Powder Flow Research Articles

Advances in Powder-Filled Mold Processes: A Comprehensive Review and Outlook

Powder molding technology is a versatile process widely used in the pharmaceutical, ceramic, chemical, food, and powder metallurgy industries. The powder-filling mold process is a key link in powder compression molding, and the uniformity and consistency of powder filling directly affect the final quality of powder products. Powder filling of molds is a more complex flow process. This paper first reviews the methods used to test powder flow characteristics and comments on their applicability to the mold-filling process, provides an in-depth discussion of four different filling techniques, focusing on the flow behavior of the powder during the filling process, and analyzes the effects of powder characteristics and process parameters on the filling effect. By reviewing the latest advances and identifying the key challenges, a valuable reference is provided for the mold-filling process.

Novel Pharmaceutical Cocrystal Consisting of Chlorzoxazone and Nicotinamide: A New Promising Carrier for Solubility Augmentation.

Chlorzoxazone (CHZ) is a centrally acting muscle relaxant used to treat muscle spasms. It is employed as a first-line medication for treating muscle spasms, offering both musculoskeletal relaxation and mild sedative effects. According to the biopharmaceutics classification system, it belongs to class II drug having poor solubility and high permeability. In order to improve the flow property, water solubility, and dissolution of CHZ, CHZ-nicotinamide (NA) cocrystal was prepared by liquid-assisted grinding cocrystallization (LAG CC) method using methanol as the choice of solvent. CHZ-NA cocrystal was characterized by differential scanning calorimeter (DSC), powder X-ray diffraction (PXRD), Fourier transform infrared spectrometry, and scanning electron microscopy (SEM). DSC scan showed a sharp endothermic peak shift, which is caused by the formation of a new crystal form with altered physical properties, which was further confirmed by PXRD. Also, a change in the surface morphology of LAG CC compared to CHZ was observed in SEM. The resultant CHZ-NA cocrystal displayed improved powder flow properties compared to the native form of CHZ. LAG CC demonstrated a 3.1- and 2.6-fold increase in saturated solubility and intrinsic dissolution rate, respectively, compared to CHZ alone. Furthermore, the in vitro dissolution study showed that the cumulative dissolution of CHZ in 2 h was about 53%. Whereas, dissolution of LAG CC reached 99% in 2 h, showing obvious dissolution improvement. Thus, CHZ-NA cocrystal could significantly improve the flow properties, solubility and dissolution of CHZ.

Investigation into particle flow patterns during powder spreading in SLM process

Particle flow patterns and their variation mechanism during powder spreading in selective laser melting (SLM) are comprehensively investigated based on discrete element method. Two typical particle flow patterns, circulation and discharge, are identified. The patterns are found to alternate during powder spreading, and the underlying dynamical mechanism are clarified. Variations in the particle flow state across the gap induce variations in vertical velocities of particles in front of the blade, affecting the particle flow pattern. Effect of process parameters on flow pattern is studied, and the dynamical mechanism of the effect is analyzed in depth by two newly proposed indexes. Decreasing gap height, and increasing spreading speed and blade inclination, reduce the proportion of particles moving downward in shear band and enhance inter-particle forces near the gap, thus weakening discharge and intensifying circulation. This study provides a beneficial insight into the powder flow during powder spreading in SLM process.

Effect of lubricants type and particle size on the rheological properties and aerosolization behavior of dry powder inhalers

