Operando X-ray diffraction study of thermal and phase evolution during laser powder bed fusion of Al-Sc-Zr elemental powder blends

doi:10.1016/j.addma.2022.102806

Additive Manufacturing

Volume 55, July 2022, 102806

https://doi.org/10.1016/j.addma.2022.102806 Get rights and content

Abstract

Elemental powder blends are an emerging alternative to prealloyed powders for high-throughput alloy design via additive manufacturing techniques. Elemental Al+Sc(+Zr) powder blends were processed by laser powder bed fusion into Al-Sc and Al-Sc-Zr alloys, with operando X-ray diffraction at the Swiss Light Source extracting the structural and thermal history of the process. The pure Sc and Zr particles were found to react with the molten Al pool at 550–650 °C, well below their respective melting temperatures. Various scan areas (1 × 1, 2 × 2, 4 × 4, and 8 × 2 mm²) were studied to compare (i) the base plate “preheating” effect caused by prior laser scans, (ii) the return temperature reached after the melting scan and before the following scan, (iii) the initial cooling rate immediately after solidification, and (iv) the time spent in the “intrinsic heat treatment range”, defined as 300–650 °C, where secondary Al₃(Sc,Zr) precipitation occurs. Microstructural analysis of the as-built samples show 110–140 nm L1₂-Al₃(Sc,Zr) primary precipitates at the bottom of the melt pool. The 1 × 1 mm² samples exhibit the most elongated grains (long axis of 10 ± 5 µm), which correlates with the highest build plate temperature and the slowest initial cooling rate (3–5 × 10⁵ K/s). In comparison, the 4 × 4 mm² samples exhibit the smallest equiaxed grains (2 ± 0.6 µm), corresponding to the lowest build plate temperature and the fastest initial cooling rate (6–7 × 10⁵ K/s). These results indicate the need for establishing a minimum feature size during part design, or for modifying the laser parameters during processing, to mitigate microstructure and performance differences across features of different sizes.

Keywords

Selective laser melting

Operando diffraction

Elemental blends

Additive manufacturing

Aluminum

1. Introduction

Laser powder bed fusion (L-PBF) is the most commonly used additive manufacturing (AM) technique for aluminum alloys [1]. Early work has focused on Si-containing cast alloys (AlSi10Mg, AlSi7Mg) due to the easily-achievable high density and low susceptibility to cracking; however, these cast alloys are not suitable for usage at high temperatures (>250 °C). Subsequent L-PBF studies incorporated Zr in Si-free Al alloys, leading to formation of primary L1₂-Al₃Zr to nucleate small, equiaxed Al grains with a high resistance to hot cracking [2].

Most powder-bed AM processes use prealloyed powder, in which each powder particle contains all constituent elements in the same ratio as in the final alloy. This technique is cost-efficient for industrial-scale production of parts with optimized compositions, but not for the alloy design process, which may require many iterations of different elements in different ratios. An alternative AM approach uses mixed elemental powders, as demonstrated in directed energy deposition (DED) of high entropy alloys (HEAs) [3], [4], [5], [6], [7], [8], [9], [10], [11], and in L-PBF of binary alloys such as Ti-X (X = Ni, Nb, Ta, Al, V, Zr, Cr, Mo) [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], Ni-Sn [23], Fe-Cu [24], Al-Cu [25], [26], and Al-Si [27], [28], [29]. Prior work showed the dissolution and reaction process during L-PBF single-line scans of elemental blends of Al-Sc, Al-Zr, and Al-Sc-Zr to create compositionally- and microstructurally-homogeneous dilute alloys [30], expanding the ability to design precipitation-strengthened Al-base alloys from elemental blends. The present study builds on that prior work by investigation, via synchrotron X-ray diffraction, the operando dissolution and reaction of elemental Sc and Zr particles in the Al matrix during layer-wise printing of bulk samples.

In situ and operando synchrotron studies of single melt pool tracks, constituent phase evolution, and the entire layer-wise AM process have been performed previously using in situ X-ray imaging [31], [32] and diffraction [33], [34] during L-PBF. Melt pool spatter, particle interactions, Marangoni convection and flow, and porosity formation have been the focus of multiple in situ synchrotron X-ray imaging studies [35], [36], [37], [38], [39], [40], [41], [42]. Hocine et al. built the miniSLM - a custom, portable small-scale L-PBF machine compatible with multiple beamlines at the Swiss Light Source - to directly observe the phase evolution of Ti-6Al-4V in small-scale builds via synchrotron X-ray diffraction [43], [44]. In the present work, this instrument is employed for the first time on Al-base alloys.

When progressing from single-line scans to full multilayer AM builds, generating a laser scan path to fill the processing area in an optimal way is an entire area of work within the AM field [45]. The scan path affects not only build time and surface roughness, but also heat accumulation, solidification rate, and resulting microstructure, which affect the properties of the consolidated material. A popular tool path to reduce residual stresses and warpage is a “checkerboard” or “island pattern” strategy[46], subdividing a large area into small fields scanned in a random order. Previous work has reviewed the microstructure, mechanical properties, and residual stresses of the nickel-base alloy INCONEL 718 printed with 2 × 2, 3 × 3, 5 × 5, and 7 × 7 mm² square areas [47]. The present study investigates the effect of different island sizes (1 × 1, 2 × 2, 4 × 4, and 8 × 2 mm²) on the microstructure of Al-Sc(-Zr) printed parts, to inform tool-path selection for L-PBF Al alloys in the future.

In this work, the reaction of elemental Sc and Zr powders with liquid aluminum is observed directly via operando diffraction in Al-Sc and Al-Sc-Zr powder blends during L-PBF, with a temporal resolution of 50 µs. The Sc/Zr dissolution into the Al melt pool is followed by precipitation of primary L1₂-Al₃Sc and -Al₃(Sc,Zr) phases, respectively, which act as grain refiners, thus enabling crack-free AM processing of Al alloys. Excess Sc and Zr remain in supersaturated solid solution in the Al matrix and are available for secondary precipitation of L1₂ nanoprecipitates upon aging heat-treatments. From the operando diffraction data, the local thermal history for each sample is extracted via the measured lattice expansion, providing quantitative measurements of (i) the influence of scan area size on the heat buildup prior to melting, (ii) the return temperature reached between subsequent laser passes, (iii) the initial cooling rate immediately after solidification, and (iv) the time spent in the intrinsic heat treatment range (300 – 650 °C) after each laser pass, which can cause precipitation of secondary phases over an entire multilayer build.

