Effects of process parameters and geometry on dimensional accuracy and surface quality of thin strut heart valve frames manufactured by laser powder bed fusion

Laser powder bed fusion (LPBF) is one of the most popular metal additive manufacturing technologies. LPBF applies a high-energy laser to melt particles in a thin powder layer to produce three-dimensional parts. Compared to conventional subtractive manufacturing methods, LPBF can produce metallic parts with extremely high structural complexity. Currently, a wide range of metal materials can be processed by LPBF including stainless steel, titanium, titanium alloys, nitinol, aluminium, aluminium alloys and metal matrix composites [1‐3]. LPBF parts typically have high density and fine microstructures, leading to excellent mechanical properties which could be equivalent to that of wrought parts [4]. Thus, LPBF has found its applications in high-value sectors such as aerospace [5, 6] and biomedical devices [7‐9].

Although LPBF has many advantages over the conventional manufacturing methods, there are several major drawbacks, such as large surface roughness [10] and low dimensional accuracy [11], which reduce its popularity in wider applications, especially fabrication of fine-sized products (structure features under 1 mm). Most of the current literature relating to surface roughness are based on large bulk parts. It was reported that the surface finish is directly affected by process parameters, such as laser energy density, building orientation and layer thickness [12]. Khorasani et al. [13] studied the effects of laser power, scan speed, hatch space, scan pattern angle and heat treatment temperature on the top surface roughness of LPBF Ti-6Al-4 V parts via an experiment using the Taguchi method. The results showed that ranking of the most to the least effective parameters was obtained as heat treatment > hatch space > scan speed > laser power > scan pattern angle. Meanwhile, the authors suggested that a combination of higher laser power and lower scan speed produces higher temperatures to reduce the surface tension of melt pool, an effect which could improve the surface quality. Guo et al. [14] investigated the effects of laser power, scan speed and hatch space on surface roughness of as-built IN738LC parts via LPBF. The top surface roughness was obtained between Ra 11 and Ra 28 μm. A minimum surface roughness was obtained with a specific combination of process parameters. The surface became rougher with higher energy density combinations as more mass was transferred to the previously fabricated tracks due to more vigorous Marangoni flow. The surface roughness increased significantly with low energy density combinations since increasing numbers of open pores were formed as well as the presence of many un-melted particles. Snyder and Thole [15] explored the influence of hatch space and contour scan on the roughness of both the up-skin and down-skin surfaces. The results showed the roughness of down-skin surface had higher magnitudes than the up-skin surface (up to 25 μm). They believed that the roughness of up-skin surfaces was tied to the overall size of the melt pool, while the down-skin surfaces were more sensitive to the melt pool depth. Fox et al. [16] reported the roughness of down-skin surfaces increased greatly with smaller overhanging angles. Calignano [17] found downward faces could be successfully built without supports at an angle up to 30° (between surface and horizontal plane) but with a much higher surface roughness and structure deformation.

Dimensional accuracy is another critical issue to consider in the LPBF of fine-sized parts. Tomas et al. [18] investigated the dimensional accuracy of thin-wall, circular H13 tool steel parts (1 mm thickness, diameters of 25–85 mm) with stripe and sectional scan strategies. All the parts were oversized with a dimensional error ranging from 0.1 to 0.5 mm compared to the nominal diameters. Meanwhile, the dimensional error increased along the building height from the base plate. Ahmed et al. [19] fabricated thin-walled AlSi10Mg parts with a thickness from 0.5 to 5 mm. They found both the dimensional error and sample distortion increased with decreasing wall thickness. The sample with design thickness of 0.5 mm had a 2.4% error for actual thickness and 158.62% distortion rate. Charles et al. [20] studied the dimensional error in 45° down-facing surfaces with different process parameters. The study indicated laser power was the most significant factor, followed by layer thickness, scan speed and then the interaction effect of laser power and scan speed. The dimensional error was between 4 and 30%. Wu et al. [21] explored the fabrication limits of thin-wall structures from Ti-6Al-4 V, AlSi10Mg and Inconel 718. The target thickness was set as between 0.1 and 0.5 mm, with inclined angles of 30°, 45° and 60°. The results showed the minimum thicknesses for Ti-6Al-4 V, AlSi10Mg and Inconel 718 were 99 μm, 101 μm and 107 μm, respectively. The maximum inclined angle of 60° can be achieved with specific process parameters.

