Multi-layered laser welded metallic joints are often used for electrical connections, as in batteries. These joints are commonly laser welded multi-layered metallic stack-ups. Although additional layers are often beneficial from a battery design architecture standpoint, an increase in layers leads to an increase in porosity. This porosity issue is especially pronounced for anodized aluminum. An increase in porosity can be detrimental to the structural behavior of the joint [1] . The conditions for laser weld porosity to occur are based on the weld pool dynamics, keyhole collapse, and solidification processes. High turbulence of the molten weld pool can cause entrained gas and porosity. Keyhole porosity is caused by keyhole instability and collapse. Interface porosity can develop where gas is trapped between the layers and is enclosed due to varying melt pool size associated with different locations in the laser oscillation pattern [2] [3] [4] [5] . Weld joints with poor strength also may have low electrical conductivity or fatigue strength. It is thus important to assess weld integrity by characterizing the porosity.
Laser weld inspection can be done inline, during the laser welding process, or post-process after the weld has been formed. Inline inspection techniques primarily rely on monitoring one of the many energy forms that are emitted from laser-material interactions during welding. They necessarily rely on remote sensors, since contact is not possible. These techniques fall within the process-monitoring domain, and as such will not be reviewed here. The reader is referred to [6] for a more in-depth review of inline laser weld monitoring techniques. Post-weld inspection techniques include ultrasound, EMAT, X-ray radiography, and eddy current. Passini et al. [7] used phased-array ultrasound to inspect porosity in laser welded thin aluminum sheets. They found that
Multi-layered laser welded metallic joints are often used for electrical connections, as in batteries. These joints are commonly laser welded multi-layered metallic stack-ups. Although additional layers are often beneficial from a battery design architecture standpoint, an increase in layers leads to an increase in porosity. This porosity issue is especially pronounced for anodized aluminum. An increase in porosity can be detrimental to the structural behavior of the joint [1] . The conditions for laser weld porosity to occur are based on the weld pool dynamics, keyhole collapse, and solidification processes. High turbulence of the molten weld pool can cause entrained gas and porosity. Keyhole porosity is caused by keyhole instability and collapse. Interface porosity can develop where gas is trapped between the layers and is enclosed due to varying melt pool size associated with different locations in the laser oscillation pattern [2] [3] [4] [5] . Weld joints with poor strength also may have low electrical conductivity or fatigue strength. It is thus important to assess weld integrity by characterizing the porosity.
Laser weld inspection can be done inline, during the laser welding process, or post-process after the weld has been formed. Inline inspection techniques primarily rely on monitoring one of the many energy forms that are emitted from laser-material interactions during welding. They necessarily rely on remote sensors, since contact is not possible. These techniques fall within the process-monitoring domain, and as such will not be reviewed here. The reader is referred to [6] for a more in-depth review of inline laser weld monitoring techniques. Post-weld inspection techniques include ultrasound, EMAT, X-ray radiography, and eddy current. Passini et al. [7] used phased-array ultrasound to inspect porosity in laser welded thin aluminum sheets. They found that
Multi-layered laser welded metallic joints are often used for electrical connections, as in batteries. These joints are commonly laser welded multi-layered metallic stack-ups. Although additional layers are often beneficial from a battery design architecture standpoint, an increase in layers leads to an increase in porosity. This porosity issue is especially pronounced for anodized aluminum. An increase in porosity can be detrimental to the structural behavior of the joint [1] . The conditions for laser weld porosity to occur are based on the weld pool dynamics, keyhole collapse, and solidification processes. High turbulence of the molten weld pool can cause entrained gas and porosity. Keyhole porosity is caused by keyhole instability and collapse. Interface porosity can develop where gas is trapped between the layers and is enclosed due to varying melt pool size associated with different locations in the laser oscillation pattern [2] [3] [4] [5] . Weld joints with poor strength also may have low electrical conductivity or fatigue strength. It is thus important to assess weld integrity by characterizing the porosity.