2. Materials and methods

2.1. Elemental powder characterization and mixing

Powders of aluminum (99.7% pure, 30 µm average size, from US Research Nanomaterials, Inc.), scandium (99.5% pure, 44 µm average size, from Nanografi Inc.), and zirconium (99% pure, <44 µm size, from US Research Nanomaterials, Inc.) were combined to create Al-Sc and Al-Sc-Zr elemental blends, as shown in Table 1. The powders were mixed by rotational ball-milling for 3 h in an argon atmosphere, using yttria-stabilized zirconia balls (6.5 and 12 mm diameter) in high-density polyethylene vials at a 5:1 ball-to-powder ratio. This low-energy blending does not mechanically alloy the powders, which maintain a round shape for good flowability. More details can be found in a previous study [30]. The elemental powders were examined via SEM and energy dispersive X-ray spectroscopy (EDS) to determine their morphology, as shown in Fig. 1.

Table 1. Compositions of Al-Sc(-Zr) elemental powder blends used for L-PBF.

Alloy	Sc	Zr
Al-Sc	0.52 at% 0.86 wt%	–
Al-Sc-Zr	0.26 at%	0.26 at%
Empty Cell	0.43 wt%	0.87 wt%

2.2. Laser powder bed fusion via miniSLM

Offline manufacturing of the different alloys was performed to establish a set of optimized laser parameters maximizing the build density prior to the operando, in situ experiments. The experimental setup enlisted the miniSLM, a custom-built, small-scale L-PBF machine; details are given in previous works by Hocine et al. [43], [44]. In brief, the miniSLM is a self-contained chamber which can be mounted in a beamline and tilted up to 20° for operando X-ray experiments in either transmission or reflection mode. The chamber, containing a 12 × 12 mm² build plate with a 10 × 10 × 5 mm³ available build volume, is continuously flushed with high-purity Ar (99.998%) gas during printing and is equipped with a high-energy, continuous-wave laser beam with a 1070 ± 10 nm wavelength and a maximum power of 500 W, mounted on a 2-axis scanning unit. For this work, a constant laser spot size of 100 µm was used. The baseplates for L-PBF were machined from a rod of 99.999% pure Al (Goodfellow, Inc.) instead of other commonly used alloys (e.g., AlSi10Mg) to minimize contamination from the baseplate into the elemental powder blends. Processing was performed with a variety of laser parameter combinations, ranging from 200 to 400 W power, 200–675 mm/s beam velocity, 30–70 µm layer thickness, and 70–90 µm hatch spacing, corresponding to energy densities between 90 and 312 J/mm³ where energy density is given as $Ψ = P / (v * h * t)$ (P = power in W, v = velocity in mm/s, h = hatch spacing in mm, and t = layer thickness in mm). Previous in situ X-ray imaging experiments using comparable laser parameters (P = 350 W, v = 350–600 mm/s) resulted in conduction mode, which is taken to be the case in this work [30]. Ten sets of laser parameters producing the densest builds were selected from this range, with energy densities of 225 and 259 J/mm³, as shown in Table 2.

Table 2. Laser parameter combinations for L-PBF of Al-Sc and Al-Sc-Zr.

Laser power (W)	Scan speed (mm/s)	Hatch spacing (µm)	Layer thickness (µm)	Energy density (J/mm³)
325	451	80	40	225
325	392	80	40	259
350	389	80	50	225
350	338	80	50	259
350	486	80	40	225
350	423	80	40	259
375	417	80	50	225
375	362	80	50	259
375	521	80	40	225
375	452	80	40	259

2.3. Operando X-ray diffraction

Operando X-ray diffraction was performed in reflection mode at the Swiss Light Source (SLS) at the Materials Science beamline (MS-X04SA), using a monochromatic 12 keV beam on an 8 × 2 mm² rectangular laser scan area (Fig. 2, top), and at the microXAS beamline (X05LA) using a monochromatic 9.3 keV beam in a series of 1 × 1, 2 × 2, and 4 × 4 mm² laser scan areas (Fig. 2, bottom). Multiple layers (at least five per sample) were built for each sample geometry, with several-minute-long pauses between subsequent layers for static diffraction patterns to be recorded.

An 8 × 2 mm² sample area was printed at the MS beamline, and 1 × 1, 2 × 2, and 4 × 4 mm² square sample areas were printed at the microXAS beamline, with a bidirectional scan strategy and 90° layer rotation. The diffraction volume was focused at the horizontal center of each sample area during laser scanning and at the downstream end of the scan area (as illustrated in Fig. 2). The sample was positioned 80 mm from an ultrafast single photon EIGER detector, shown on the right side of the schematic in Fig. 2.

The X-ray beam at the MS beamline was focused to 130 $\hat{x}$ × 60 $\hat{y}$ µm² (FWHM) and the sample was tilted at a 15° angle with respect to the X-ray source, resulting in a projected area of 130 $\hat{x}$ × 230 $\hat{y}$ µm² and allowing an X-ray penetration depth of 72 $\hat{z}$ µm into the sample, estimated assuming 10% transmission through the sample. The X-ray beam at the microXAS beamline was focused with Kirkpatrick-Baez mirrors to 80 $\hat{x}$ × 36 $\hat{y}$ µm² (FWHM) and the sample was tilted at a 20° angle with respect to the X-ray source, resulting in a projected area of 80 $\hat{x}$ × 105 $\hat{y}$ µm² and allowing an X-ray penetration depth of 42 $\hat{z}$ µm into the sample, estimated in the same way. The tails of the beams extend to roughly twice the projected areas; thus, the majority (~63%) of the signal originates from particles located in the FWHM of the beam, but some signal from particles located in the tails of the beams may be captured as well. Fig. 2 shows the approximate diffraction volumes (using the FWHM) of the experimental setups at the MS (top) and microXAS (bottom) beamlines, with 15–30 µm powder particles included within each diffraction volume for scale. Depending on the specific particle size distribution, approximately 50–100 particles are contained within a given MS diffraction volume and 10–20 within a given microXAS diffraction volume. The atomic compositions of Al-0.52Sc and Al-0.26Sc-0.26Zr (at%) are equivalent to volumetric compositions of Al-0.78Sc and Al-0.39Sc-0.37Zr (vol%); assuming all Al, Sc, and Zr particles are approximately the same size, this equates to one Sc or Zr particle for every 130 Al particles. Thus, the diffraction volume at the MS beamline has a much higher probability of capturing a Sc or a Zr particle during the operando experiment than the diffraction volume at the microXAS beamline. Conversely, the smaller beam at the microXAS beamline provides less volume-averaging for temperature measurements. An approximate melt pool is overlaid in red on the two diffraction volumes represented in blue in Fig. 2, illustrating how the melt pool is not expected to melt the entirety of the MS diffraction volume, but is expected to melt all the microXAS diffraction volume. Further details are given in previous works by Hocine et al. [43], [44].