Generally, for small dimensions which can only be achieved by single-bead mode, the wall thickness is controlled by the melt pool size instead of the CAD design. For larger sizes, achievable by both single-bead mode and raster mode, the final dimensional accuracy is related to the compensation setting of scan strategy and inclined angle as well as the material used.

Since recent research [22, 23] has reported that thin stent structures can be successfully fabricated via LPBF, it raises new opportunities in the fabrication of heart valve frames, which have similar thin strut structures. Transcatheter aortic valve implantation (TAVI) devices—designed for the minimally invasive treatment of a failing aortic valve—typically comprise a stent-like frame and a bioprosthetic valve. The device is commonly delivered into the degenerated valve through femoral access, and then deployed via balloon expansion or self-expansion [24]. State of the art TAVI frames are fabricated by laser cutting from metallic tubes. Figure 1 depicts the balloon-expandable SAPIEN 3 (S3) valve from Edwards Lifesciences. The S3 frame has a 4-layer structure and 12 cells with thin cobalt-chromium struts, approximately 0.3 mm thickness. The inclined struts have an angle of approximately 55° with the vertical direction. The structure provides enough radial strength to push aside the native valve leaflets and can be easily crimped and expanded. The key features of the heart valve frame such as strut thickness and inclined angles are close to the fabrication limits of LPBF, suggesting that improvements are needed in LPBF and/or the geometry of the frame needs to be modified to achieve acceptable quality. However, Melancon et al. [25] reported there are 49% and 41% mismatches between original CAD design and LPBF porous biomaterials for compressive elastic modulus and yield strength due to the large dimensional errors. The capability of LPBF to produce thin strut structure must be fully understood as the baseline in the novel design for heart valve via LPBF.

Recently, we demonstrated that a valve frame manufactured by LPBF could be successfully crimped and expanded [26]. Encouraged by these results, a detailed analysis was conducted on several test models based on the S3 frame. Measurements were made to assess (i) the effect of strut angles and process parameters on the manufacturing quality of these thin strut structures, (ii) the dimensional accuracy and surface morphology of the frames and (iii) the geometric accuracy of a complete S3 style frame using a high-resolution computer tomography (CT) scan.

Due to the layer-by-layer manufacturing fashion of LPBF, the dimensional accuracy and surface quality of as-built parts are significantly affected by the characteristics of a single melt track and the scan strategy to stack the melt tracks. Since the frame struts are relatively thin, it is difficult to prepare metallurgical samples to observe the cross-section of the struts. Mathematical methods have been used to explore and understand the fundamental behavior of the single melt track in LPBF. The Rosenthal model was first developed in 1941 to evaluate the thermal field during arc welding [27]. Due to the similarities of thermal history between arc welding and LPBF, the Rosenthal model can be used to predict the thermal characteristic in LPBF. There are several assumptions to the model in the simulation of powder-bed simulation [28]: (1) the thermophysical properties are temperature independent. The latent heat due to phase change is neglected. (2) The scanning speed and power input are constant. (3) The heat source is a point source. (4) The heat transfer is only governed by conduction. Convection and radiation are not considered. (5) The deposition of powder has no significant influence on melt pool size. The Rosenthal equation can be expressed as follows: where T₀ is the temperature at locations far from the top surface, ε is the absorptivity of the material, P is the laser power, κ is the thermal conductivity, r is the distant from the heat source, and α is the thermal diffusivity. The laser moves along the x-axis, in which the moving coordinate of x-Vt is replaced by ξ. Recently, it has been reported to successfully predict the thermal field, melt track geometry and microstructure fabricated with LPBF [28‐30]. In this study, a MATLAB program was used to calculate the thermal field of a single melt track based on the Rosenthal model. Table 6 lists the material properties used in the calculation.

Figure 12a depicts the temperature contour and melt track boundary of a single melt track using 113 W and 700 mm/s, obtained using the MATLAB calculation from The MathWorks, Inc. (USA). The width of the melt track is 131.4 μm, while the depth is 65.7 μm. As shown in Fig. 12b, the width and depth of the melt track increase linearly with the increase of laser power. The width and depth of the melt track vary, respectively, between 125.3 and 137.2 μm, and 62.6 and 68.6 μm. With respect to variation of the scan speed between 600 and 800 mm/s (Fig. 12c), the width of the melt track decreases linearly from 141.7 to 123 μm whilst the depth decreases from 70.8 to 61.5 μm.

