (NIR) spectroscopy to continuous monitoring of extrusion processes of polymers was demonstrated. NIR probes were adapted to the extruder outlet. The connection between probe and extruder was realized through a fiber-optic cable. The measurements utilized transmission or diffuse reflectance modes. Quantitative analysis was carried out using the chemometric methods of Partial Least Squares (PLS) and Principle Component Regression (PCR). Subjects of our investigations were the quantification of the composition of polymer blends (polypropylene/ethylene vinyl acetate copolymer) and the quantification of content of filler in polymer matrices (polypropylene/pulverized chalk) in the range of weight concentrations from 0 to 40%. The results show that NIR spectroscopy is suitable for quantitative in-line and real-time analysis of polymers. Received: 25 October 1996 / Revised: 22 May 1997 / Accepted: 24 May 1997     

Polystyrene prepared by reactive extrusion: kinetics and effect of processing parameters

The conversion and residence time were investigated during the bulk polymerization of styrene in a twin screw extruder. It was found that polymerization mainly occurred in the zone between 400 and 1000 mm along the screw axis in the extruder, corresponding to the residence time of the reactants ranging from 1 to 4 min in the extruder. Furthermore, the processing conditions (feed rate, screw rotation rate) and average molecular weight of the polymer have a great effect on the residence time. Based on dimensionless analysis, a model of the residence time has been built‐up, which has been confirmed by the results of realistic measurements. A kinetic model of the polymerization has also been established under the assumption that the screw extruder can be regarded as an ideal plug flow reactor. Copyright © 2004 John Wiley & Sons, Ltd.     

Modeling of L-lactide Polymerization by Reactive Extrusion

The kinetics of L-lactide ring-opening polymerization initiated by stannous octoate and triphenylphosphine was investigated in a batch apparatus (Haake Rheocord Mixer). Based on the experimental data, a kinetic model is developed, considering a coordination-insertion mechanism. Reactive extrusion experiments were further conducted for the same polymerization process, on a co-rotating twin screw extruder. The melted material flow and mixing was described by using the Ludovic® commercial simulator. Based on the developed kinetic model and simulated flow of L-lactide polymerization mixture, a mathematical model of reactive extrusion process is formulated, describing the evolutions of monomer conversion and average molecular weight along the extruder. The model is predicting with a reasonable good accuracy the experimental data.     

Data Reconciliation and Control in Styrene-Butadiene Emulsion Polymerizations

Summary: A nonlinear model-based predictive control (NLMPC) method was developed using a First Principles model of an emulsion copolymerization of carboxylated styrene butadiene rubber (XSBR). Copolymer composition, conversion and average molecular weights of the copolymer were chosen as the controlled variables due to their influence on the final product properties and quality. These properties, however, are rarely measured in-line due to the operational difficulties associated with their measurement. For this reason a soft-sensor using reaction calorimetry techniques was developed and used to infer reaction conditions, rates, species concentrations and polymer properties in a industrial scale emulsion polymerization reactor.     

A real‐time model based on optimized least squares support vector machine for industrial polypropylene melt index prediction

The accurate and reliable real‐time prediction of melt index (MI) is indispensable in quality control of the industrial propylene polymerization (PP) processes. This paper presents a real‐time soft sensor based on optimized least squares support vector machine (LSSVM) for MI prediction. First, the hybrid continuous ant colony differential evolution algorithm (HACDE) is proposed to optimize the parameters of LSSVM. Then, considering the complexity and nondeterminacy of PP plant, an online correcting strategy (OCS) is adopted to update the modeling data and to revise the model's parameters adaptively. Thus, the real‐time prediction model, HACDE‐OCS‐LSSVM, is obtained. Based on the data from a real PP plant, the models of HACDE‐LSSVM, DE‐LSSVM and LSSVM are also developed for comparison. The research results show that the proposed real‐time model achieves a good performance in the practical industrial MI prediction process. Copyright © 2016 John Wiley & Sons, Ltd.     