The diffracted beam is captured by an in-house-developed ultrafast EIGER 500k detector positioned at a distance of ~80 mm from the sample along the X-ray beam direction ( $\hat{y})$ , at a frame frequency of 20 kHz, and an exposure time of 45 µs [48]. The setup was calibrated with the diffraction signal of quartz powder, yielding the sample-to-detector distance, beam center and detector tilt. This single-photon-counting hybrid detector, with an area of ~8 × 4 cm², contains 500,000 pixels with a pixel size of 75 × 75 µm², and it can store 30,000 recorded patterns in 4-bit mode. During the operando measurements, up to 20,000 2D diffraction patterns were acquired for each printed layer. These 2D patterns were azimuthally integrated and reduced to 1D diffraction patterns via the Bubble software package [49], which is based on pyFAI, a Python library for fast integration [50]. A MATLAB script developed in-house was used to calculate the center of mass of selected Al/Sc/Zr peaks and track their locations and intensities over time; these peak locations were then used to extract the temperature shifts using the respective planes’ coefficients of thermal expansion.

2.4. Microstructure characterization

The top surface of selected samples deposited during beamline experiments were lightly polished to a 0.04 µm finish with a standard fumed-silica suspension from Struers to remove top surface texture and reveal bulk porosity and composition. The samples were then cut perpendicular to the surface and the cross-sections were polished to a 0.02 µm finish with a non-crystallizing colloidal silica suspension. A Leica TIC3X triple ion beam miller was used at 6.0 kV and 2.2 mA, with a flat milling stage angled at 6°. Both top and cross-sectional areas were examined with a FEI Quanta 650 scanning electron microscope (SEM) with secondary electron (SE), backscatter electron (BSE), and energy dispersive X-ray spectroscopy (EDS) detectors, and a JEOL JSM-7900-FLV SEM with SE, high-sensitivity BSE, and EDS detectors. Particle size analysis was performed using ImageJ.

3. Results and Discussion

3.1. Operando reaction of Sc and Zr with Al

High-speed operando diffraction to study the reaction of Zr and Sc was performed at the MS powder beamline featuring a larger diffraction volume during the L-PBF of elemental powder blends with target composition of Al-0.52Sc and Al-0.26Sc-0.26Zr. The larger diffraction volume of ~130 × 230 × 72 µm³ increases the probability to observe a Zr or Sc particle within the blend at a ratio of ~1:130 by volume. Fig. 3 shows the phase and temperature evolution in (a-c) Al-Sc and (d) Al-Sc-Zr, during laser scanning of 8 × 2 mm² blocks. Fig. 3a shows the evolution of diffraction patterns for an Al-Sc sample (power: 375 W, scan speed: 521 mm/s, hatch spacing: 80 µm) from t = 0 to 700 ms, where t = 0 corresponds to the start of printing; however, the laser is far from the diffraction volume, and so t = 0 shows diffraction data collected from the Al-Sc(-Zr) powder blend layer prior to laser interaction. The data are shown as logarithmically color-mapped diffraction intensity as function of time (on the y-axis) and diffraction angle (on the x-axis). Due to a low number density of Sc and Zr powders within the diffraction volume, combined with random crystal orientation, Sc/Zr single peaks are observed only in a fraction of the experiments. Here, the (0002) diffraction of a favorably-oriented Sc particle is observed in the powder bed and persists to 316 ms, where it abruptly disappears. Fig. 3b shows a reduced angle and timescale view of the diffraction data in Fig. 3a. While the X-ray beam, and thus the observation point, is centered and fixed in the long dimension of the 8 × 2 mm² rectangular scan area, the laser is scanning over the full area with a hatch spacing of 80 µm. At the fixed observation location, the laser passes by in close proximity multiple times, leading to thermal expansion of the Al powders in the diffraction volume, observed as a shift towards a smaller diffraction angle. This sharp peak shift is followed by a gradual return to the centerline upon cooling, before the next laser pass causes the expansion/contraction cycle to repeat. Due to the size of the diffraction volume (130 × 230 µm²) compared to the hatch spacing (80 µm), combined with the high thermal conductivity of Al, thermal lattice expansion is observed prior to the laser passing directly through the observed volume. From a processing perspective, this leads to a preheating of the powder bed prior to the melt scan.

After the melting event, the subsequent laser scan vectors re-heat the solidified diffraction volume on each pass until the passes are sufficiently far away. This leads to a complex thermal history within a single solidified layer, with a series of rapid thermal-cycling treatments of diminishing intensity. In these experiments, the diffraction volume (~130 × 230 × 72 µm³) is larger than the melt pool size, and thus solid material from the melt pool edges is always observed in diffraction, consistent with the diffraction pattern never disappearing completely (as would be expected if all the material within the diffraction volume were molten at the same time). The pattern repeat time is defined as the time the laser reaches the end of the scan area, turns around and again reaches the location of the X-ray beam; i.e., when scanning the 8 × 2 mm² area, the laser travels 4 mm to the edge, turns around and travels another 4 mm within ~16 ms to reach the observation location again.

Fig. 3c and d shows the estimated average temperature of the phases within the diffraction volume, calculated from the peak shifts during laser scanning. The (111), (200), and (220) peaks of the face-centered cubic α-Al phase were tracked from before to after the laser melting event, as were the (0002) peak of hexagonal close-packed (h.c.p.) pure Sc observed in an Al-Sc sample and the (11 $\overset{̅}{2}$ 0) peak of h.c.p. pure Zr in an Al-Sc-Zr sample. Based on known thermal lattice expansion of the pure Al (27 × 10⁻⁶ K⁻¹), Sc (15 × 10⁻⁶ K⁻¹), and Zr phases (11 × 10⁻⁶ K⁻¹) [51], [52], the temperature can be calculated from the measured change in lattice parameter during the heating events. Various sources of errors exist. First, the lattice expansion is assumed to be solely due to thermal expansion from heating, not accounting for the effect of residual stresses or compositional changes. If tensile stresses arise, the estimated temperatures are an upper bound and may overestimate the actual temperatures experienced by the samples; if compressive stresses arise, the calculated temperature is underestimated. Second, the conversion from lattice expansion to temperature of the Al peaks was performed assuming a constant coefficient of thermal expansion (CTE) of 26.7 × 10⁻⁶ K⁻¹, which is an average value corresponding to the CTE around 280 °C. In reality, the CTE is temperature-dependent, and this analysis using constant CTE leads to a ~5% overestimation of the temperatures experienced by the melt pool, compared to the analysis performed with variable CTE vs. temperature. However, this simplification was determined not to change the results given in Fig. 3, Fig. 4, Fig. 5. A full comparison of the analyses using constant vs. variable CTE is given in the Supplemental Information (Figs. S1-S4). Third, the diffraction volume extends into colder regions, leading to an averaging of lattice parameter across a temperature gradient within the Al matrix. Temperatures for the Al matrix determined by operando X-ray diffraction are thus a volume average. In contrast, the temperatures determined for single Sc and Zr particles captured in the diffraction volume are only averaged over the particle volume (~30 µm diameter), the only place where pure Zr/Sc exists. These single particles can thus be used as temperature probes with higher spatial resolution compared to the surrounding Al matrix.