Laser weld inspection can be done inline, during the laser welding process, or post-process after the weld has been formed. Inline inspection techniques primarily rely on monitoring one of the many energy forms that are emitted from laser-material interactions during welding. They necessarily rely on remote sensors, since contact is not possible. These techniques fall within the process-monitoring domain, and as such will not be reviewed here. The reader is referred to [6] for a more in-depth review of inline laser weld monitoring techniques. Post-weld inspection techniques include ultrasound, EMAT, X-ray radiography, and eddy current. Passini et al. [7] used phased-array ultrasound to inspect porosity in laser welded thin aluminum sheets. They found that
Multi-layered laser welded metallic joints are often used for electrical connections, as in batteries. These joints are commonly laser welded multi-layered metallic stack-ups. Although additional layers are often beneficial from a battery design architecture standpoint, an increase in layers leads to an increase in porosity. This porosity issue is especially pronounced for anodized aluminum. An increase in porosity can be detrimental to the structural behavior of the joint [1] . The conditions for laser weld porosity to occur are based on the weld pool dynamics, keyhole collapse, and solidification processes. High turbulence of the molten weld pool can cause entrained gas and porosity. Keyhole porosity is caused by keyhole instability and collapse. Interface porosity can develop where gas is trapped between the layers and is enclosed due to varying melt pool size associated with different locations in the laser oscillation pattern [2] [3] [4] [5] . Weld joints with poor strength also may have low electrical conductivity or fatigue strength. It is thus important to assess weld integrity by characterizing the porosity.
Laser weld inspection can be done inline, during the laser welding process, or post-process after the weld has been formed. Inline inspection techniques primarily rely on monitoring one of the many energy forms that are emitted from laser-material interactions during welding. They necessarily rely on remote sensors, since contact is not possible. These techniques fall within the process-monitoring domain, and as such will not be reviewed here. The reader is referred to [6] for a more in-depth review of inline laser weld monitoring techniques. Post-weld inspection techniques include ultrasound, EMAT, X-ray radiography, and eddy current. Passini et al. [7] used phased-array ultrasound to inspect porosity in laser welded thin aluminum sheets. They found that 48th SME North American Manufacturing Research Conference, NAMRC 48 (Cancelled due to while small pores were not well resolved, grouped pores directly affected the wave attenuation. Laser-vision systems have also been successfully employed for laser weld inspection [8] ; however, vision systems do not allow for subsurface characterization. Laser ultrasound allows for single-sided, remote, non-contact, inspection [9] . In this case, the surface of the inspected sample is slightly altered since ablation is required to achieve a high signal-to-noise ratio. Diot et al. successfully used laser ultrasound to characterize the porosity in laser welded aluminum alloy plates [10] . Destructive techniques, such as tensile tests and cross sections, can alternatively be employed in an audit-type fashion to understand the strength and potential porosity or lack of fusion. Of course, destructive techniques cannot be used for 100% inspection.
Laser welded electrical joints cannot be inspected using many of the aforementioned techniques, because the surface cannot be altered (e.g. applying couplant or ablating the surface) without sacrificing functionality. A quick, non-contact technique is very desirable. For this reason, pulse thermography [11] [12] was chosen as a promising approach.
Thermography has been widely applied as a non-destructive technique on polymers, but low-emissivity materials present more challenge. Flash thermography has been shown to be a viable nondestructive technique for characterizing thin metallic ultrasonic welded joints [13] . Recently, Broberg studied surface cracks in welded metal plates using thermography with an infrared heat source [14] . Other researchers have employed process heat for thermography to identify pores as small as 0.5 mm in copper laser welded fillet joints [15] . These recent studies have demonstrated the successfulness of thermography in characterizing surface and slightly sub-surface defects. Uncertainty remains surrounding the effect of porosity on thermographic measurements in multi-layered welds. Specifically, it is known that defect detection is limited by greater depth and by smaller size of defects due to diffusion. For this reason, a controlled study was performed on both bare and anodized thin aluminum sheets that were welded to a thicker aluminum substrate. The anodized aluminum was chosen for comparison because of the tendency to develop porosity during laser welding as shown in previous studies [16] . Multi-layered stack-ups composed of 1-, 2-, and 3-layers were welded to the substrate to create a sample set with varying levels of porosity, and the samples were assessed via flash thermography. X-ray computed tomography (CT) was used to quantify porosity related to thermographic measurements. Lap shear strength and electrical resistance measurements were also performed.
Pulsed thermography was implemented via a single-sided flash thermography set-up, where the heat source was a 1200Ws Xenon flash tube. The resulting sample response was recorded with an x8501 MWIR FLIR infrared camera, operating at a sample rate of 590Hz. Please refer to [13] for a more detailed description of the set-up. To mitigate diffusion effects, the raw thermal data was post-processed to obtain a heat source distribution (HSD) image. A time shortly after the flash was selected to maximize the signal-to-noise ratio. The heat source distribution (W/m 3 ) is found from the heat equation as follows:
where k is thermal conductivity (Wm -1 /°C), α is the thermal diffusivity (m 2 /s), and T is temperature (°C). The partial derivative terms are experimentally measured, whereas the constants k and α are known for aluminum [11] . To mitigate pixel to pixel variation, smoothing was performed prior to taking the spatial derivatives.
