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Among the various additive manu- facturing (AM) processes either in use or under development, e.g., metal powder bed fusion (PBF) and ce-ramic binder jetting, several employ powder feedstocks. As a result of manu-facturing artifacts and inter-particle forc-es, powder materials exhibit properties that depart from those of bulk materi-als in other forms. Manufacturing condi-tions can affect all aspects of individual particle properties, which in turn affect attractive particle interactions such as adhesion and non-bonded van der Waals forces[1,2]. Differences in these properties manifest themselves in the dynamics of powder flow and subsequent particle fu-sion, which must be optimal to achieve fully densified parts.

In some cases, conventional pow-der characterization techniques pro-vide useful information when adapting powders to AM processes. Yet there are many cases where the techniques fail to adequately distinguish enough in-formation to enable process optimiza-tion[2,3]. The most common example is the use of static flow characterization methods (such as Hall or Carney fun-nel flowrate tests) to quantify powder flowability or spreadability. Additive manufacturers have found that these methods often provide little or no use-ful information to explain observed differences in flow behavior between virgin and recycled powders or powders

with varying levels of moisture content, for example.

A recent study from the Massachu-setts Institute of Technology[2] present-ed a dramatic difference in the surface energy of three Ti-6Al-4V PBF powders (0.1 mJ/m2) compared to bulk metals (40-50 mJ/m2). Results were attributed to parameters such as surface rough-ness, surface chemistry, and surface oxidation, and the study explained why conventional metrics such as angle of repose fail to properly represent bulk behavior in metal AM powders. There-fore, a suite of advanced characteri- zation techniques is now being de-ployed across the full range of the AM powder supply chain. In most cases, these are well-established methods that have found common use in fields such as catalysis, mining, pharmaceuticals, and glass.

A joint effort between ASTM and ISO is working toward standardization of powder characterization techniques for AM, borrowing from existing stan-dards in other fields as well as devel-oping new standards unique to AM. The Additive Manufacturing Consortium operated by EWI is concurrently pro-viding data to support standardization through a varied portfolio of R&D proj-ects. Nonetheless, several notable gaps in AM-specific powder characterization still exist: sample conditioning, particle

morphology, moisture analysis, and powder flow characterization. In this article, a few of the myriad characteri-zation options available to particle sci-entists will be discussed.

It is useful to describe individu-al powder properties with respect to the scale at which they are manifest-ed—the core material level, the formed particle level, or the bulk powder level. As an example, a few of the most com- mon powder characterization tech-niques are categorized using a matrix of material scale and four property cate-gories (Table 1).

SAMPLING AND CONDITIONING

Note the inclusion of sampling and conditioning methods at the top of the matrix in Table 1. Although not characterization techniques per se, it is critical that these are not overlooked or discounted when dealing with pow-der samples. Proper powder sampling techniques must be used in order to produce representative samples for subsequent laboratory analysis. The unique nature of powders can also lead to self-segregation during conveyance, storage, packing, and handling[4]. In one example, a 2014 NIST study revealed significant variability in chemical com-position among four sub-samples taken from a single lot of a cobalt-chromium

ADVANCED POWDER CHARACTERIZATION FOR ADDITIVE MANUFACTURINGAs powder-based additive manufacturing (AM) processes continue to mature, reliable powder characterization techniques will be key to optimizing both AM processes and final part performance.Dave van der Wiel NSL Analytical Services Inc., Cleveland

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AM alloy, as well as two sieve frac-tions within a recycled stainless steel powder[5].

Standard practices for represen-tative powder sampling at all scales are well established[6,7]. At the laborato-ry level (typically

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One drawback of many of these ap-proaches is the necessity to simplify complex or irregular shapes into equiv-alent ideal geometries, analogous to how laser scattering particle size data is fit to equivalent spherical diameters. Another problem with some of these techniques is the limitation of analyzing particles with 2D imaging, where a par-ticle outline or shadow is used to repre-sent an entire particle. A third challenge in microscopy techniques is the limit-ed number of particles that can be ana-lyzed in each image, often on the order of 100 particles or fewer. Nonetheless, dynamic image analysis instrumenta-tion is evolving rapidly and could soon become a benchmark technique.