A novel apparatus combining polymer extrusion processing and x-ray scattering

A novel apparatus was designed and constructed combining polymer extrusion processing and x-ray scattering. It allows direct, real time monitoring of structure and temperature development in polymer material during extrusion. The apparatus involves a vertical industrial extruder equipped with a four-roll stretching device to mimic the processing environments of uni-axially oriented films or sheets, a simultaneous small and wide angle x-ray scattering system and an infrared thermometer as detection unit. The charging barrel of the extruder and the stretching device can be moved upward and downward precisely. By moving the sample along the center line, structure and temperature development as a function of position can be obtained. The performance of the apparatus was verified by a test experiment, which allows us to establish the relationship between processing parameters and evolution of structure with different length scales, and may lead to a better understanding of the physics in polymer processing.     

In-line monitoring of droplets deformation and recovering and polymer degradation during extrusion

An extruder can be operated as a torque rheometer by setting an external control of the processing variables and adding an in-line optical detector and an on-off mechanical valve at the extruder die exit. Various operational modes can be used including constant, ramp and sinusoidal changes of the die-head pressure. With the valve closed, a fixed amount of polymer is added and the extruder put into operation, controlling the screw rotation speed via software, having a proportional/integral/derivative controller. Polymer degradation can be followed recording changes in barrel pressure and torque. After processing, the valve is opened and the molten polymer discharged under a controlled die-head pressure, manipulating again the screw rotation speed. The polymer mixture morphology can be scanned during the discharge of the melt flow by the in-line turbidimeter, showing the deformation/recovery of the second phase droplets.     

A batch modelling approach to monitor a freeze-drying process using in-line Raman spectroscopy

Freeze-drying or lyophilisation is a batch wise industrial process used to remove water from solutions, hence stabilizing the solutes for distribution and storage. The objective of the present work was to outline a batch modelling approach to monitor a freeze-drying process in-line and in real-time using Raman spectroscopy. A 5% (w/v) d-mannitol solution was freeze-dried in this study as model. The monitoring of a freeze-drying process using Raman spectroscopy allows following the product behaviour and some process evolution aspects by detecting the changes of the solutes and solvent occurring during the process. Herewith, real-time solid-state characterization of the final product is also possible.The timely spectroscopic measurements allowed the differentiation between batches operated in normal process conditions and batches having deviations from the normal trajectory. Two strategies were employed to develop batch models: partial least squares (PLS) using the unfolded data and parallel factor analysis (PARAFAC). It was shown that both strategies were able to developed batch models using in-line Raman spectroscopy, allowing to monitor the evolution in real-time of new batches. However, the computational effort required to develop the PLS model and to evaluate new batches using this model is significant lower compared to the PARAFAC model. Moreover, PLS scores in the time mode can be computed for new batches, while using PARAFAC only the batch mode scores can be determined for new batches.     

衰减全反射-紫外/可见光谱传感技术

阐述了衰减全反射法(ATR)的光学原理、衰减全反射一紫外／可见光谱方法(ATR-UV)的特征及其应用中的校正方法。ATR-UV传感器能够同时检测化工过程中体系的多种主要组成的含量,其方法简单、迅速、准确,无需对试样进行预处理或稀释,该技术对于在线或内置传感监测化学化工过程方面具有很好的应用前景。     

Modeling and Simulation of Liquid Phase Propylene Polymerizations in Industrial Loop Reactors

Liquid phase tubular loop polymerization reactors are widely used in the polyolefin industries because of their capabilities to promote high mixing of reactants in the reaction vessel and to allow for high heat transfer rates with the cooling jacket due to their high aspect ratio. Previous works on this subject focused on the modeling of the polymerization system, but only a few compared their results with real industrial data. A literature review about the propylene production in loop reactors shows that the validation of a distributed model with actual industrial data is yet to be presented. A distributed mathematical model is presented for industrial liquid phase loop polypropylene reactors and validated with actual industrial data for the first time. The model is able to represent the dynamic trajectories of production rates, MFI and XS values during grade transitions within the experimental accuracy. The model indicates that the polymer quality can change significantly along the reactor train and that manipulation of feed flow rates can be successfully used for production of more homogeneous polymer products.     