A commonly used strategy to improve aerosolization behavior of carrier-based dry powder inhalers (DPIs) is the addition of magnesium stearate as a lubricant, yet it may also negatively affect properties of DPIs. Thus, the aim of this study was to find lubricants that could be used as alternatives of magnesium stearate and meanwhile verify the applicability of using powder rheological properties to predict the performance of different lubricants in DPIs. Here, using fluticasone propionate as a model drug, LH200 as the carrier, influence of lubricants type and particle size, including magnesium stearate, sodium stearate, Leucine, sodium stearate fumarate, Compritol® 888 ATO, and Compritol® HD5 ATO, on the physicochemical properties, powder rheology and aerosolization behavior of the DPI formulations was characterized. Further, the relationship between powder rheological parameters and in-vitro drug deposition parameter, fine particle fraction (FPF), were explored, and the contribution of powder flowability and adhesion was evaluated using principal component analysis (PCA). The results showed that magnesium stearate, sodium stearate and smaller sized leucine significantly reduced the basic flowability energy, aeration energy and Permeability of the DPI formulations, leading to improved aerosolization behavior. A robust linear correlation was established between rheological parameters and FPF. PCA showed that in lubricants containing formulations, the contribution of flowability (74.69%) was greater than that of adhesion (25.31%). In conclusion, sodium stearate and smaller particle size Leucine can be considered as substitutes of magnesium stearate in DPI formulations.

High-fidelity modelling of unburnt coal flow in an industry-scale blast furnace using a hybrid CFD-DEM method

Solid fuels, such as coal or biochar, can be injected into a blast furnace for low-carbon ironmaking. However, unburnt coal or biochar powders may accumulate in the coke bed, potentially reducing bed permeability and compromising furnace stability. Current CFD-DEM methods struggle to simulate systems with significant size differences between coke particles and coal or biochar powders, where the diameter ratio dck/dcl is 100–200 times. In this work, a novel multi-resolution hybrid CFD-DEM model is developed to simulate gas-unburnt powders-coke particles flow dynamics within and around the raceway with high fidelity. The model’s accuracy is validated by comparing the simulated evolution of the raceway cavity shape with experimental results. Subsequently, the hybrid model is used to simulate unburnt powder flow through the raceway and the adjacent coke bed (dck/dcl = 100), comparing its performance with conventional smoothed CFD-DEM models. The effects of gas inlet velocity and powder wettability are also analysed. Results show that the hybrid CFD-DEM model effectively simulates detailed pore fluid flow in the coke bed, which the smoothed model fails to capture, demonstrating the hybrid model’s superiority. Increasing gas inlet velocity enlarges the raceway cavity, intensifies high-speed pore flows, and accelerates powder transport into the coke bed. Additionally, higher cohesion energy density (kCED) reduces powder penetration, aligns the peak holdup position and penetration angle, and decreases permeability at key probe positions. This work provides an effective and efficient numerical tool to help understand and optimise the injection operation in blast furnaces.

Investigating the effects of powder feeding rate on microstructure transformation in linear laser beam additive manufactured thick-walled structures

The coarse columnar crystals that grow through multiple layers are commonly observed in laser additive manufactured structures, with fractures tending to occur in regions where there are abrupt changes in grain morphology. This can lead to a degradation of the mechanical properties of the samples. In this study on laser additive manufacturing, thick-walled structures made of 304 stainless steel were created using a linear beam spot with a rectangular powder feeding nozzle. By adjusting the powder feeding rate to influence the thermal cycling characteristics during the laser additive manufacturing process, a hierarchical grain structure that combines coarse and fine equiaxed grains was achieved, enhancing the forming efficiency and overall mechanical performance of the structure. The results from the thermal cycling characteristics and microstructure analysis indicate that increasing the powder feeding rate during the additive manufacturing process can decrease the hierarchical cooling rate, temperature gradient, and heat accumulation effect. This reduction in turn decreases the grain size and facilitates the transformation of columnar crystals into equiaxed crystals. Furthermore, the transformation of low-angle grain boundaries into high-angle grain boundaries in the interlayer region helps to reduce stress concentration, weaken anisotropic tendencies, and mitigate intergranular fracture tendencies, ultimately improving the mechanical properties of the overall structure. In actual engineering applications, the powder flow can be adjusted to control the temperature gradient and cooling rate of the deposition layer, thereby altering the grain morphology and optimizing the mechanical properties of additive manufacturing parts.