In Fig. 3c and d, the Sc(0002) and Zr(11 $\overset{̅}{2}$ 0) peaks become too weak to detect at times t = 316 and 400 ms, respectively. Based on the observed maximum temperatures of 350 and 405 °C, respectively, the Sc and Zr particles tracked here are assumed to have reacted with the Al melt and not have been ejected from the melt pool, in which case no temperature increase would be observed due to the fixed location and size of the X-ray beam. For comparison, an example of an Sc/Zr particle ejected from the melt area prior to melting can be found in the Supplemental Information (Fig. S5). The maximum calculated temperatures from the Sc and Zr peaks in Fig. 3(c,d) are close to the temperature observed in the Al matrix, indicating that the particles react with the Al melt at a temperature (400–650 °C) close to the melting point of Al (662 °C), rather than being directly heated to the melting point of Sc or Zr (1541 and 1855 °C, respectively) by the laser. This is in agreement with prior work, where reaction of solid Sc and Zr particles with molten Al was observed during in situ high-speed imaging experiments of a single laser scanning line [30].

In Fig. 3d, the temperatures in the solidified diffraction volume, calculated from the Al (111), (200), and (220) peaks, differ by up to ~100 °C at 700 ms. The Al(111) direction yields the highest temperature, while the Al(200) direction shows the least lattice expansion and thus lowest calculated temperature. Physically, the crystals’ diffraction should be very close in temperature. The difference between the directions is thus likely caused by internal stresses arising during solidification and cooling. Based on the diffraction geometry of a 15° tilt of the miniSLM chamber and the diffraction angle of ~28°, the observed (200) direction is closest to the surface normal (30°) of the specimen, in comparison to the (111) and (220) directions with diffraction angles of ~24° and ~40°, respectively. As such, the observed (200) planes are least affected by the large horizontal tensile stresses that typically arise during L-PBF [53]. Thus, the Al(200) direction provides the most consistent temperature estimation across different experiments.

Fig. 4 shows the evolution of the elemental Sc (a-b) and Zr (c) peak intensities in counts per pixel decreasing over six timesteps of 50 µs intervals (300 µs total) as the laser interacts with the diffraction volume containing elemental Sc/Zr particles. Fig. 4(a-b) and 4c correspond to the experiments described in Figs. 3c and 3d, respectively; Fig. 4b likely captures a different grain within the same Sc particle as in Fig. 4b, as the timing of the reaction is identical in both. This time scale lines up with previously observed interactions between Sc/Zr elemental particles with molten Al droplets [30].

3.2. Influence of scan area size on thermal history

High-speed operando X-ray diffraction to study the influence of the scan area size on the temperature history of the alloys is performed at the microXAS beamline on the same Al-Sc and Al-Sc-Zr elemental powder blends with a diffraction volume of ~80 × 105 × 42 µm. Fig. 5 shows four representative temperature evolution curves from the 1 × 1 (yellow), 2 × 2 (green), and 4 × 4 (teal) mm² samples of an Al-Sc powder layer processed with laser parameters of 375 W, 521 mm/s, 80 µm hatch spacing, and 40 µm layer thickness, which corresponds to a volumetric energy density of 225 J/mm³. Additionally, the data from the MS powder beamline featuring an 8 × 2 (blue) mm² scan area are shown for comparison. Depending on the layer number, the 8 × 2 mm² field was scanned along its short or long direction, yielding additional information for scan vector lengths of 2 and 8 mm. The Rosenthal equation [54] - an analytical solution for the three-dimensional heat distribution for a moving heat source - was used as an approximation to fit the shape of the thermal profiles:(1a) $T (x, R) = T_{0} + \frac{Q}{2 π R k_{T}} * \exp (- \frac{v}{2 α} (R + x))$ $where R = \sqrt{x^{2} + y^{2} + z^{2}} and$ where T₀ is the original temperature of the powder bed upon laser scanning, k_T is the thermal conductivity, $α = \frac{k}{c_{p} ρ}$ is the thermal diffusivity (where k is the thermal conductivity in W/mK, c_p is the specific heat capacity in J/(kg*K), and ρ is the density in kg/m³), v is the laser scan speed, and Q is the absorbed power.

The Rosenthal equation can be simplified to:(1b) $T (x, R) = T_{0} + \frac{Q}{2 π k_{T}} * \frac{1}{- x}$ by choosing R, the location of interest, to be -x, which is the farthest point on the surface of the trailing edge of the melt pool. The spatial coordinate x can then be related to time with $x_{rel} = x - x_{0} - v * t = \overset{̅}{x} - v * t$ , where x is the real x-coordinate in space, x₀ is the location of the laser at t₀, and x_rel describes the constant x-coordinate relative to the laser through time t. An x-coordinate of 150 µm was selected as an approximation for the tail end of the surface melt pool. The Rosenthal equation can then be expressed in the form:(1c) $T (t) = \frac{a}{(t - c)} + b,$ where a, b, and c are constants. Fitted thermal profiles based on the Rosenthal equation are shown overlaid in black in Fig. 5.