In contrast to these approaches, the use of well-established gas adsorp-tion techniques provides a way to probe bulk quantities of a powder—with parti-cle quantities ranging from thousands

to hundreds of thousands. The BET (Brunauer-Emmett-Teller) method uses condensation of krypton or nitrogen gas on a powder surface at cryogen-ic conditions, measuring the resulting gas pressure change to quantify the ex-posed surface area of powder. Well-es-tablished in powder metallurgy[8], the method is also used extensively in ce-ramics, pharmaceuticals, and geology to characterize particle morphology[9-12]. The specific surface area is reflective of the particle size, shape, texture, and porosity. It can therefore also serve as a way to quantify defects in a large en-semble of particles.

A rigorous analysis of the rela-tive contributions of particle size and morphology to BET surface area was conducted by Corning using XRD crys-tallography and electron microscopy to demonstrate the strong correlation between these properties in talc pow-

ders[13]. For routine analyses, gas ad-sorption is therefore an excellent way to conduct true 3D, bulk morphological analysis much more efficiently and pre-cisely than other methods. When inves-tigating specific morphology issues, it is useful to couple this with microscop-ic analyses.

BULK POWDER PROPERTIESOne of the traits of the energet-

ics of fine powder surfaces described above is that these forms of materials tend to absorb ambient moisture much more readily than they do in other forms[3]. Both metals and ceramics ex-hibit this behavior, impacting powder flow and final part chemistry and den-sity[14-16]. However, depending on the material, the absolute amount of mois-ture can still be very low and is often less than 0.5 wt% for metal powders. Therefore, conventional oven-based

TABLE 3 — PARTICLE SCALE MORPHOLOGY PARAMETER CHARACTERISTICS AND TECHNIQUESParticle scale

Macroshape MesoshapeSurface/textural scale

Descriptors Sphericity,elongation, etc.

Circularity,angularity, etc.

Roughness Surface area

Nature 3D 2D 2D 3DBasis Equivalent dimensions

or volumeEquivalent area or

perimeter

Comparative geometries

Geometric analysis(ratios, etc.)

Pressure measurement

Techniques Dynamic or static digital imaging,optical or electron microscopy,

tomography, laser scattering

Gas adsorption(BET)

Sample representation

Microscopy (static imaging): ≈ Hundreds of particlesLaser or dynamic Imaging: Tens of thousands of particles

Tens of thousands of particles

TABLE 4 — MOISTURE ANALYSIS TECHNIQUES AND LIMITATIONSNon-specific

Technique LimitationsWater-specific

Technique Limitations

Chemical Karl FischerCalcium carbide

LaboriousComplex

Spectroscopic TPD/TDS Precision TPD-MS/TDMSNear IR

PrecisionSample prep

Thermogravimetric Oven/vacuumMicrowaveHalogen IRTGA/DSC

Slow>2% H2O

DecompositionMethod

RH sensorTGA-MS

SlowSample size, method

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(loss-on-drying) techniques are usual-ly too imprecise. While the Karl Fischer titration method is water-specific, it is comparatively complex and laborious. The very small sample sizes used in TGA methods often lead to poor precision. Halogen IR methods (already standard-ized for determining moisture in plas-tics) are perhaps the most promising technique, especially because they can accommodate fairly large sample sizes (up to 200 g) and are simple to operate. Nonetheless, the low moisture levels in metal powders require the most ad-vanced (and expensive) versions of these instruments, with some users still reporting insufficient sensitivity. See Table 4.

Bulk powders are often character-ized according to one or more types of density. Each type may be useful in an-alyzing powder impacts on the various stages of material densification that oc-cur in powder AM processes, from pow-der spreading to final sintering. Along with apparent (or bulk) density (both loose and tapped), skeletal density continues to be an important powder property for optimizing final AM part density. This parameter is measured through the well-established technique of gas displacement pycnometry, most often using a helium pycnometer with

microcell chambers to improve preci-sion in smaller sample volumes. An at-tractive aspect of this technique is that the same instrument can be used to measure the true (or absolute) density of a sample from a final part.

Perhaps the most active area of development in powder characteriza-tion for AM is the field of powder flow analysis. Table 5 summarizes the var-ious static, quasi-static, and dynam-ic techniques commonly in use, along with the author’s opinions on their ap-plication to AM powders.

