## 2 Materials and Methods  
Three rectangular cuboids with dimensions of \(10\times 10\times 1.25\) mm\({}^{3}\) were manufactured by SLM using a MCP Realizer SLM 250 from Grade 5 titanium powder provided by SLM Solutions. According to the certificate from the provider the powder has the following composition: 6.34 wt.% Al, 4.1 wt.% v, 0.183 wt.% Fe, 0.140 wt.% O, 0.005 wt.% C, 0.007 wt.% N, 0.0020 wt.% H, and the powder size ranges from 20 to 63 \(\upmu\)m. The specimens were built on support structures using three different scan strategies (Figure 1):  
1. Line scanning using antiparallel stripes,
2. Island scanning using parallel-interlaced-reversed stripes and
3. Island scanning using a modeled pattern of six scan types: 1. out-in spiral
2. in-out spiral
3. antiparallel stripes
4. parallel stripes
5. parallel-interlaced stripes
6. parallel-interlaced-reversed stripes. The scan pattern in Figure 1c was simulated by [PERSON] and [PERSON] [21] for a \(10\times 10\) mm\({}^{2}\) square using a \(20\times 20\) grid (i.e., an island size of \(0.5\times 0.5\) mm\({}^{2}\)). The full pattern is shown in Figure S1. The island scanning sequence for both island scanning stripes and island scanning modeled was the same and kept constant through the build. A randomized processing sequence was applied, as generated by [PERSON] and [PERSON] [21], as shown in Figure S2. The processing parameters were kept constant, using a laser power of 119 W, scan speed of 800 mm s\({}^{-1}\), energy density of 37 J mm\({}^{-3}\), hatch distance of 80 \(\upmu\)m, and layer thickness of 50 \(\upmu\)m.  
Figure 1: Investigated scan strategies: (**a**) line scanning using antiparallel stripes; (**b**) island scanning using parallel-interlaced-reversed (PIR) stripes; (**c**) island scanning using a specific random pattern of the six scan types: (**1**) out-in spiral, (**2**) in-out spiral, (**3**) antiparallel stripes, (**4**) parallel stripes, (**5**) parallel-interlaced stripes, and (**6**) parallel-interlaced-reversed stripes. The scan order and type was kept consistent in every layer of a specimen, and there was no rotation between layers. X-ray tomography of the as-built specimens was performed in a ZEISS Xradia 410 Versa, using a voltage of 100 kV, a power of 10 W, and a HE1 filter. For each specimen, two computed tomography (CT) scans were performed: one full specimen using the large field of view (LFOV) objective, taking 1601 projections with an 8 s exposure time, and one with 4\(\times\) zoom objective, taking 3201 projections with a 15 s exposure time. The projection images were reconstructed using the inbuilt software which is based on an implementation of the Feldkamp-Davis-Kress (FDK) algorithm [22]. The resulting reconstructed volumes had a voxel size of 13.5 \(\upmu\)m and 3.4 \(\upmu\)m, respectively, giving detection limits of around 25 \(\upmu\)m and 7 \(\upmu\)m. Matlab and Avizo 9 were used for porosity analysis. For pore statistics, pores with volumes below four times the voxel volume were removed from the data. The pores were divided into spherical and irregular pores, using the sphericity shape factor:  
\[\Psi=\frac{\pi^{\frac{1}{3}}\left(6V_{p}\right)^{\frac{2}{3}}}{A_{p}}, \tag{1}\]  
where \(V_{p}\) and \(A_{p}\) are the volume and surface area of the pore, respectively. A cut-off value of 0.7 was used, where pores with \(\Psi>0.7\) were treated as spherical, while pores with \(\Psi<0.7\) were treated as irregular. The roughness of the top surfaces of the specimens was measured using an Alicona Infinite Focus microscope (IFM) with G4 5\(\times\) objective and evaluated using SPIP software. No form removal was employed in the calculations of three-dimensional (3D) surface roughness, S. Three different areal amplitude parameters were calculated: arithmetic mean height, S\({}_{\text{a}}\); root mean square height, S\({}_{\text{q}}\); and maximum height, S\({}_{\text{z}}\).