The size of the scanned field (i.e., the length of the scan vector) affects the preheating temperature before melting, the duration of the preheating, the return temperature after melting until the next laser pass starts, and the time between individual laser passes. With increasing field area, the preheating time is increased, as it takes more time for the laser to travel the longer distance. As heat flow is limited by thermal conductivity, a smaller scanned field experiences a higher preheating temperature as the laser returns within a shorter period of time, adding more energy into the material. With a higher baseline temperature achieved by preheating, the temperature after the melting scan (defined here as the scan reaching the highest observed temperature in the crystalline Al matrix surrounding the melt pool) is also increased with smaller scan sizes. The combination of these effects can be considered as a base plate “preheating” effect, which is dependent on scan area size. Additionally, the scan repeat time between consecutive heating/cooling cycles is marked in Fig. 5 for all four curves. The high temporal resolution of the X-ray diffraction experiment allows to determine a 0.4–0.6 ms delay in beam optics when turning the laser beam around, which matches well with a calculated settling time of 0.63 ms from previous experiments [55]; this is the difference between the calculated scan repeat times (1.9, 3.8, 7.7, and 15.4 ms, based on the scan speed of 521 mm/s) and the measured repeat times (2.3, 4.4, 8.2, and 16.1 ms).

Fig. 6(a-d) show (a) an example temperature profile of Al-0.52Sc processed at 375 W and 417 mm/s, and (b-d) three parameters, extracted and averaged over all operando experiments, as a function of scan vector length and alloy type, namely: (b) the return temperature between the melt scan and the subsequent scan, (c) the initial cooling rate in the solid Al after the melt scan, and (d) the time spent in the intrinsic heat treatment range (300–650 °C) after the melting event. The three square field samples (1 ×1, 2 ×2, and 4 ×4 mm²) were measured at the microXAS beamline. The 8 × 2 mm² samples were measured at the MS beamline: alternating layers (in the long and short directions) were used to collect data for the 8- and 2-mm scan vectors respectively, allowing comparison with the square field data. The return temperature and initial cooling rate are calculated from only a single curve per layer, which experienced the highest temperature and steepest initial cooling rate, defined as the “melt scan”; by contrast, the time spent in the intrinsic heat treatment range is a sum of all times spent between 300 and 650 °C after the full melting curve. The return temperature is estimated by fitting the selected curve to the form of the Rosenthal equation (Eq. 1(c)), where b is the y-asymptote as time approaches infinity. The return temperature is then defined as the last temperature prior to the temperature increase of the subsequent scan (Fig. 6a). The initial cooling rate is estimated by fitting the highest-temperature data with a linear approximation, which is validated by the analysis performed on similar data with Ti-6Al-4 V on the same experimental setup [55]. The time spent in the intrinsic heat treatment range is calculated using the linear fit between 300 and 650 °C.

For the scan sizes studied here, the observed return temperature decreases with increasing scan vector length (Fig. 6b), indicating that the larger samples reach a lower temperature before the subsequent laser scan, as expected. The average temperatures in a 1 × 1 mm² field reach ~200 °C, but they drop to ~100 °C in scans which are 4 mm and longer.

The samples also show an increase in cooling rate with the increasing scan vector size (Fig. 6c); the 1 × 1 mm² sample experienced the lowest cooling rate of 3–5 × 10⁵ K/s, compared to 5–6 × 10⁵ K/s for the 2 × 2 mm² sample, and 6–7 × 10⁵ K/s for the 4 × 4 mm² and 8 × 2 mm² samples. With an increased scan vector length, the lower temperature within the surrounding area leads to a larger temperature gradient, as more time passes between consecutive laser scans and thus more heat is removed into the baseplate by thermal conduction. This difference in thermal gradient and solidification rates is expected to affect the resulting microstructure: changing solidification speed in the melt pool leads to the nucleation of more L1₂-Al₃(Sc,Zr) precipitates, which in turn nucleate smaller, equiaxed α-Al grains. Conversely, a constant solidification speed traps Sc/Zr solute in the melt and nucleates fewer L1₂-Al₃(Sc,Zr) precipitates, leading to fewer, more elongated grains. These results are further discussed in Section 2.3.

The time spent by the samples in the intrinsic heat-treatment region can be estimated using the linear fits up to 650 °C, the temperature at which the material is expected to solidify, and down to 300 °C, the temperature below which Sc and Zr diffusion in Al becomes slow. In this temperature range, precipitation of secondary phases is possible. The approximate times spent within this intrinsic heat treatment regime for each laser pass are shown in Fig. 6d. The recently solidified material in the 1 × 1 and 2 × 2 mm² samples spend the longest time (1.0–1.3 ms) above 300 °C, compared to 0.7–0.9 ms for the 4 × 4 and 8 × 2 mm² samples. Although 1 ms is far too short to precipitate any nanoscale secondary phases in a single laser pass, the cumulative effects of this varying intrinsic heat treatment could become significant in a larger, multilayer build with different feature sizes. Layer-wise AM reheats the underlying material, so in a full build, the material experiences numerous such intrinsic heat treatment cycles. If sufficient time and temperature is provided, precipitation of secondary L1₂ or other phases may occur by the end of the build, depending on the precipitation kinetics of the alloy.

In summary, the observed return temperature, cooling rate, and intrinsic heat treatment time all approach a constant value for scan vector lengths greater than 4 mm. Any island-scan strategy using shorter scan vectors, or any feature with a smaller cross-section, will experience a higher cooling rate and return temperature and spend more time in the intrinsic heat treatment regime.

3.3. Precipitation of primary L1₂-Al₃(Sc,Zr) on solidification

In addition to quantifying the solidification and cooling behavior in single scan fields within multilayer builds of Al-Sc(-Zr), reactions between elemental Al, Sc, and Zr powder particles were studied. Scandium and zirconium are expected to exothermically react with, and dissolve in, molten aluminum [30], nucleating randomly-oriented submicron L1₂-Al₃(Sc,Zr) precipitates in the melt pool upon cooling, which then nucleate α-Al matrix grains due to the similar lattice constants (0.410 nm for Al₃Sc, 0.408 nm for Al₃Zr, and 0.405 nm for α-Al) [56], [57]. Operando X-ray diffraction experiments captured the disappearance of Sc and Zr particles during L-PBF, as shown in Fig. 3, and also captured the appearance of peaks corresponding to cubic L1₂-Al₃(Sc,Zr) precipitates, as shown in Fig. 7a. The latter figure shows the evolution of the Al(111) and (200) peaks through laser melting in an Al-0.52Sc sample measured at the microXAS beamline, with a new peak corresponding to the L1₂-Al₃Sc (210) appearing after the first full melting event (as indicated by the characteristic leftward shift and reduction in peak intensity of Al(111) and (200) peaks) at 139 ms. Although the Al(111) peak disappears between 140 and 170 ms, a (200) peak located around 30.8 Å is still observed in this time interval. This peak likely corresponds to the L1₂(200) peak belonging to Al₃(Sc,Zr) precipitates which form rapidly in the melt, which is supported by the fact that the L1₂(200) peak at 30.8 Å and L1₂(210) peak at 34.2 Å appear at the same time (t = 140 ms). As the L1₂-Al₃(Sc,Zr) precipitates have the same crystal structure (f.c.c.) as the α-Al matrix, the L1₂(200) peak overlaps the Al(200) peak and is generally indistinguishable, except if, as in this case, the α-Al matrix is in the liquid phase while the L1₂-Al₃(Sc,Zr) precipitates are solidified. Additionally, as the L1₂-Al₃(Sc,Zr) phase has a slightly larger lattice parameter (0.408–0.410 nm) compared to the α-Al matrix (0.405 nm), at room temperature the L1₂(200) peak is observed slightly shifted to the left of the Al(200) peak, as expected. Additional data from operando L-PBF experiments capturing the simultaneous disappearance of peaks corresponding to h.c.p. Sc/Zr particles and appearance of peaks corresponding to f.c.c. L1₂-Al₃(Sc,Zr) precipitates are given in the Supplemental Information (Fig. S6).