Dynamic flow analysis techniques are of particular relevance to pow-der AM applications, where recoater spreading is an example of a dynamic environment under a low stress state. In many cases, when conventional stat-ic funnel testing cannot distinguish be-tween different powders (or when the powders will not flow through the fun-nels), avalanche/drum type rheometers will consistently differentiate between samples. Further, the instruments allow for parametric evaluation to identify “sweet spots” in powder flow behavior, correlating with recoater roller trans-versal speed or rotation speed/direc-tion, for example.

The ASTM powder metallurgy sub- committee recently sponsored a round

robin test to evaluate the ability of three commercial instruments (one quasi- static and two dynamic) to distinguish between six different AM powder sam-ples. Dynamic avalanche-type instru-ments were best able to differentiate samples based on material type and history (virgin, recycled, or blended). Data presented in the ASTM study, as well as the author’s own experience using an avalanche rheometer, shows that most parameters can achieve good reproducibility.

SUMMARYAs powder-based AM processes

continue to mature, various combina-tions of the powder characterization techniques discussed here will be key to optimizing AM processes and final part performance. At the same time, some of these methods can provide rapid feedback for manufacturing control, powder qualification, and yield optimi-zation. It is important for those involved in the powder supply chain to appre-ciate the unique nature of powders, which results in their distinct behav-iors—making proper powder sampling crucial. Well-established advanced characterization techniques such as krypton BET adsorption, helium pyc-nometry, and powder XRF can provide

TABLE 5 — POWDER FLOW ANALYSIS TECHNIQUES AND CHARACTERISTICSPowder Flow Analysis Techniques

Static Quasi-static Dynamic

Methods Hall, Carney, etc. Shear cell, impeller Avalanche/drumQualitative Yes/No Flow regimes

Semi-quantitative FlowabilityFlow rate

Angle of repose

Stress curvesFlowability energy

Flow functionWall friction angle

Surface fractalAvalanche energy

Cohesive indexAvalanche angle

Rest angle

Quantitative Carr indexHausner ratio

Volume changes Volume changeVolume memory

Apparent density Conditioned densityConsolidation index

Dynamic densityVibrated density

Stress state Low Moderate to high LowEase of operation Simple Complex Simple

Data interpretation Simple Complex ValuesParametric analysis No Yes Yes

Standardization ASTM, ISO ASTM (plastics) No

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more meaningful data to solve man-ufacturing challenges. In the near fu-ture, new and improved techniques like halogen IR moisture analysis, dynamic image analysis, and dynamic rheome-try promise to provide much improved data streams. ~AM&P

For more information: Dave van der Wiel, analytical operations manag-er, NSL Analytical Services Inc., 4450 Cranwood Pkwy., Cleveland, OH 44128, 216.438.5215, dvanderwiel@nslanalyti-cal.com, www.nslanalytical.com.

References1. A. Castellanos, Adv. Phys., Vol 54, p 263-376, 2005.2. C. Meier, et al., Powder Technol., Vol 343, p 855-866, 2019.3. J.A. Muñiz-Lerma, et al., Materials, Vol 11 (12), p 2386, 2018.4. J.M. Nicholas and T. Gray, Annu. Rev. Fluid Mech., Vol 50, p 407-433, 2018.5. J.A. Slotwinski, et al., J. Res. Natl. Inst. Stand. Technol., Vol 119, p 460, 2014.

6. A. Jillavenkatesa, et al., NIST Special Publication 960-1, 2001.7. ASTM Standard Practice B215-15.8. ASTM Standard Test Method B922-17.9. D. Faroongsarng and G.E. Peck, Drug Dev. Ind. Pharm., Vol 20 (15), p 2353-2367, 1994.10. C. Papelis, et al., Coll. Surf. A Phys. Eng. Asp., Vol 215 (1–3), p 221-239, 2003.11. O.P. Mills and W.I. Rose, Geosphere,

Vol 6 (6), p 805-811, 2010.12. T. Theivasanthi and M. Alagar, arX-iv:1307.1091, 2013.13. H.J. Holland and M.J. Murtagh, Adv. X-ray Anal., Vol 42, p 421-428, 2000.14. G. Matei, et al., Mod Dev in Powder Metall., Vol 8, p 5-11, 1974.15. N. Vluttert, bachelor's degree the-sis, University of Twente, 2016.16. P. Mellin, et al., Met. Powder Rep., at press, 2019.

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