Figure 13a and b schematically illustrate the border scan strategy for vertical struts and inclined struts. The cross-sections of struts are simplified as square and rectangle shapes due to the large ratio between the strut width and radius of strut curvature. As shown in the top view, the dash lines represent the border of the struts. The vertical struts have a square shape since the width and thickness of struts were set as the same value. The longer side of the cross-section of inclined struts can be calculated as strutWidth/cos(strutAngle), roughly 1.22–3.87 times strutWidth as the strutAngle increases from 55 to 75°. The cyan solid lines represent the laser scan vectors, and the yellow solid shape is the melt track of the border. The red double arrow represents the laser beam compensation, d_c. As shown in the side view of struts, the melt tracks are stacked with the specific layer thickness, 20 μm. As for the inclined struts, the melt tracks shift in every single layer with an offset of d_L*tan(strutAngle), roughly 28–75 μm.

Due to the laser beam energy distribution in LPBF, the cross-section of melt tracks is generally symmetric [34]. Figure 13c depicts the cross-sectional view of the melt tracks in the 0.3-mm strut. Based on the calculated results in Fig. 12, the depth of the melt track is much higher than the layer thickness. The melt track tends to re-melt at least three previous layers. The middle of the border melt track has a compensation, d_c, with the geometry border (dash line). For the vertical struts, the width of vertical strut can be estimated as strutWidth-2d_c + width. Based on the calculated results, the width of vertical strut fabricated with 113 W and 700 mm/s is 0.281 mm. The experimental results in TM2 samples are 0.298 mm and 0.302 mm, which are a little higher than the calculated results. The effects of laser power and scan speed on the vertical strut width are consistent with the calculated results from the Matlab. As for the inclined struts, the slice shifts layer-by-layer as discussed in the previous paragraph. Part of the scan vectors are directly on the powder particles. Compared with the vertical strut, less solid beneath the melt track leads to lower heat conduction [17] and higher sustained temperatures in the melt pool. Thus, more powder particles will be melted and form a larger melt track. The excess melted mass tends to penetrate into the powder particles with the effect of gravity and surface capillary force [35], which forms large dross as shown in Figs. 5b–f and 13c. Meanwhile, the depth of the melt track also causes the severe mismatch of melt tracks and the designed geometry. With the increase of laser power, the melt track becomes wider and deeper, which leads to a larger dimensional error for the inclined struts. However, the effects of scan speed on the strut width does not follow the MatLab calculated results. It was found that increasing scan speed gave rise to residual stresses [36], which can worsen the warping effect [37] and cause larger dimensional errors. Furthermore, for the smaller planar cross-section of the vertical strut, the overlaps between melt tracks are higher than the inclined struts and the large cross-section near the assembly slots. When the struts become thicker, the overlaps between melt track become smaller, which could lead to pores being created in the frames. This helps to explain the specific distribution of pores in the S3 frame as illustrated in Fig. 10c. Also, thicker struts have better structural stability when interacting with the powder spreader. Thus, the dimensional accuracy is generally better with thicker struts.

Unlike conventional manufacturing technologies, LPBF tends to produce surfaces with several topographical features including micro-scaled surface asperity, wave-like melt track features and form error globules of surface pores [12]. The surface profiles of the side surface, up-skin surface and down-skin surface are also marked in Fig. 13c. The wave-like features and form error globules are the main factors to influence the surface roughness in this study. There is minimum variation in the waviness profile of the side surface, but it is higher in the up-skin surface and higher still in the down-skin surface. There are less partially sintered particles on the side surface and up-skin surface due to the lower sustained melt pool temperature. However, many partially melted particles and even large dross can be observed on the down-skin surface, which is also reported in other publications [11, 12, 15, 35]. Thus, the bottom surface is much rougher compared to the other surfaces. When strut thickness increases, there is improved structural stability and better thermal conduction through the struts helps to reduce the surface roughness. The effects of laser power and scan speed variation on the surface roughness is unclear based on our results. However, some basic features of surface quality of thin strut structures have been concluded in Section 3.2.

In this study, the effects of strut dimensions and angles, laser power and scan speed on the dimensional accuracy and surface quality of the thin struts, that make up a typical frame for a replacement heart valve, were systemically studied. The results can be concluded as follows: