Powder Mixing Process Research Articles

Spatially resolved monitoring of powder mixing processes via multiple NIR-probes

Abstract The production of pharmaceutical dosage forms relies on efficient blending of granular components. By monitoring in real-time the blending processes via non-invasive techniques, such as near-infrared (NIR) spectroscopy, the blending end-point can be determined and homogeneity can be guaranteed for a given material blend. In this study an experimental setup with multiple NIR probes attached to a lab-scale blending vessel is presented. The probes were connected to a Fourier-transform NIR spectrometer via an optical fiber switch. Thereby, the blending processes could be “quasi-simultaneously” monitored at multiple positions. Differences in blending behavior in the monitored positions inside the vessel were identified, which would be impossible using a single probe system. The interpretation of the NIR-spectra was done using a chemometric model based on partial least squares regression. Premixed samples with varied content of an active pharmaceutical ingredient were used for calibration. To prevent segregation problems during calibration, it was performed on a rotating disk outside the vessel. Using this multiple-probe setup in combination with the developed chemometric model, segregation and blending inside the vessel were analyzed by observing the temporal and spatial concentration changes, without interruptions caused by manual sampling and/or pausing of the process.

Reduced-order discrete element method modeling

Reduced-order modeling (ROM) techniques are playing a very significant role in the recent literature bridging the gap between computationally expensive simulators and their application in optimization and control of distributed parameter systems. In modeling of solid-based processes, Discrete Element Method (DEM) is a very popular high-fidelity modeling approach which enables the tracking of discrete entities as they are processed inside complex geometries interacting with each other and with process boundaries. However, the computational cost of DEM models limits their applicability to simulation of specific and limited number of cases. In this work, we develop the DE–ROM (Discrete Element–Reducer-order model) approach which reduces the computational cost—while maintaining model accuracy—of expensive DEM models. The proposed methodology is based on Principal Component Analysis (PCA), combined with surrogate-model mapping and data imputation for the cases where there is missing information. The results of the application of the developed method to the powder mixing process, demonstrate that the DE–ROM model produces accurate profiles of distributed particle properties in real time. Finally, the developed model is used for the identification of the optimal design and operating conditions of the mixing process.

표면 부식 처리한 WS2입자를 첨가한 Cu/Sn계 다이아몬드 마이크로 블레이드의 절삭특성

particles were added to micro-diamond blades with Cu/Sn binding metal as lubricants to improve cutting efficiency. It was found in previous works that the added lubricant could reduce remarkably the momentary energy consumption during dicing tests but increased wear rate slightly owing to weak bonding between lubricant particles and bond metals. In the present work, the surface of lubricant particles were etched for activating the surface of particles that provide even distribution of particles during powder mixing process and improvement of wetting at the interfaces between particles and molten Cu/Sn bond metals during pressurized sintering so that could provide the improved strength of micro-blades and result in extended life. Chipping behavior of workpiece with the types of micro-blades including were compared because it is important in semiconductor and micro-packaging industries to control average roughness and straightness of sliced surface which is closely related with quality.

Development of a methodology to estimate error in the on-line measurements of blend uniformity in a continuous powder mixing process

Abstract In this paper, a multi-point fiber optic based NIR system was implemented to monitor API concentration at the discharge of a continuous mixer. The sample size being interrogated by NIR was determined by measuring the velocity of the powder on the chute, which allowed selection of the number of scans to be averaged. A methodology was developed that allows quantification of the error associated with the in-line measurements. Comparison of in-line and off-line measurements was made at equivalent sample sizes. Mathematical model fitting for the in-line as well as off-line data revealed that the contribution of the analytical method error was negligible. A baseline RSD of 0.02 in the in-line measurements persists because of the inherent non-uniform nature of powder material. These results are useful towards achieving Real-Time-Release (RTR) of continuously manufactured drug product.