In-line rheometry of polypropylene based Wood Polymer Composites

A completely satisfactory off-line rheological investigation of Wood Polymer Composites (WPCs) is very challenging at processing temperatures: when using rotational rheometry in oscillatory mode, the linear viscoelastic region is often too small, while in capillary rheometry the sieving effect of the fibres may invalidate the results. Moreover, all off-line tests present the risk of wood degradation.To this aim, an in-line extrusion rheometer (slit die) has been developed. The major advantages are that the measurements are made in real processing conditions and degradation problems are less severe thanks to reduced oxygen level inside the extruder barrel.In order to verify the methodology, tests have been conducted on a commercial polypropylene based WPC with 30 wt.% white fir fibres and compared with off-line measurements performed at a lower temperature on the same material. For comparison, a temperature shift factor has been used, that has been estimated by characterizing the polypropylene matrix alone.     

Raman spectroscopy as a process analytical technology tool for the understanding and the quantitative in-line monitoring of the homogenization process of a pharmaceutical suspension

The aim of this study was to propose a Process Analytical Technology (PAT) strategy for the quantitative in-line monitoring of an aqueous pharmaceutical suspension using Raman spectroscopy. A screening design was used to study the significance of process variables (mixing speed and height of the stirrer in the reactor) and of formulation variables (concentration of the active pharmaceutical ingredient (API) ibuprofen and the viscosity enhancer (xanthan gum)) on the time required to homogenize an aqueous pharmaceutical model suspension as response variable. Ibuprofen concentration (10% and 15% (w/v)) and the height of stirrer (position 1 and 2) were discrete variables, whereas the viscosity enhancer (concentration range: 1-2 g L-1) and the mixing speed (700-1000 rpm) were continuous variables. Next, a multilevel full factorial design was applied to study the effect of the remaining significant variables upon the homogenization process and to establish the optimum conditions for the process. Interactions between these variables were investigated as well. During each design experiment, the conformity index (CI) method was used to monitor homogeneity of the suspension mixing system in real-time using Raman spectroscopy in combination with a fibre optical immersion probe. Finally, a principal component regression (PCR) model was developed and evaluated to perform quantitative real-time and in-line measurements of the API during the mixing process. The experimental design results showed that the suspension homogenization process is an irregular process, for which it is impossible to model the studied variables upon the measured response variable. However, applying the PCR model it is possible to predict in-line and real-time the concentration of the API in a suspension during a mixing process. In this study, it is shown that Raman spectroscopy is a suitable PAT tool for the control of the homogenization process of an aqueous suspension. Raman spectroscopy not only allowed real-time monitoring of the homogeneity of the suspension, but also helped (in combination with experimental design) to understand the process. Further, the technique allowed real-time and in-line quantification of the API during the mixing process.     

Infrared spectroscopy in hemodialysis: reagent-free monitoring of patient detoxification by infrared spectroscopy

A method for monitoring hemodialysis based on quantitative infrared spectroscopic determination of the molecules dialyzed from patient blood is reported. The measurements are reagent-free and aim at real-time and in-line monitoring of the hemodialysis patient. A flow cell using attenuated total reflection infrared spectroscopy is coupled downstream of the dialysis filter unit. A calibration model has been developed from real hemodialysis samples analyzed by chemical reference analysis and from artificially mixed dialysis samples. The infrared monitoring of hemodialysis includes quantitative determination of urea as the lead substance, as well as glucose, lactate, and creatinine, all at a precision only limited by the chemical reference analysis. The flow cell can be fitted to all standard hemodialysis systems. Preliminary tests with hemodialysis patients have demonstrated that detoxification can be clearly monitored. Furthermore, these experiments demonstrate that a wide, real-time control of the patient’s physiological parameters is possible with this method, which could lead to increased patient safety.     

Arduino实时在线监测系统在聚甲基丙烯酸甲酯本体聚合过程中的应用

利用自主研发的实时在线监测系统，对不同聚合温度条件下，聚甲基丙烯酸甲酯（PMMA）的本体聚合过程进行实时在线监测，建立"虚拟信号值-反应时间"实时在线监测曲线.通过曲线的变化，可以清晰观察到PMMA本体聚合过程的4个阶段，即诱导期、初期、中期和后期.根据本体聚合"转化率-反应时间"S型曲线的特点，构建"虚拟信号值-反应时间-转化率"关系曲线和聚合物转化率计算公式，并提出PMMA预聚体的预测和实时在线监测方法.方法具有操作简单、实时性强、外界因素影响小和性能稳定等优点，是一种新型的实时在线分析方法.     