On the feasibility of a predictive model of mechanical properties of AM Inconel 718 thin wallets produced by DED-LB process monitored with thermal methods

AbstractNickel-based superalloys are widely used in applications requiring resistance to high temperatures and high strain rates. Various additive manufacturing (AM) processes, such as Laser Metal Deposition (LMD), a Directed Energy Deposition (DED) process, can be used to produce these components. The quality of the components depends on the process parameters, so it is crucial to investigate the influence of each parameter and their combinations through extensive experimental campaigns. In this scenario, it would be very important to predict the mechanical properties of the produced components through the online monitoring of the process parameters using non-destructive techniques, such as thermography. The aim of this work was to explore the feasibility to predict the mechanical properties of Inconel 718 thin wallets around 10 mm produced by DED-LB, based on the extraction of suitable thermal features directly during the production. An experimental campaign analysed the effect of different process parameters (laser power, scan speed, powder flow rate, and energy density) on the mechanical properties achieved. All sample production was monitored with an infrared uncooled camera integrated with the laser head moving at the same scan speed. After the process, hardness measurements and tensile tests in both growth directions were carried out for each sample to evaluate the mechanical behaviour of the "as-built" coupons and the influence of selected process parameters. Macrographic analyses of the material structure were performed to determine the morphology of the passes and the degree of overlap between different passes and layers. Various thermal features and statistical models were considered to demonstrate the possibility of establishing a predictive model. The obtained results demonstrated the correlation between the hardness and the apparent temperature assuming a confidence level of 95%, and the possibility of predicting in this sense the final macrostructure and the mechanical behaviour of the printed material considering an empirical model with the R2 coefficient around 0.8.

Numerical Simulation of Gas Atomization and Powder Flowability for Metallic Additive Manufacturing

The quality of metal powder is essential in additive manufacturing (AM). The defects and mechanical properties of alloy parts manufactured through AM are significantly influenced by the particle size, sphericity, and flowability of the metal powder. Gas atomization (GA) technology is a widely used method for producing metal powders due to its high efficiency and cost-effectiveness. In this work, a multi-phase numerical model is developed to compute the alloy liquid breaking in the GA process by capturing the gas–liquid interface using the Coupled Level Set and Volume-of-Fluid (CLSVOF) method and the realizable k-ε turbulence model. A GA experiment is carried out, and a statistical comparison between the particle-size distributions obtained from the simulation and GA experiment shows that the relative errors of the cumulative frequency for the particle sizes sampled in two regions of the GA chamber are 5.28% and 5.39%, respectively. The mechanism of powder formation is discussed based on the numerical results. In addition, a discrete element model (DEM) is developed to compute the powder flowability by simulating a Hall flow experiment using the particle-size distribution obtained from the GA experiment. The relative error of the time that finishes the Hall flow in the simulation and experiment is obtained to be 1.9%.

Development of a high-fidelity digital twin using the discrete element method for a continuous direct compression process. Part 1. Calibration workflow

In this work, a high-fidelity digital twin was developed to support the design and testing of control strategies for drug product manufacturing via direct compression. The high-fidelity digital twin platform was based on typical pharmaceutical equipment, materials, and direct compression continuous processes. The paper describes in detail the material characterization, the Discrete Element Method (DEM) model and the DEM model parameter calibration approach and provides a comparison of the system’s response to the experimental results for stepwise changes in the API concentration at the mixer inlet. A calibration method for a cohesive DEM contact model parameter estimation was introduced. To assure a correct prediction for a wide range of processes, the calibration approach contained four characterization experiments using different stress states and different measurement principles, namely the bulk density test, compression with elastic recovery, the shear cell, and the rotating drum. To demonstrate the sensitivity of the DEM contact parameters to the process response, two powder characterization data sets with different powder flowability were applied. The results showed that the calibration method could differentiate between the different material batches of the same blend and that small-scale material characterization tests could be used to predict the residence time distribution in a continuous manufacturing process.