Multi-scale flowsheet simulation of an integrated continuous purification–downstream pharmaceutical manufacturing process

Properties of active pharmaceutical ingredients influence the critical quality attributes (CQAs) of final solid dosage forms (e.g. tablets). In the last decade, continuous manufacturing has been shown to be a promising alternative to batch processing in the pharmaceutical industry. Therefore, a quantitative model-based analysis of the influence of upstream API properties on downstream processing quality metrics will lead to enhanced QbD in pharmaceutical drug product manufacturing (Benyahia et al., 2012). In this study, a dynamic flowsheet simulation of an integrated API purification step (crystallization), followed by filtration and drying, with a downstream process (powder mixing) is presented. Results show that the temperature profile of a cooling crystallization process influences the crystal size distribution which in turn impacts the RSD and API concentration of the powder mixing process, which in turn has a direct effect on tablet properties (Boukouvala et al., 2012). A hybrid PBM-DEM model is also presented to demonstrate the coupling of particle-scale information with process-scale information leading to enhanced elucidation of the dynamics of the overall flowsheet simulation.

Mathematical Development and Comparison of a Hybrid PBM-DEM Description of a Continuous Powder Mixing Process

This paper describes the development of a multidimensional population balance model (PBM) which can account for the dynamics of a continuous powder mixing/blending process. The PBM can incorporate the important design and process conditions and determine their effects on the various critical quality attributes (CQAs) accordingly. The important parameters considered in this study are blender dimensions and presence of noise in the inlet streams. The blender dynamics have been captured in terms of composition of the ingredients, (relative standard deviation) RSD, and (residence time distribution) RTD. PBM interacts with discrete element modeling (DEM) via one-way coupling which forms a basic framework for hybrid modeling. The results thus obtained have been compared against a full DEM simulation which is a more fundamental particle-level model that elucidates the dynamics of the mixing process. Results show good qualitative agreement which lends credence to the use of coupled PBM as an effective tool in control and optimization of mixing process due to its relatively fewer computational requirements compared to DEM.

Analysis and Evaluation of the Recycled Asphalt Mixture Performance Influencing Factors

This paper is based on majority indoor tests of recycled asphalt mixture performance. To analyze the elements which could affect different blended rates of the old material and the different mixing processes of recycled asphalt mixture by using orthogonal experiment method. The results show that, different mixing processes have significantly influenced the performance of rutting resistance on the high temperature, resistance to water damage of the recycled asphalt mixture. However blending rate of the old material has influenced more on low-temperature crack resistance of the recycled asphalt mixture. Old material blended rate is 30% and first mixing of old materials and recycling agent in a hot-melt state, by adding new complementary stone , followed by a new supplementary asphalt mineral powder mixing process to produce recycled asphalt mixture for an ideal performance.

Multi-dimensional population balance modeling and experimental validation of continuous powder mixing processes

It has been recognized that the application of quality by design (QbD) to continuous processing in the pharmaceutical industry leads to better process control, improved product quality and mitigates scale-up issues (Schaber et al., 2011), whereby a component of QbD involves the development quantitative model-based representation of the process. In this work a population balance model (PBM) framework has been developed to model the dynamics of a continuous powder mixing process which is an important and complex unit operation used in a pharmaceutical tablet manufacturing process. Our previous studies have shown that PBM is effective in determining the various critical quality attributes (CQAs) (relative standard deviation (RSD), API composition and residence time distribution (RTD)) associated with mixing. It can also account for the key design and process parameters such as mixer RPM, processing angle, blender dimensions and number of radial and axial compartments. The developed PBM has been quantitatively validated by fitting experimentally obtained values of the above mentioned CQAs for different operating conditions. The model is dynamic and computationally tractable compared to traditional discrete element model (DEM) representations of mixing processes. This lends credence to the use of the model as an effective tool in control and optimization of blending process and can have future implementation in designing a Process Analytical Technology (PAT) system which will allow considerable improvements on the current manufacturing framework.