In this section, the preparation of the samples is discussed, along with characterization by CT, electrical resistance and tensile tests. These characterizations are later compared with the thermal results for the purpose of evaluating thermography's ability to detect porosity. Lap-shear coupons were created by laser welding upper sheets of 0.2 mm Al to a lower sheet of 1.6 mm 3003-H14 Al. To generate porosity, one of two upper sheet materials (bare Al or anodized aluminum) were layered with one, two, or three sheets. The sheets were welded with a fiber laser with a maximum power output of 2000 W at the 1070 nm wavelength. The laser beam was delivered by an optical fiber of 50 µm in diameter before connecting to a galvo scanner, which resulted in a final laser spot size of approximately 115 µm at the focal plane. The working distance of the scan head was 300 mm and the scanning area with the f-theta lens was 125 mm by 125 mm. For these samples, the linear scan speed was 175 mm/s. During welding, the beam traveled in an oscillation with an elliptical pattern with the amplitudes of 0.5 mm (perpendicular to the laser travel direction) and 0.2mm (parallel to the laser travel direction) at a frequency of 250 Hz.
Both upper sheet materials were Al 1100-O, with their base material properties shown in Table 1 . The anodized material, labeled AA, had an anodized coating thickness of 12.5 µm [16] . The set of one, two, or three sheets of each material were laser welded with a laser power of 1200 W, 1600 W, and 2000 W, respectively, to the lower sheet for a total of six conditions. Note that during this investigation, no attempt was made to reduce the porosity generated by adjustment of the laser conditions. The resulting weld seams were 30 mm long on 45 mm wide samples with a 25 mm overlap as shown in Figure 1 . Six replicates were welded for each condition.
One sample from each set was measured via X-ray CT to quantify the porosity. The samples were cut to remove excess non-weld material prior to scanning. Scans were collected with a Nikon XT scanner with a 225 kV microfocus tube. The scan geometry was such that the voxel size in the data set was about 19 µm. Therefore, the minimum theoretical detectable pore size was about 38 µm in diameter; practically, the software routine described below rejected most detection events below 50 µm in diameter as unreliable. Pore identification was performed using VolumeGraphics GmbH VGSTUDIO MAX version 3.3 using the VGDefX pore identification algorithm, which uses an initial thresholding to identify pore geometries that have a high probability of being a pore based on the local density measurements. From a thermography standpoint, the most important pores are those which obstruct the path of thermal flow, which includes pores that may be open to the surface typically discarded by CT scanning. For this reason, a "surface closing" technique was performed to include as many surfaceconnected pores as possible. This technique will identify areas that are substantially concave, and "close" that concavity along the surface to count it as a pore. This technique was limited to concave regions that were at least one radius deep (nominally a half sphere or more concave) and only closed openings smaller than about 60-100 µm (3-5 voxels). Noise reduction was used to average single-voxel density variations, and thus eliminate false detections of small pores that are below the resolution of the scan. Three types of pores were observed in these samples: small entrapped gas pores, pores that localized to the interface due to the stitch pattern of the laser weld, and deep pores that resulted from keyholing during laser welding (see Figure 2 ). The smallest and most numerous pores appear to be from trapped gases in the molten pool that are captured during rapid solidification. These are highly spherical pores, and often located near the top surface of the weld. The second type are pores located at the faying interface in the cavities between the peaks of the stitch weld. These are relatively large pores (compared to the trapped gas pores) that are either partially or fully closed off from the faying interface. When they are partially closed off, these may involve large networks of interconnected pores with thin regions connecting them. Finally, there are keyhole pores, which are found in the base metal far below the faying interface. In some conditions, the keyhole reached full penetration of all sheets, leaving protrusions and pores at the opposite surface. Collapses of this keyhole can lead to the formation of these large pores relatively deep within the thicker sheet. More gas porosity was seen in the anodized welds than the bare metal, and in general the volume of pores increased as the number of layers increased (see Figure 3 ). However, since the volume of the sample increased with number of layers, the fraction of porosity remained relatively constant with layer thickness. While the overall porosity fraction changes very little between the bare metal 1-layer and 3-layer stack-ups, the 1-layer weld is dominated by deep keyhole pores, while the 3layer sample has many more pores at the interfaces (nearer to the surface) than in the keyhole locations (compare Figure 3 d and f). Electrical resistance measurements were taken using a 4point probe resistance fixture, which measures the resistance through the thickness of each weld. Each measurement was recorded to the nearest 0.01 micro-ohm (μΩ) three times and averaged. The anodized stack-up displayed an increasing resistance with stack-up layer number (see Figure 4) . No significant differences in mean resistivity were found using the Tukey comparison method [17] between stack-ups in the bare aluminum sample set. The anodized set, however, exhibited statistically significant higher average resistances than the bare set, both