A stethoscope-guided interpretable deep learning framework for powder flow diagnosis in cold spray additive manufacturing

Cold spray (CS) particle deposition, also known as cold spray additive manufacturing, has garnered great attention as an advanced additive manufacturing (AM) and surface deposition technology, facilitating rapid and scalable production of functional parts and surfaces in a solid-state manner. In CS, consistent and precise feeding of functional feedstock powders is crucial for achieving effective particle deposition. However, vibratory-based powder feeders often face challenges associated with powder delivery and powder segregation. This underscores the critical need for a precise diagnostic framework to effectively control powder flow during cold spraying. To this end, the present study proposes a powder flow monitoring framework for the CS process using a stethoscope sound-guided interpretable deep learning (IDL) model. Internal sound data from the vibrated powder feeder is collected through a stethoscope sensor to train a two-stage model. In the first stage, a convolutional autoencoder (CAE) is trained to build an unsupervised learning-based anomaly detector, which identifies classification thresholds based on the receiver operation characteristic curve. In the second stage, a convolutional neural network (CNN) model is trained as the powder flow diagnostic tool by considering process anomalies, namely (i) no powder flow; (ii) feeder clogging; and (iii) no gas flow. The results reveal that the stethoscope sound-guided model achieves a classification accuracy of 95% on the test set, significantly outperforming benchmark utilizing typical external-sound recording microphones in diagnosing CS powder flow. Furthermore, the model is visualized and interpreted by employing t-distribution stochastic neighbor embedding and integrated gradients techniques to enhance reliability of CS powder flow diagnosis. This research highlights the effectiveness of the stethoscope sound-guided IDL model for in situ powder flow monitoring and process diagnosis in the domain of cold spray additive manufacturing, contributing to effective particle deposition.

Investigation of correlations between powder functionalities and powder surface properties for milk protein ingredients

Milk protein powders are widely used ingredient in processed food products, meanwhile, characterization of powder functionalities is of technical challenge to the manufacturers of ingredients and consumer foods. Rapid evaluation methods or indicators are needed to fill the mentioned technological gap. This study aimed to investigate correlations between a series of powder functionalities and powder surface properties, which may be characterized using a relative rapid method. Six types of milk protein powder with 2 different batches were used as samples in this study. The powder wettability was determined based on a modified International Dairy Federation method. Powder flowability was determined using the Warren Spring cohesion measured by rheometer. The dispersibility was indicated by the median particle size at a designated dispersing time point. Regarding the surface properties, the contact angle of powder samples was determined by the sessile drop method using both water and diiodomethane as reference liquids. Subsequently, surface free energy was computed through the Owens, Wendt, Rabel, and Kaelble model. Pearson correlation analysis revealed meaningful correlations between surface properties (e.g., surface free energy, cohesion work, and adhesion work) and powder functionality attributes (e.g., wettability and flowability). This study suggests that the wettability and flowability of milk protein powders can be indicated by powder surface energy-related parameter, such as work of cohesion.

Powder-bed additive manufacturing: The effect of layer thickness on powder bed density

The effect of layer thickness (LT) on powder bed density (PBD) was experimentally studied. The effect of LT on PBD was found dependent on both the powder flowability and measurement scenario. In the measurement scenario of fixing the powder bed height, increasing LT decreased PBD of both free-flowing powders and cohesive powders. In the measurement scenario of fixing the number of powder layers, increasing LT did not significantly affect PBD of free-flowing powders but significantly decreased PBD of cohesive powders. These findings shed light on the inconsistent results in the literature and provide guidance on the design of future studies.