Optimizing continuous powder mixing processes using periodic section modeling

While continuous powder mixing has been an area of active research in recent years, effects of operating conditions on the mixing performance has not been well understood yet. Based on our previously developed periodic section modeling (Gao et al., 2012), this paper examines the effects of operating conditions on two significant parameters of the continuous blending processes: axial velocity and local mixing rate of the mixture. Four mixing cases differing in particle size, density and cohesiveness are simulated. Results show that when the local mixing rate improves at low fill levels and high blade speed, particles also move faster in the axial direction and reside for a shorter time inside the mixer. This trade-off between ascending local mixing rate and descending residence time indicates a non-optimal overall blending performance even when the best operating condition is applied. Based on these results, strategies that can further improve the blending performance are performed, which are proposed by increasing the blade speed while keeping a constant axial velocity. These strategies guarantee that the variance decay rate along the mixing axis is proportional to the blade speed in continuous blending processes. Dramatic improvements are observed when these strategies are applied, which shows the merit of this work on design and optimization of continuous power blending processes.

Green and NIR sensitized luminescent nanophosphor: Preparation, characterization and application

Luminescent nanophosphor of Er, Yb: Gd2O3 has been synthesized by well known combustion synthesis. Along with strong UV–Vis upconversion emission, sensor for temperature and magnetic field, nano-heater etc., it can also be used as luminescent ink by dispersing the nanophosphor in aqueous polyvinyl alcohol solution. The stability of the ink has been found to depend strongly on the mixing process of the phosphor powder in the polymer solution. The X-ray diffraction results and TEM images with diffraction pattern show that the particles are in cubic phase of Gd2O3 with particles of average size <40nm. SEM images show flaky structure which makes it suitable for dispersing in PVA and useful for luminescent ink purposes on NIR excitation. The FT-IR and the thermal analysis support the presence of PVA. Upconversion and downconversion luminescence has also been observed with 532nm excitation and energy transfer mechanism has been explained. The NIR pumping gives strong UC emission bands in red and green regions extending up to extreme UV (240nm) in this host.

A multi-dimensional population balance model approach to continuous powder mixing processes

This study is concerned with the development of a novel population balance model (PBM) framework that can qualitatively capture the dynamics of a continuous powder mixing process. For the first time, a PBM has been developed to model powder mixing and it accounts for key design and process parameters such as mixer RPM, processing angle in terms of powder fluxes, along with the effect of number of axial and radial compartments. Via this approach, results clearly show the qualitative validity of the PBM as a tool to capture the dynamics of the process that affect API composition, RSD and RTD. The model also demonstrates the use of the PBM as an overall multi-scale modeling tool to combine micro-level models such as DEM in a hybrid framework. Due to the relative computational simplicity of solving the PBM (as compared to DEM), the developed model can be used effectively in control and optimization of the mixing process.

Monitoring the particle size distribution of a powder mixing process with acoustic emissions: a review

In mixing processes, the particle size distribution (PSD) is an important physical quality driver of these powders. In most production plants the current method of inspecting this PSD is by means of a manual reference sieve analysis, which is reliant on human effort, and it is slow and time consuming. With the current manufacturing flow, in-process optimisation is difficult to implement and this has caused final output quality to vary considerably per box. This has necessitated the need for real-time process monitoring sensors, to provide the online data needed for quality monitoring and produce opportunity for process optimisation. A summary of in-process sensing methods that can be used to monitor PSD are presented and reviewed. This is followed by a critical analysis of the related research where acoustic emissions have been used to monitor particle sizes.

