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Additive manufacturing (AM) involves creating 3D objects, one ultra-thin layer at a time, making it more expensive than traditional processing. However, only a small portion of the powder is welded to the component during the assembly process. The rest do not fuse, so they can be reused. In contrast, if the object is created in the classical way, it usually requires milling and machining to remove material.
The properties of the powder determine the parameters of the machine and must be taken into account in the first place. The cost of AM would not be economical given that the unmelted powder is contaminated and not recyclable. Powder degradation results in two phenomena: chemical modification of the product and changes in mechanical properties such as morphology and particle size distribution.
In the first case, the main task is to create solid structures containing pure alloys, so we need to avoid contamination of the powder, for example, with oxides or nitrides. In the latter phenomenon, these parameters are associated with fluidity and spreadability. Therefore, any change in the properties of the powder can lead to a non-uniform distribution of the product.
Data from recent publications indicate that classical flowmeters cannot provide adequate information about the distribution of powder in AM based on the powder bed. Regarding the characterization of the raw material (or powder), there are several relevant measurement methods on the market that can satisfy this requirement. The stress state and the powder flow field must be the same in the measuring setup and in the process. The presence of compressive loads is incompatible with the free surface flow used in IM devices in shear testers and classical rheometers.
GranuTools has developed a workflow for characterizing AM powder. Our main goal is to equip each geometry with an accurate process simulation tool, and this workflow is used to understand and track the evolution of powder quality in various printing processes. Several standard aluminum alloys (AlSi10Mg) were selected for different durations at different thermal loads (from 100 to 200 °C).
Thermal degradation can be controlled by analyzing the ability of the powder to accumulate an electrical charge. The powders were analyzed for flowability (GranuDrum instrument), packing kinetics (GranuPack instrument) and electrostatic behavior (GranuCharge instrument). Cohesion and packing kinetics measurements are suitable for tracking powder quality.
Powders that are easy to apply will show low cohesion indices, while powders with fast filling dynamics will produce mechanical parts with lower porosity compared to more difficult to fill products.
After several months of storage in our laboratory, three aluminum alloy powders with different particle size distributions (AlSi10Mg) and one 316L stainless steel sample were selected, here referred to as samples A, B and C. The properties of the samples may differ from other manufacturers. Sample particle size distribution was measured by laser diffraction analysis/ISO 13320.
Because they control the parameters of the machine, the properties of the powder must be considered first, and if unmelted powders are considered contaminated and unrecyclable, then additive manufacturing is not as economical as one might hope. Therefore, three parameters will be investigated: powder flow, packing dynamics and electrostatics.
Spreadability is related to the uniformity and “smoothness” of the powder layer after the recoating operation. This is very important as smooth surfaces are easier to print and can be examined with the GranuDrum tool with adhesion index measurement.
Because pores are weak points in a material, they can lead to cracks. Fill dynamics is the second key parameter as fast filling powders provide low porosity. This behavior is measured with GranuPack with a value of n1/2.
The presence of electrical charges in the powder creates cohesive forces that lead to the formation of agglomerates. GranuCharge measures the ability of powders to generate an electrostatic charge when in contact with selected materials during flow.
During processing, GranuCharge can predict the deterioration of flow, for example, when forming a layer in AM. Thus, the obtained measurements are very sensitive to the state of the grain surface (oxidation, contamination and roughness). The aging of the recovered powder can then be accurately quantified (±0.5 nC).
The GranuDrum is a programmed powder flow measurement method based on the rotating drum principle. Half of the powder sample is contained in a horizontal cylinder with transparent side walls. The drum rotates around its axis at an angular speed of 2 to 60 rpm, and the CCD camera takes pictures (from 30 to 100 images at 1 second intervals). The air/powder interface is identified on each image using an edge detection algorithm.
Calculate the average position of the interface and the oscillations around this average position. For each rotation speed, the flow angle (or “dynamic angle of repose”) αf is calculated from the mean interface position, and the dynamic cohesion factor σf associated with intergrain bonding is analyzed from interface fluctuations.
The flow angle is affected by a number of parameters: friction, shape and cohesion between particles (van der Waals, electrostatic and capillary forces). Cohesive powders result in intermittent flow, while non-viscous powders result in regular flow. Low values ​​of the flow angle αf correspond to good flow. A dynamic adhesion index close to zero corresponds to a non-cohesive powder, so as the adhesion of the powder increases, the adhesion index increases accordingly.
GranuDrum allows you to measure the first angle of the avalanche and the aeration of the powder during the flow, as well as measure the adhesion index σf and the flow angle αf depending on the rotation speed.