Experimental Study on the Mass Flow Rate Characteristics of a Fluidized Bed Powder Fuel Feeding System

In this study, a fluidized bed powder fuel feeding system that controls flow using the principle of two-phase gas-solid choking is proposed. Experiments based on real-time weighing methods were conducted to explore the flow rate characteristics under various total pressure and throttle-orifice area conditions. The experimental results showed that as the total pressure increased, the powder flow rate first decreased and then increased. To achieve the same increase in powder mass flow rate by altering the pressure, fine powder requires a greater pressure increment than coarse powder. A choked flow formula based on the gas-solid two-phase nonequilibrium model was derived, for investigating the influence of these two factors on the powder flow rate. Compared with the experimental results, this formula predicts the powder flow rates within a 20 % error margin. This model provides more precise guidance for engineering designs. The studied powder fuel-feeding system was connected to a powder engine, and hot-fire tests were conducted. The results showed that the pressure fluctuation in the powder engine combustion chamber did not exceed 2.5 %, confirming the feasibility and stability of the powder supply in the fluidized bed powder fuel feeding system.

Highly correlated deposition characteristics between individual elemental powders and elemental powder blends of MoNbTaTi in laser melt deposition

The laser melt deposition process often involves fabricating custom alloys from cost-effective elemental powder blends. However, discrepancies between the nominal ratio of the pre-mixed powders and the final composition of the deposited part are commonly observed due to variations in the material properties of the elemental powders. In this study, separate experiments were employed to investigate the relationship of deposition characteristics between individual elemental powders and elemental powder blends in the laser melt deposition process. To investigate the spatial distribution between elemental powder particles, powder flow characteristics in four different delivery systems were measured. Single-track deposition experiments were deployed to study the real powder catchment efficiency of elemental powder and the final composition of the deposited layer. In addition, a finite element model was established and validated with experimental data to predict the dilution rate and final chemical composition of the deposited layer. The experimental results indicate a strong correlation between the powder catchment efficiency of individual elemental powder and the final composition of the deposited layer. The simulation results agreed well with the actual composition of the deposited track. This study’s findings have the potential to predict and optimize the composition of the desired materials fabricated by elemental powder blends in the laser melt deposition process.

Assessing melt pool temperature independence from hardness via photodiode-based plank thermometry (PDPT)

Directed Energy Deposition (DED) has emerged as a promising metal additive manufacturing technique due to its ability to create components comparable or superior to traditional fabrication. Although industrial adoption of this technology is underway, there exists a considerable need to improve the predictability of the components it manufactures to promote wider adoption of this technology. Currently, melt pool temperature is the primary metric for build monitoring and control. However, stronger correlations must be established between the process parameters, including melt pool temperature, and resulting material outcomes to determine if melt pool control is a sufficient metric to control part quality. The goal of this research is to establish correlations between laser power (W), scanning speed (mm/s), powder flow rate (g/min), average melt pool temperature (C), and hardness. The average melt pool temperature was measured through Photodiode-based Planck thermometry (PDPT) with dual on-axis photodiodes. To obtain the correlation between these factors, 54 samples of Inconel 718 were printed, cross-sectioned, and tested using a Vickers diamond indenter. The resulting correlations exhibited extremely low R2 values and validated the findings of previous studies in that process parameters are exceedingly poor predictors of component properties. Average melt pool temperature lacked a significant correlation with hardness, instead process scanning speed demonstrated a more significant impact on the final material hardness. Since hardness is largely dictated by average grain size which in turn is controlled primarily by solidification rate, solidification rate should be the focus of future work to control material properties. The results of this study indicate that melt pool thermal control is not a sufficient metric to control part quality, and a solution is needed that can oversee the build process in such a way that solidification rate can be monitored and controlled in addition or instead of melt pool temperature. Future work must be done to apply the PDPT methodology to real time calibrated indirect measurement of melt pool solidification rates to improve prediction and control of final part mechanical properties.