Predicting bulk powder flow dynamics in a continuous mixer operating in transitory regimes

Over recent years there has been increasing interest in continuous powder mixing processes, due mainly to the development of on-line measurement techniques. However, our understanding of these processes remains limited, particularly with regard to their flow and mixing dynamics. In the present work, we study the behaviour of a pilot-scale continuous mixer during transitory regimes, in terms of hold-up weight and outflow changes. We present and discuss experimental results concerning the start-up dynamics of a Gericke GCM 500 mixer, for which a specific experimental protocol has been developed to determine the evolution of the hold-up in the mixer and the real outflow. Empirical relationships are derived so as to link hold-up weight variations with operating conditions. A simple stochastic approach, based on a non-homogeneous Markov chain, is developed to simulate the bulk particle flow and transport in the continuous mixer at a macroscopic level. Although this simple model is only based on the start-up behaviour, it provides a full description of the mixer dynamics in response to strong perturbations on the flow rate or on the rotational speed of the stirring device, such as negative or positive steps. This model is validated experimentally for a wide range of operating conditions, and constitutes a first approach to process control.

Carbon Nanotube Evolution in Aluminum Matrix during Composite Fabrication Process

In this study, carbon nanotube (CNT) reinforced aluminum (Al) composite was fabricated by powder metallurgy (P/M) technique and the evolution of CNTs within the matrix were traced, characterized and discussed. It was found that the separation of CNTs was affected by both the powder mixing operation as well as the secondary processing. CNTs were damaged during mechanical powder mixing and sintering process, whilst the graphitic structures were not damaged during the secondary processing. In addition, CNTs were subjected to substantial compression stress in both powder mixing and sintering process.

Periodic section modeling of convective continuous powder mixing processes

AbstractThis study aims to develop a general model of the convective continuous mixing process. The main idea is that continuous mixing can be considered as a combination of powder flow and mixing processes. Although powder flow is characterized by the residence time distribution (RTD), powder mixing can be described by a batch mixing process simulated in one periodic section of the continuous mixer. By characterizing the two processes separately, we can calculate the number of sections required to achieve certain homogeneity. In this study, continuous mixing is simulated using the discrete element method, and segregating and non‐segregating mixing cases are tested to investigate the applicability of the model. Results show satisfactory predictions by the model, which is able to characterize the continuous mixing performance of both mixing cases. On the basis of this study, we were also able to suggest a novel method in design and control of continuous powder mixing systems. © 2011 American Institute of Chemical Engineers AIChE J , 2012

Use of Near Infrared Spectroscopy for in- and Off-Line Performance Determination of Continuous and Batch Powder Mixers: Opportunities & Challenges

Within the scope of the PhD thesis “Continuous dynamic mixing of cohesive powders” (V. Kehlenbeck, TU Munich, 2006) a new approach of applying Near Infrared (NIR) spectroscopy was developed to study the mixing performance of powder mixers. For the in-line use of a BRUKER FT-NIR spectrometer in a continuous GERICKE powder mixer an attachment to clean the probe tip of the spectrometer with compressed air was developed. In parallel, this prototype was optimised for the in-line application in a batch mixer from LÖDIGE as well as for an automatic and dust-free off-line analysis of powder samples in a self-developed apparatus. Besides the in-line applications, the FT-NIR spectrometer was also used to analyze samples taken from a batchwise working PRODIMA mixer. For two-component powder mixtures (calcium carbonate and maize starch) it has been shown that FT-NIR spectroscopy is a powerful technique to study powder mixing processes in batch and continuous mixers as well as for the in- and off-line determination of the mixer performance. Due to the risk of encrustation, the complex calibration and the missing robustness of the calibration method as well as the analytical device, the academic findings were so far not applied to the production of bouillon products (multi-component mixes with powders and liquids). In the framework of a Process Analytical Technology (PAT) initiative the use of NIR spectroscopy for an industrial application will be studied.