comparing across number of upper layers and both sets in aggregate. This correlates well to the conditions where there is a substantial fraction of the small (50-150 µm) gas pores near the surface, despite these features being smaller and further from the surface than typically can be found in thermography. It may be possible that these relatively small gas pores are located so closely together that the remaining metal between pores becomes very thin and has a tortuous path from top to bottom of the weld, which therefore substantially affects the conductivity. The larger, more widely distributed faying interface and keyhole pores do not have this effect (and are therefore not observed in the thermography data), since there are portions away from the pore that have direct or nearly direct connectivity from top to bottom of the weld. Four samples from each set were pulled in tension to failure via an Instron universal testing machine with side action grips at a rate of 10 mm/min. The lap-shear samples were loaded such that the upper sheets were inserted in one grip, and the lower sheet was inserted in the other. The load was applied perpendicular to the long axis of the weld. Shims were not used during testing. Results are shown in Figure 5 . The welded coupons in the bare set failed through the thickness of the upper sheets near the weld in all cases. For the welded set with bare layers, the maximum load increased as the number of upper sheets increased as expected. For the welded coupons with the anodized layers, the welds also failed through the thickness of the upper sheets, but the failure appeared to originate within the welded area, most likely rupturing through the regions of extensive porosity. The elongation at maximum load during the test for the welds with the anodized aluminum layers was lower (average 0.46 mm vs. 1.75 mm for the welds with bare coupons). For the welds with anodized layers, the maximum load did not increase with additional layers.
For the anodized samples, the relatively-constant, low strength can be explained by the high number of gas pores in the upper portion of the weld. A shear line or crack can develop from the faying surface to the free surface through these gas pores, and the porous material fails at a relatively low load. In the bare metals however, the shear localization or crack is going through less-porous material around the larger pores that developed near the interface. This solid metal increases in thickness as the number of top layers increase, leading to a higher failure load than the anodized material, and an increasing failure load with increasing number of layers.
Observations on the general thermography trends will now be discussed and presented, followed by a discussion on the ability of thermography to detect porosity.
After the thermal data was captured, they were analyzed as in [9, 10] to display the heat source distribution (HSD) of only the region of interest. Figure 6 shows HSD images for sample #1, i.e., the sample selected for CT scanning, from each stackup set. The two-layer bare sample contained a surface scratch, which was captured in the resulting thermography image. The dark pixel values correspond to a more negative HSD value, indicating better thermal flow. The color scale is the same for all six images. The anodized samples exhibit observably lowermagnitude HSD values than the bare samples, likely due to the higher presence of gas pores near the surface for anodized samples when compared to the bare samples. This is further indicated in Figure 7 , which contains the histograms for the HSD images in Figure 6 . This shift in HSD values was captured by determining the location of the maximum HSD histogram value. While this metric alone will not completely describe the pixel distribution, it serves well to indicate the general peak location of the pixels for the distributions in this study. Fig. 6 . Table 2 . HSD Histogram Peak Location average with respect to number of layers for bare and anodized aluminum sample sets. Figure 8 (a) and (b) contain the HSD maximum peak histogram value relationship with electrical resistance and tensile strength, respectively. As expected, a positive trend is observed between the electrical resistance and HSD peak value. Recall that more negative HSD indicates better thermal flow. A negative trend is observed between the HSD peak value and tensile strength.
Based on the porosity results presented in Section 3, it is hypothesized that porosity effects on thermography generally increase with the number of layers, as more pores are near to the surface with increasing layers. Refer to Table 2 , which contains the average (across six samples) HSD histogram peak value locations for all stack-ups. For both the anodized and bare samples, it is observed that 1-layer results in the highest magnitude HSD peak histogram value. For the averaged values, there is no observable difference between 2-and 3-layer stack-ups for the anodized sample or the 1-and 2-layer stackups for the bare samples. For sample 1 in each set, the relationship between the surface area of pores and the maximum histogram peak location is shown in Figure 9 . The anodized and bare samples also show clear separation in both the surface area of the pores and the maximum histogram peak location. 
All else being equal, a deeper pore will be more difficult to detect than a pore closer to the surface due to thermal diffusion effects. Furthermore, thermography necessarily only captures the IR emitted from the sample surface, i.e., the surface heat. Since the sample is a three-dimensional object, the heat spreads in all directions, i.e., diffusion occurs. By the time the heat reaches the surface and emits IR, diffusion causes blurring of the resulting IR signal. By using the HSD, this blurring effect is slightly mitigated, though not completely [18] .