The GranuPack’s bulk density, tapping density and Hausner ratio measurements (also known as “tapping tests”) are ideal for powder characterization due to their ease and speed of measurement. The density of the powder and the ability to increase its density are important parameters during storage, transportation, agglomeration, etc. Recommended procedures are outlined in the Pharmacopoeia.
This simple test has three major drawbacks. The measurement depends on the operator, and the method of filling affects the initial volume of the powder. Measuring total volume can lead to serious errors in the results. Due to the simplicity of the experiment, we did not take into account the compaction dynamics between the initial and final measurements.
The behavior of the powder fed into the continuous outlet was analyzed using automated equipment. Accurately measure the Hausner coefficient Hr, initial density ρ(0) and final density ρ(n) after n clicks.
The number of taps is usually fixed at n=500. The GranuPack is an automated and advanced tapping density measurement based on recent dynamic research.
Other indexes can be used, but they are not provided here. The powder is placed into a metal tube through a rigorous automated initialization process. The extrapolation of the dynamic parameter n1/2 and the maximum density ρ(∞) has been removed from the compaction curve.
A lightweight hollow cylinder sits on top of the powder bed to keep the powder/air interface level during compaction. The tube containing the powder sample rises to a fixed height ΔZ and falls freely at a height usually fixed at ΔZ = 1 mm or ΔZ = 3 mm, which is automatically measured after each touch. Calculate the volume V of the pile from the height.
Density is the ratio of the mass m to the volume of the powder layer V. The mass of the powder m is known, the density ρ is applied after each impact.
The Hausner coefficient Hr is related to the compaction factor and is analyzed by the equation Hr = ρ(500) / ρ(0), where ρ(0) is the initial bulk density and ρ(500) is the calculated flow after 500 cycles. Density tap. When using the GranuPack method, results are reproducible using a small amount of powder (usually 35 ml).
The properties of the powder and the properties of the material from which the device is made are key parameters. During the flow, electrostatic charges are generated inside the powder due to the triboelectric effect, which is the exchange of charges when two solids come into contact.
When the powder flows inside the device, a triboelectric effect occurs at the contact between the particles and at the contact between the particles and the device.
Upon contact with the selected material, the GranuCharge automatically measures the amount of electrostatic charge generated inside the powder during flow. The powder sample flows inside the vibrating V-tube and falls into a Faraday cup connected to an electrometer that measures the charge acquired as the powder moves inside the V-tube. For reproducible results, use a rotating or vibrating device to feed V-tubes frequently.
The triboelectric effect causes one object to gain electrons on its surface and thus become negatively charged, while another object loses electrons and thus becomes positively charged. Some materials gain electrons more easily than others, and similarly, other materials lose electrons more easily.
Which material becomes negative and which becomes positive depends on the relative propensity of the materials involved to gain or lose electrons. To represent these trends, the triboelectric series shown in Table 1 was developed. Materials with a positive charge trend and others with a negative charge trend are listed, and material methods that do not show any behavioral trend are listed in the middle of the table.
On the other hand, the table only provides information on trends in the charging behavior of materials, so GranuCharge was created to provide accurate numerical values ​​for the charging behavior of powders.
Several experiments were carried out to analyze thermal decomposition. The samples were placed at 200°C for one to two hours. The powder is then immediately analyzed with GranuDrum (hot name). The powder was then placed in a container until reaching ambient temperature and then analyzed using GranuDrum, GranuPack and GranuCharge (i.e. “cold”).
Raw samples were analyzed using GranuPack, GranuDrum and GranuCharge at the same room humidity/temperature (i.e. 35.0 ± 1.5% RH and 21.0 ± 1.0 °C temperature).
The cohesion index calculates the flowability of powders and correlates with changes in the position of the interface (powder/air), which is only three contact forces (van der Waals, capillary and electrostatic forces). Before the experiment, the relative air humidity (RH, %) and temperature (°C) were recorded. Then the powder was poured into the drum, and the experiment began.
We concluded that these products are not susceptible to agglomeration when considering thixotropic parameters. Interestingly, thermal stress changed the rheological behavior of the powders of samples A and B from shear thickening to shear thinning. On the other hand, Samples C and SS 316L were not affected by temperature and only showed shear thickening. Each powder had better spreadability (ie lower cohesion index) after heating and cooling.