A General Autofluorescence Method to Characterize Polymerization Progress

An autofluorescence technique to characterize polymerization progress in real time/in line was developed, which functioned in the absence of typical fluorogenic groups on the monomer or polymer. The monomer dicyclopentadiene and polymer polydicyclopentadiene are hydrocarbons that lack traditional functional groups for fluorescence spectroscopy. Here, the autofluorescence of formulations containing this monomer and polymer during ruthenium-catalyzed ring-opening metathesis polymerization (ROMP) was harnessed for reaction monitoring. The methods fluorescence recovery after photobleaching (FRAP) and here-developed fluorescence lifetime recovery after photobleaching (FLRAP) characterized polymerization progress in these native systems—without requiring exogenous fluorophore. (Auto)fluorescence lifetime recovery changes during polymerization correlated linearly to degree of cure, providing a quantitative link with reaction progress. These changing signals also provided relative rates of background polymerization, enabling comparison of 10 different catalyst-inhibitor-stabilized formulations. Multiple-well analysis demonstrated suitability for future high-throughput evaluation of formulations for thermosets. The central concept of the combined autofluorescence and FLRAP/FRAP method may be extendable to monitoring other polymerization reactions previously overlooked for lack of an obvious fluorescence handle.     

A new device for in-line colorimetric quantification of polypropylene degradation under multiple extrusions

An in-line colorimeter that is able to quantify color changes in real time during extrusion was developed and validated. It is composed of LEDs emitting at three different wavelengths and a photocell that measures the intensity of the light transmitted through the polymer melt flow. The colorimeter was validated at the bench by employing colored aqueous solutions and in-line during the extrusion of a colored polypropylene. Furthermore, it was used to in-line quantify the color changes in a polypropylene as generated over multiple extrusions due to thermo-mechanical degradation. The technique was proved to be fast and suitable to measure color changes in real time during extrusion.     

Determination of sulfonamide residues in water samples by in-line solid-phase extraction-capillary electrophoresis

An in-line solid-phase extraction-capillary electrophoresis method with UV–vis detection was developed for the monitoring of residues of five sulfonamides (sulfadoxin, sulfadimethoxine, sulfamerazine, sulfachloropyridazine and sulfamethoxazole) in tap, bottled mineral and river waters. For this purpose an analyte concentrator was constructed, based on the introduction of a small portion of a solid-phase extraction sorbent into the electrophoretic capillary to carry out an in-line concentration step, improving sensitivity. A detailed study was carried out to optimize parameters affecting the in-line solid-phase extraction process, such as the design of the concentrator device, type of sorbent and conditions of elution and injection. The proposed method is simple for the environmental monitoring of these antibiotic residues in waters, allowing the direct injection of the samples without any off-line pretreatment and achieving limits of detection between 0.3 and 0.6 μg/L. Recoveries ranging 52.2–109.2% and relative standard deviations below 13.4% were obtained.     

A novel multi‐mode data processing method and its application in industrial process monitoring

Multi‐mode process monitoring is a key issue often raised in industrial process control. Most multivariate statistical process monitoring strategies, such as principal component analysis (PCA) and partial least squares, make an essential assumption that the collected data follow a unimodal or Gaussian distribution. However, owing to the complexity and the multi‐mode feature of industrial processes, the collected data usually follow different distributions. This paper proposes a novel multi‐mode data processing method called weighted k neighbourhood standardisation (WKNS) to address the multi‐mode data problem. This method can transform multi‐mode data into an approximately unimodal or Gaussian distribution. The results of theoretical analysis and discussion suggest that the WKNS strategy is more suitable for multi‐mode data normalisation than the z‐score method is. Furthermore, a new fault detection approach called WKNS‐PCA is developed and applied to detect process outliers. This method does not require process knowledge and multi‐mode modelling; only a single model is required for multi‐mode process monitoring. The proposed method is tested on a numerical example and the Tennessee Eastman process. Finally, the results demonstrate that the proposed data preprocessing and process monitoring methods are particularly suitable and effective in multi‐mode data normalisation and industrial process fault detection. Copyright © 2014 John Wiley & Sons, Ltd.