Fig. 7(b,c) show cross-sectional microstructures of the (b) Al-0.52Sc and (c) Al-0.26Sc-0.26Zr alloys after five layers of L-PBF, featuring the melt pool morphology and L1₂ precipitate size and distribution. The top surface of the samples were lightly polished for prior top-down imaging, so Fig. 6(b,c) depict the lower layers. Nanoscale cubic L1₂ precipitates are observed at the base of the melt pool roughly 20–40 µm below the polished top surface of the samples. The Al₃Sc and Al₃(Sc,Zr) primary precipitates have an average diameter of 120–135 nm (n = 335) and 112–125 nm (n = 692) respectively. Only one solidified melt pool is observed, likely for two reasons: (i) the depth of the melt pool during laser melting is greater than 150 µm, suggesting that all five 30-µm layers are remelted even during the fifth laser pass; and (ii) the top of the melt pool was removed via polishing. Below the melt pool is the original microstructure of the 99.999% Al base plate, featuring large (hundreds of microns), elongated grains.

Fig. 7(d-f) show cross-sectional microstructures of the (d) 1 × 1 mm², (e) 2 × 2 mm², and (f) 4 × 4 mm² samples which were built operando in the microXAS beamline, illustrating the grain size and shape in each sample, as well as submicron L1₂-Al₃Sc precipitates present at the bottom of the melt pools. The average grain sizes (long axis) of the 1 × 1, 2 × 2, and 4 × 4 mm² samples respectively are 10.1 ± 5.1 µm (n = 55), 4.7 ± 2.4 µm (n = 161), and 1.9 ± 0.6 µm (n = 62). As previously mentioned, this trend of increasing grain size with decreasing sample size is expected based on the increasing cooling rates (300–500, 500–600, and 600–700 K/ms for the 1 × 1, 2 × 2, and 4 × 4 mm², respectively), shown in Fig. 6b. Assuming that each grain is nucleated by one L1₂-Al₃Sc precipitate (which may or may not be visible in the cross-section), the rapidly changing solidification and subsequent cooling rates observed in the larger samples (4 × 4 and 8 × 2 mm²) generate more L1₂ precipitates in the melt pool, leading to a higher number of smaller, equiaxed, randomly oriented α-Al matrix grains. This is beneficial for strength, but may be detrimental for creep resistance, due to diffusional creep. Conversely, the larger grains in the 1 × 1 mm² sample are probably nucleated by larger primary L1₂-Al₃Sc precipitates. The cooling rate trends in Fig. 6 and comparable cooling rates between the 4 × 4 and 8 × 2 mm² samples indicate that the microstructure and average grain size of the 8 × 2 mm² are likely similar to those seen in the 4 × 4 mm² sample.

This work suggests that scan areas greater than 4 × 4 mm² display comparable solidification and cooling rates, heating and cooling cycles, and intrinsic heat treatments, all of which stem from sufficient time for the sample to cool between laser passes, leading to similar microstructures. This has important design consequences for parts with small feature sizes: improvements in feature resolution in L-PBF have achieved microfeatures as small as 60 µm [58], well below the studied sample area of 1 × 1 mm² in this work. Designers must be aware of the microstructural differences of these small feature sizes, due to the thermal conductivity of the material, baseplate preheating effects or return temperature between scans, and intrinsic heat treatment which can accumulate throughout the build. Additionally, although aluminum alloys were the focus of this study, pure Al has a much higher thermal conductivity (270 W/mK) [59] compared to other popular alloys for L-PBF, such as AlSi10Mg (115–130 W/mK) [60], 316 stainless steel (16 W/mK), Inconel 625 and 718 (10 and 11 W/mK, respectively), and Ti-6Al-4V (7 W/mK). These alloys are thus likely to exhibit large differences in cooling rates, show greater microstructural differences between small and large feature sizes, and exhibit a larger feature-size “threshold” beyond which uniform microstructures can be assumed (taking 4 × 4 mm² as the example threshold feature size in this study). This threshold feature size and the microstructure differences for features below that size must be determined for each alloy individually as part of the alloy and part design process.

4. Conclusions

Operando L-PBF of elemental powder blends with Al-0.52Sc and Al-0.26Sc-0.26Zr (at%) compositions was performed on a custom miniSLM machine at the Swiss Light Source (SLS), leading to the following observations:

•
High-speed synchrotron X-ray diffraction reveals that, upon laser melting, an elemental blend of Sc, Zr, and Al powders reacts to create L1₂-Al₃(Sc,Zr) precipitates. Reaction occurs when the Sc and Zr particles reach ~400–650 °C (well below their melting points), indicating that solid Sc/Zr reacts with molten Al, likely via dissolution/precipitation. This reaction takes approximately 300 µs, as captured by the diffraction patterns of the elemental Sc/Zr peaks diminishing in intensity over six 50-µs timesteps.
•
Return temperatures reached between subsequent laser passes are lower in the largest (4 ×4 and 8 ×2 mm²) samples and higher in the smallest samples (1 × 1 and 2 ×2 mm²), due to the longer time available for the sample to cool while the laser completes its pass. Correspondingly, initial cooling rates after solidification are slowest in the smaller samples (3–5 × 10⁵ K/s) and fastest in the larger samples (7–8 × 10⁵ K/s), indicating a larger thermal gradient between the melt pool and surrounding material. As a result, the larger samples experience the shortest intrinsic heat treatment (defined as the time spent between 300 and 650 °C - 0.7–0.9 ms per laser pass), since the initial cooling rates are the fastest, whereas the smaller samples experience almost double that time (1.2–1.3 ms) in the intrinsic heat treatment range.
•
As-solidified alloys exhibit 100–130 nm primary L1₂-Al₃(Sc,Zr) precipitates at the base of the melt pool with elongated columnar Al matrix grains growing in the direction of the solidification front towards the sample surface.
•
The long axis of the Al grains decreases from 10 ± 5 µm for the 1 × 1 mm² sample to 5 ± 2 µm for the 2 × 2 mm² and 2 ± 0.6 µm for the 4 × 4 mm² samples, consistent with the decreasing trend in cooling rate. A slower cooling rate leads to larger, more elongated Al grains growing in the direction of the solidification front, whereas a faster cooling rate results in smaller, more equiaxed grains.