Enhanced powder characteristics of succinic acid through crystallization techniques for food industry application

During crystallization, succinic acid, an important food additive, exhibit severe agglomeration behaviour, uneven crystal size distribution (CSD), and irregular crystal morphology, resulting in poor powder flow properties. This paper presents an innovative approach to optimize succinic acid crystallization through investigation of novel blade milling method, seeding, and inclusion of green additive, cetyltrimethylammonium bromide (CTAB). CTAB for crystal habit regulation and formation of desired cubic-like morphology. We employ Mask R-CNN, a deep learning-based image analysis tool to quantitatively assess crystal and powder flow properties. Results demonstrate that the inclusion of 0.5 wt% CTAB with two-stage cooling method yields uniform CSD ranging from 30 μm to 160 μm and improves powder properties, reducing the agglomeration degree by 46% and caking ratio to only 6.78%, indicating a decreased tendency for clumping. The integration of crystallization with the proposed deep learning framework not only improves succinic acid food functionality but also showcases highly efficient method for optimizing crystal properties, setting new standard for food crystallization processes. It has been adequately presented with real-time high-precision analysis of CSD, agglomeration, etc, facilitating rapid screening for optimized food quality improvements.

Chemometrics analysis of the flow and thermal properties of cardaba banana starch.

Starch from a non-conventional source such as cardaba banana is relatively underexplored compared to conventional sources such as potato, maize or tapioca. Its high amylose content, however, suggests its suitability for specific industrial uses. Understanding the flowability, rheology and thermal properties of cardaba banana starch could lead to its novel application in food product formulation and pharmaceutical industry. Therefore, the present study aimed to examine the effect of modification on the bulk material characterization (powder flowability), granule size and shape (measured by light microscope), rheology and thermal properties of cardaba banana starch. The flowability of cross-linked starch was affected significantly by the granule size (105 892.7 μm), shape (circularity 0.78) and compressibility (0.20), making it a more free-flowing powder than other starch powders. The rheological behavior of the starch paste revealed that the Herschel-Bulkley model best predicts the rheological behavior with the highest coefficient of determinant (R2 > 0.9). Cross-linked Cardaba banana starch with an excellent characteristic will find good application in food products that require free-flowing behavior. © 2024 Society of Chemical Industry.

Feasibility of a High-Dose Inhaled Indomethacin Dry Powder with Dual Deposition for Pulmonary and Oral Delivery

In this study we have developed a high-dose dry powder inhaler formulation of indomethacin using a novel approach to carrier-based formulations. Specifically, larger drug particles serve as the carrier for the smaller micronized drug particles, such that an inhaled dose is combined with an oral dose. To study this system, the aerosol performance of a standard indomethacin–lactose formulation was compared to carrier-free micronized indomethacin and a drug-as-carrier formulation (a micronized indomethacin–coarse indomethacin blend). Indomethacin with lactose showed a very poor aerosol performance, indicating high adhesion between the drug and carrier. The performance of the carrier-free micronized drug was significantly better, indicating low cohesion. Coarse drug particles as a carrier allowed improved powder flow and aerosol performance while also providing a potential secondary route of absorption of indomethacin, namely oral. An optimal formulation ratio of 1:1 (w/w) fine indomethacin–coarse indomethacin was developed in this study.

Research Progress and Current Status of Gas-Solid Two-Phase Flow Technology in the Direction of Laser Cladding.

In the process of laser cladding, there are usually problems such as powder plugging and uneven delivery, which affect the quality of the final cladding layer. Therefore, powder convergence characteristics in laser cladding need to be further improved. Gas-solid two-phase flow technology has been widely used in the study of powder flow characteristics because it can precisely regulate the interaction between carrier air and powder flow. In this paper, we systematically review the current status of gas-solid two-phase flow in the field of laser cladding powder, deeply analyze the latest optimization progress of laser cladding nozzle design, and comprehensively explain the key progress of gas-solid two-phase flow technology in improving the uniformity and efficiency of powder field distribution. At the end of this paper, the research results are summarized and a series of prospective prospects are proposed, aiming to provide a valuable reference framework and directional guidance for the subsequent related research.

Effect of Particle Size, Lubricant, and Heat Temperature on the Flowability of Ni-Based Powders for Additive Manufacturing

Effect of Particle Size, Lubricant, and Heat Temperature on the Flowability of Ni-Based Powders for Additive Manufacturing