Effect of processing parameters on the microstructure and thermal conductivity of diamond/Ag composites fabricated by spark plasma sintering

Diamond/metal composites with 50 vol.% diamond have been produced by spark plasma sintering (SPS) using pure Ag as a matrix and diamond particles as reinforcement. Three kinds of powder mixing processes were used to prepare the mixture of diamond/Ag powders: dry mixing without milling medium, wet mixing and magnetic blending. Subsequently, they were all consolidated by SPS at various processing parameters to produce bulk diamond/Ag composites. Then samples were heat treated in order to obtain a higher thermal conductivity. The effect of processing parameters on the morphologies of the mixed powders, the microstructure and the thermal conductivity of the composites were investigated by comparing the experimental data. It reveals that particles were easy to agglomerate and the distribution of mixed powders was inhomogeneous by dry mixing method, and wet mixing method is too complex. The most favorable mixing process is magnetic blending by which the powders can be homogenously mixed and the composites prepared by optimized SPS processing parameters can obtain the highest relative density and the best thermal conductivity among the composites prepared by different processes. The magnetic blending diamond/Ag composites even have a 23% increase in thermal conductivity compared with pure silver sintered by SPS.

Continuous quantitative monitoring of powder mixing dynamics by near-infrared spectroscopy

FT-NIR spectroscopy with a fiber optical reflection probe was applied as a process analytical technology tool for the continuous quantitative in-line monitoring of pharmaceutical powder mixing processes in a bladed mixer. Two powders, acetyl salicylic acid as an active pharmaceutical ingredient (API) and α-lactose monohydrate as an excipient were characterized in advance in terms of shear cell tests, flowability tests and particle-size determination to deduce flow properties of the powders. For the quantitative monitoring of the API content, two predictive models were developed with partial-least-squares calibration based on off-line calibration. On the basis of these predictive models, powder agitation and mixing times until blend uniformity were quantitatively monitored. Mixing experiments with systematically varied filling levels and filling protocols showed a strong variation in mixing, but eventually yielded uniform powder blend. Simulation results from the literature were linked to our experimental findings in order to identify and elucidate the effects of convective and diffusive mixing. In accordance to the international conference on harmonization acceptance level of 5% for the nominal API content, UV/Vis reference measurements were performed to verify the blend uniformity as predicted by the NIR measurements.

Alumina-Copper Composites with High Fracture Toughness and Low Electrical Resistance

Through an intense mixing process of Al2O3 powder with different copper contents, Al2O3-Cu composites were fabricated by sintered at 1300°C during 1h, where the likely liquid sintering mechanism, lead to obtain composites with relative densities greater than 95%. Scanning electron microscopy was used to observe the resulting microstructures, which indicated that these composites were mostly formed by a fine and homogeneous Al2O3-ceramic matrix with immerse nano-metallic copper particles. The behavior of both fracture toughness and electrical resistance of the composites is directly dependent with the copper content in the matrix. As the copper contents increased, the composites exhibited high values of fracture toughness, whereas, their electrical resistance is reduced considerably.

Real-time monitoring of drug concentration in a continuous powder mixing process using NIR spectroscopy

A non-destructive NIR spectroscopic method was used to acquire on-line spectra of a continuous mixing process, and evaluate the performance of this novel system. Partial least squares (PLS) calibration models were developed and used for real-time determination of active ingredient concentration on the blends produced with a continuous mixer. The NIR method was developed for concentrations ranging from 0 to 15% (w/w) of acetaminophen (APAP), the active pharmaceutical ingredient used in the experiments. The calibration model's overall accuracy was 0.41% (w/w), and estimated through the root mean square error of cross validation (RMSECV) for samples predicted using leave-class-out cross validation. In this cross validation, each concentration was defined as a class, and when a sample of a specific concentration was predicted all samples of that concentration were left out of the calibration model. The precision of the calibration model was also estimated at various concentration levels, to facilitate the differentiation between the variation in drug concentration due to the analytical method's measurement uncertainty and the variation in the drug distribution throughout the powder blend. The results obtained are very promising since in three of the five powder mixes, the variation in the drug concentration in the powder blends was similar to that of the analytical method indicating a high degree of blend homogeneity