This work shows that elemental blends can be successfully used to create Al-Sc(-Zr) alloys with L1₂-Al₃(Sc,Zr) primary precipitates acting as Al-grain refiners, even at a very low ratio of Sc/Al and Zr/Al particles (~1:130). Operando X-ray diffraction showing the evolution of the Al, Sc, and Zr particles indicates that the reaction between Al and the Sc/Zr particles occurs at temperatures near the melting point of Al (~650 °C), so that melting of the Sc/Zr particles (at 1541 and 1855 °C) is not necessary, consistent with the exothermic nature of the reaction.

The feature size has a major influence on the part’s local thermal history. As the 4 × 4 and 8 × 2 mm² samples exhibit comparable return temperatures, initial cooling rates, and intrinsic heat treatment times, it can be assumed that the 8 × 2 mm² has a comparable microstructure with respect to primary precipitate size and number density, and grain size. From this, 4 × 4 mm² is taken as the feature threshold size above which microstructure differences are negligible.

The difference in return temperature, initial solidification and cooling rate, intrinsic heat treatment, and resulting microstructure must all be considered when designing parts with small feature sizes. Features below a certain threshold size - which must be determined for each alloy individually, depending on materials properties such as the thermal conductivity - will result in different primary precipitate sizes and number densities, grain sizes, and potentially secondary precipitation effects due to the cumulative intrinsic heat treatment during layer-wise building. These effects can be mitigated by keeping features above this threshold size or by changing the laser parameters to account for different cooling rates and preheating effects.

CRediT authorship contribution statement

Jennifer A. Glerum: Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing, Samy Hocine: Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – review & editing, Cynthia Sin Ting Chang: Data curation, Investigation, Methodology, Christoph Kenel: Data curation, Formal analysis, Investigation, Methodology, Writing – review & editing, Steven Van Petegem: Data curation, Investigation, Methodology, Writing – review & editing, Nicola Casati: Data curation, Investigation, Methodology, Writing – review & editing, Dario Ferreira Sanchez: Data curation, Investigation, Methodology, Helena Van Swygenhoven: Methodology, Investigation, Data curation, David C. Dunand: Conceptualization, Funding acquisition, Supervision, Writing – review & editing.

Declaration of Competing Interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: DCD discloses financial interests relative to Braidy Industries, which could potentially benefit from the outcomes of this research but did not influence its conduct, description, or interpretation.

Acknowledgments

This research received funding from the DEVCOM Army Research Laboratory (award W911NF-19-2-0092). JAG was supported by the Army Research Laboratory (ARL) Oak Ridge Associated Universities (ORAU) via a Journeyman Fellowship grant, and she thanks Dr. Jon-Erik Mogonye (ARL) for numerous useful discussions. JAG also acknowledges the support of a ThinkSwiss Research Scholarship, provided by the Swiss State Secretariat for Education, Research and Innovation (SERI) managed by the Office of Science, Technology, and Higher Education of Switzerland, allowing travel to Switzerland for research purposes. The authors acknowledge the Paul Scherrer Institut (Villigen, Switzerland) for provision of synchrotron radiation beamtime at beamlines MS and MicroXAS of the SLS. This work made use of the EPIC facility of Northwestern University’s NUANCE Center, which has received support from the Soft and Hybrid Nanotechnology Experimental (SHyNE) Resource (NSF ECCS-1542205); the MRSEC program (NSF DMR-1720139) at the Materials Research Center; the International Institute for Nanotechnology (IIN); the Keck Foundation; and the State of Illinois, through the IIN. This work also made use of the Materials Characterization and Imaging Facility which receives support from the MRSEC Program (NSF DMR-1720139) of the Materials Research Center at Northwestern University. This work was further supported by (1) the PREcision Additive Manufacturing of Precious metals Alloys (PREAMPA) project, funded by the ETH board and the Swiss watch and precious metals industry; (2) the Additive Manufacturing and Metallic Microstructures (AM3) project, funded by the Competence Center for Materials Science and Technology (CCMX) and the Swiss watch and precious metals industry.

Appendix A. Supplementary material

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Supplementary material

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Cited by (28)