The temperature effect also depends on the specific area of ​​the particles. The higher the thermal conductivity of the material, the greater the effect on temperature (i.e. ???225°?=250?.?-1.?-1) and ???316?. 225°?=19?.?-1.?-1) The smaller the particle, the greater the effect of temperature. Aluminum alloy powders are excellent for high temperature applications due to their increased spreadability, and even cooled specimens achieve better flowability than the original powders.
For each GranuPack experiment, the mass of the powder was recorded before each experiment, and the sample was hit 500 times with an impact frequency of 1 Hz with a free fall of 1 mm in the measuring cell (impact energy ∝). The sample is dispensed into the measuring cell according to user-independent software instructions. Then the measurements were repeated twice to assess the reproducibility and investigated the mean and standard deviation.
After the GranuPack analysis is completed, initial bulk density (ρ(0)), final bulk density (at multiple taps, n = 500, i.e. ρ(500)), Hausner ratio/Carr index (Hr/Cr) and two registration parameters (n1/2 and τ) related to compaction kinetics. The optimal density ρ(∞) is also shown (see Appendix 1). The table below restructures the experimental data.
Figures 6 and 7 show the overall compaction curve (bulk density versus number of impacts) and the n1/2/Hausner parameter ratio. Error bars calculated using the mean are shown on each curve, and standard deviations were calculated by repeatability testing.
The 316L stainless steel product was the heaviest product (ρ(0) = 4.554 g/mL). In terms of tapping density, SS 316L remains the heaviest powder (ρ(n) = 5.044 g/mL), followed by Sample A (ρ(n) = 1.668 g/mL), followed by Sample B (ρ(n) = 1.668 g/ml). /ml) (n) = 1.645 g/ml). Sample C was the lowest (ρ(n) = 1.581 g/mL). According to the bulk density of the initial powder, we see that sample A is the lightest, and taking into account the errors (1.380 g / ml), samples B and C have approximately the same value.
As the powder is heated, its Hausner ratio decreases, and this only occurs with samples B, C, and SS 316L. For sample A, it was not possible to perform due to the size of the error bars. For n1/2, the parametric trend underlining is more complex. For sample A and SS 316L, the value of n1/2 decreased after 2 h at 200°C, while for powders B and C it increased after thermal loading.
A vibrating feeder was used for each GranuCharge experiment (see Figure 8). Use 316L stainless steel tubing. Measurements were repeated 3 times to assess reproducibility. The weight of product used for each measurement was approximately 40 ml and no powder was recovered after measurement.
Before the experiment, the weight of the powder (m.p., g), relative air humidity (RH, %), and temperature (°C) were recorded. At the start of the test, the charge density of the primary powder (q0 in µC/kg) was measured by placing the powder in a Faraday cup. Finally, the powder mass was fixed and the final charge density (qf, µC/kg) and Δq (Δq = qf – q0) at the end of the experiment were calculated.
The raw GranuCharge data are shown in Table 2 and Figure 9 (σ is the standard deviation calculated from the results of the reproducibility test), and the results are shown as a histogram (only q0 and Δq are shown). SS 316L has the lowest initial charge; this may be due to the fact that this product has the highest PSD. When it comes to initial loading of primary aluminum alloy powder, no conclusions can be drawn due to the size of the errors.
After contact with a 316L stainless steel pipe, sample A received the least amount of charge, while powders B and C showed a similar trend, if SS 316L powder was rubbed against SS 316L, a charge density close to 0 was found (see triboelectric series) . Product B is still more charged than A. For sample C, the trend continues (positive initial charge and final charge after leakage), but the number of charges increases after thermal degradation.
After 2 hours of thermal stress at 200 °C, the behavior of the powder becomes very interesting. In samples A and B, the initial charge decreased and the final charge shifted from negative to positive. SS 316L powder had the highest initial charge and its charge density change became positive but remained low (ie 0.033 nC/g).
We investigated the effect of thermal degradation on the combined behavior of aluminum alloy (AlSi10Mg) and 316L stainless steel powders, while the original powders were analyzed after 2 hours at 200°C in air.
The use of powders at elevated temperatures can improve product flowability, an effect that appears to be more important for powders with high specific area and materials with high thermal conductivity. GranuDrum was used to evaluate flow, GranuPack was used for dynamic packing analysis, and GranuCharge was used to analyze the triboelectricity of powder in contact with 316L stainless steel pipe.
These results were determined using GranuPack, which showed an improvement in the Hausner coefficient for each powder (with the exception of sample A, due to the size of the errors) after the thermal stress process. No clear trend was found for the packing parameter (n1/2) as some products showed an increase in packing speed while others had a contrasting effect (eg Samples B and C).