Generally speaking, the smallest detectable defect is one which has a diameter that is at least two times larger than its depth beneath the surface [19] . For the weld samples considered in this study, the thickness of the welds vary between 0.2 mm to 0.6 mm (for 1-layer to 3 layer, respectively). The theoretical minimum detectable pore size (diameter) at the top of the substrate for 1-, 2-, and 3-layer stack-ups is therefore 0.4 mm, 0.8 mm, and 1.2 mm, respectively.
Upon initial inspection, these numbers indicate that thermography is a fruitless endeavor; however, it is important to recall that the weld coupons contain a distribution of pores. While this method may not be able to accurately quantify the dimensions of a pore, a distribution of pores will still influence the overall heat transfer. The overall effect of porosity will therefore manifest itself in the macroscopic view of the thermal behavior. This macroscopic view is apparent when comparing the anodized and bare stack-ups. From Section 3, the anodized aluminum stack-ups had more porosity than the bare aluminum stack-ups. This is reflected in the thermography by the shift in the histograms, i.e., the histogram's maximum peak location (Figure 7) . Though unresolvable, evidence of the presence of deeper pores can still be observed in the HSD images. Figure 10 shows an HSD image for a 3-layer bare sample along with CT slices corresponding to cross-sections with a surface pore, low porosity, and a faying surface pore. Notice that the surface pore shows up very clearly in the thermal image as a light gray spot. Comparing the deeper faying surface pore with the lowporosity cases, it is observed that while the deep pore is not resolved, the pixel gray values are significantly lighter, indicating worse thermal flow. Figure 11 shows an HSD image next to a CT slice through the middle of the longitudinal axis of the weld. From this sample, it becomes apparent that while surface pores strongly impede heat flow, fine subsurface gas pores do not have such a drastic effect. These regions display relatively high-magnitude HSD values compared to "unconnected" regions as denoted in the figure. Though it is important to remember that these gas pore regions still exhibit lower-magnitude HSD values than low-porosity regions (comparing Figure 10 and Figure 11 ). It is also observed that the "trough" areas result in lower-magnitude HSD values. These troughs can be thought of as (open to the) surface pores, but these trough areas were likely not illuminated as well by the flash lamp, since the lamp will never be perfectly incident with the weld. Surface texture is therefore another important consideration during the interpretation of thermal data, since it directly affects the ability of the external heat source to uniformly heat the sample. Very deep pores, such as in the substrate material, will be undetectable unless they are very large.
These results indicate that the efficacy of thermography to detect porosity in multi-layered metal laser welds is heavily dependent on both the depth and size of porosity, sample thickness, and weld surface texture. Accordingly, the 1-layer welds are easier to interpret due to the smoother surface texture Fig. 11 . HSD image for 3-layer anodized aluminium Sample #1 with some corresponding CT scans in the cross-sectional direction and along the axial length of the weld. and smaller thickness. Trends do however exist, and so the usefulness of this technique ultimately depends on the weld acceptance criteria and how much error the customer is willing to accept. In any case, it is imperative that the inherent complications are understood. It is worth noting that some steps can be taken to overcome certain limitations, but their success will be application specific. For example, shaving down the weld surface could help to combat the effects from surface texture.
The purpose of this study was to determine the ability of thermography to detect porosity in multi-layer laser welds. Thermography was performed on laser welded samples consisting of 1, 2 or 3 top layer sheets of bare or anodized 0.2 mm aluminum and a bottom sheet of 1.6 mm 3003 aluminum, specifically created to contain varying levels of porosity. The samples were characterized by X-ray CT, electrical resistance, and tensile testing to quantify porosity and understand its effect on thermography results. It was observed that increasing the number of top layers from 1 to 2 generally resulted in increased volume of porosity, while the samples with 2 or 3 upper layers had a generally equivalent level of porosity. The anodized samples contained more porosity than bare samples, and also contained deep valleys or surface pores which created a rough surface texture, leading to lower thermography values.
A maximum peak histogram value was taken from the thermography data which correlated well with the X-ray CT, electrical resistance and tensile data. Thermography was more affected by pores close to the surface as indicated by the porosity cross sections from the CT data. It was seen, however, that where there were groups of many small pores, the overall thermography values indicated lower heat flow than other areas even if the individual pores could not be resolved. Overall, it is shown that thermography correlates well with electrical resistance and tensile results, although mores studies are needed to evaluate thicker stack-ups due to the limitations placed by diffusion.