Monitoring of laser-induced fast recrystallization in SS-316L through synchrotron X-ray diffraction
2024, Materials and Design
Laser based heat treatments have multiple applications for local tuning of microstructures. They are particularly relevant in the context of laser-based additive manufacturing (LAM), in order to relieve residual stresses or introduce equiaxed structures through recrystallization. In 316L, high stored energy inherited from the high cooling rates of laser processing creates strong crystallographic textures and stable cellular walls, which challenges the possibility of inducing fast recrystallization. In a first step, we perform here a laser heat treatment on a highly deformed 316L steel, and show that in-situ X-ray Diffraction (XRD) is a viable tool for the monitoring of fast recrystallization. The evolution of Bragg peak width over time is connected to the evolution of dislocation density and grain size, thanks to Electron Back-Scattered Diffraction (EBSD) and Transmission Electron Microscopy (TEM) characterization. X-ray signals are shown to reveal different stages of recrystallization, in particular the development of dislocation cells and the onset of nucleation. This study also demonstrates how local heat sources such as lasers may help designing composite-like materials for grain size, texture and hardness optimization.
Modeling and measurements of creep deformation in laser-melted Al-Ti-Zr alloys with bimodal grain size
2024, Acta Materialia
Elemental powders of Al, Ti, Sc, and Zr are blended to create binary Al-0.5Ti and Al-0.25Ti-0.25Zr (at%) alloys via laser powder-bed fusion (L-PBF), with Al-1Ti and Al-0.25Sc-0.25Zr alloys produced for comparison. The Al-Ti alloys formed primary D0₂₃-Al₃Ti precipitates upon solidification, whereas the Al-(Sc/Ti)-Zr alloys formed primary L1₂-Al₃(Sc,Ti,Zr) precipitates which nucleated bands of fine grains. Upon aging, the Al-Ti alloys do not harden (consistent with most Ti remaining in solid solution), unlike the Al-(Sc,Ti)-Zr alloys, as expected from precipitation of secondary L1₂-Al₃(Sc,Ti,Zr) nanoprecipitates. Upon compressive creep testing at 300–400 °C, Al-0.25Ti-0.25Zr exhibits steady-state strain rates comparable to those of Al-0.5Zr at low stresses (up to ∼14 MPa), but about an order of magnitude faster at higher stresses. The effects of bands of fine grains (formed by L1₂-Al₃(Sc,Ti,Zr) primary precipitates at the bottom of the melt pools) on hardness and creep resistance is investigated via finite element modeling of simple slab models, with varying geometries approximating experimental melt pool geometries. The degree of connectivity of coarse- and fine-grain regions is a greater factor in the resulting creep strain rates than the volume fraction or spatial orientations of these two regions. This suggests that reducing the concentration of Zr (in Al-0.5Zr), or partially substituting with a less expensive element such as Ti (as for Al-0.25Ti-0.25Zr), may maintain the added l-PBF processability benefits of Zr and reduce the volume fraction of fine grains without sacrificing creep resistance, allowing for further tailoring of custom microstructures.
In-situ experimental and high-fidelity modeling tools to advance understanding of metal additive manufacturing
2023, International Journal of Machine Tools and Manufacture
Metal additive manufacturing has seen extensive research and rapidly growing applications for its high precision, efficiency, flexibility, etc. However, the appealing advantages are still far from being fully exploited, and the bottleneck problems essentially originate from the incomplete understanding of the complex physical mechanisms spanning from the manufacturing processes, microstructure evolutions, to mechanical properties. Specifically, for powder-fusion-based additive manufacturing such as laser powder bed fusion, the manufacturing process involves powder dynamics, heat transfer, phase transitions (melting, solidification, evaporation, and condensation), fluid flow (gas, vapor, and molten metal liquid), and their interactions. These interactions induce not only various defects but also complex thermal-mechanical-compositional conditions. These transient conditions lead to highly non-equilibrium microstructure evolutions, and the resultant microstructures, together with those defects, can significantly alter the mechanical properties of the as-built parts, including strength, ductility and residual stress. We believe that the most efficient approach to advance the fundamental understanding is integrating in-situ experimentation and high-fidelity modeling. In this review, we summarize the state of the art of these two powerful tools: in-situ synchrotron experimentation and high-fidelity modeling, and provide an outlook for potential research directions.
Investigation of microstructural evolution and mechanical properties Al<inf>13</inf>Fe<inf>4</inf> produced by casting and spark-plasma sintering
2023, Vacuum
In this paper, the preparation and evolution of the polycrystalline Al₁₃Fe₄ microstructure were investigated during the casting and spark plasma sintering process (SPS). Experimental results showed that an increase in the cooling rate (90–100 °C/min) for both methods of synthesis led to the formation of cracks and chips in the bulk of the material. Cracks during casting are formed by the passage of a peritectic reaction. The high cooling rate does not allow contact melting products to fill the pores that coalesce into cracks. With SPS, the main driving force for the formation of cracks is the effect of the thermal expansion coefficient. The analysis of XRD and results of mechanical testing revealed the maximum tensile micro stresses (425–430 MPa) in samples obtained at a high cooling rate. A decrease in cooling rate promotes the formation of high-density polycrystalline Al₁₃Fe₄. It is noted that the material prepared by SPS has a fine-grained structure by using Al₁₃Fe₄ powder as the initial material. The highest indicators of flexural strength are 60 ± 10 MPa, Vickers hardness HV = 8.2 ± 0.8 GPa, fracture toughness K_1c = 1.5 ± 0.1MPa × m^−0.5, modulus of elasticity 180 ± 10 GPa. The fractography of the surfaces after the flexural test has common features of a quasi-brittle trans crystalline fracture with a “river” structure.
Enhanced strength-ductility synergy in pure Al by assembling grain and chemical gradients
2023, Materials Characterization
Titanium (Ti) is generally known for its limited solid solubility and used as grain refiner in Al-based alloys, accelerating heterogeneous α-Al nucleation during solidification. In this study, a newly developed surface modification of pure Al followed by sputtering Ti film (∼1 μm) and subsequent laser remelting has been proposed. Gradient structural features in both grain size and chemical composition have been accomplished in the top surface layer (<10 μm), showing three typical domains with different grain morphology and Al₃Ti nanoprecipitates. The simultaneous increase in strength and ductility is attributed to the strong dislocation-precipitate interaction inside gradient nano-grained top-surface layer, which has been confirmed by the partially dissolved Al₃Ti nanoprecipitates induced by deformation. The findings in this work provide a new routine for upgrading mechanical properties through the manipulation of both grain- and chemical-gradients.
Direct ageing of LPBF Al-1Fe-1Zr for high conductivity and mechanical performance
2023, Acta Materialia
The novel Al-1Fe-1Zr alloy leverages the non-equilibrium solidification conditions characteristic of the laser powder bed fusion (LPBF) process, namely a high thermal gradient (G) and solidification front velocity (R). The multiscale characterization of its microstructure in as-built and peak-aged conditions by SEM, TEM with EDS and automated crystal orientation mapping (ACOM), brings new insights on alloy design for LPBF. The solidification conditions permit the solute supersaturation of Fe and Zr, with the latter precipitating as L1₂-Al₃Zr nanoparticles following ageing, bringing a high strengthening contribution. In conventional Al alloy ingots, Fe tends to create coarse particles which are detrimental to ductility. Here the Fe particles show a fine globular morphology in the as-built condition, and fine faceted Fe-rich intermetallics are obtained upon ageing. Nanoindentation and in situ tensile tests in the SEM coupled with microscale strain measurements shed light on the relation between microstructural and strain heterogeneities in the as-built condition. Our characterization results for this new Al-1Fe-1Zr grade are synthesized into a simple model for its solidification upon LPBF. In particular, the origin of melt pool boundaries is revealed. These are associated with Fe depletion caused by an early planar growth front, and the evolution of these zones upon ageing is presented. With a high potential for industrial applications, the novel alloy with the two elements Zr and Fe exhibiting low solubility at equilibrium and diffusivity in the Al matrix permit to achieve high conductivity (27 MS/m) and yield strength (330MPa) after a simple direct ageing step at 400°C/4h.

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¹: Currently: Department of Mechanical Engineering, University College London, London, England.

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Outline

Cited by (28)

Figures (7)

Tables (2)

Extras (1)

Additive Manufacturing

Abstract

Keywords

1. Introduction

2. Materials and methods