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Imaging ionomer in fuel cell catalyst layers with synchrotron nano transmission x-ray microscopy
Solid State Ionics 335 (2019) 38–46
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Imaging ionomer in fuel cell catalyst layers with synchrotron nano transmission x-ray microscopy Stanley J. Normilea, Iryna V. Zenyuka,b, a b
T
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Department of Mechanical Engineering, Tufts University, Medford, MA 02155, USA Department of Chemical and Biomolecular Engineering, National Fuel Cells Research Center, University of California Irvine, Irvine, CA 92617, USA
A R T I C LE I N FO
A B S T R A C T
Keywords: Transmission x-ray microscopy X-ray computed tomography Fuel cells Catalyst layer Ionomer distribution
This work presents a novel characterization method for distinguishing ionomer phase within porous composite catalyst layer. Quantifying ionomer distribution in a catalyst layer of polymer electrolyte fuel cells (PEFCs) is critical to understanding the morphological and transport properties of this key component. Current methods to image ionomer rely on staining it with heavy ions, such as cesium, Cs, to enable detection with hard X-rays, however if the catalyst layer contains electrocatalyst, such as platinum, Pt, then the challenge is to distinguish between Cs-stained ionomer and Pt. These two materials have very similar X-ray attenuation coefficients. Using synchrotron transmission x-ray microscopy (TXM) and two energy imaging, above and below Pt electrocatalyst absorption edge, the ionomer distribution is quantified. The method is applied to a PEFC catalyst layer and compared against the method of single energy imaging, which is not able to separate the two phases.
1. Introduction Polymer electrolyte fuel cells (PEFCs) are a promising alternative to traditional internal combustion engines for automotive applications due to their high efficiency and zero tailpipe emissions [1]. Developing cathode catalyst layers with high electrocatalytic activity and low transport resistance is critical to ensuring high power densities of PEFCs [2,3]. Fast proton transport through the membrane electrode assembly (MEA) of the PEFC is essential, as protons are reactants in the oxygen reduction reaction. The catalyst layer of a state-of-the-art conventional PEFC is prepared as an ink consisting of carbon black, platinum (Pt) nanoparticles, and ionomer. The carbon black acts as an electrocatalyst support material and also as the electron conducting phase, the Pt acts as the electrocatalyst, and the ionomer is both the binder and the electrolyte through which the protons conduct [1,4]. Perfluorinated sulfonic acid ionomers (PFSA) are the most commonly used ionomers in PEFCs due to their exceptionally high ionic conductivity when solvated and their mechanical stability [5]. PFSA ionomers separate into hydrophilic ion-conducting sulfonic acid groups and hydrophobic matrices of polytetrafluoroethylene (PTFE) domains. It is essential that the ionomer be uniformly distributed within the catalyst layer as ionomer provides a path for the proton reactants to reach the catalyst sites on the surface of the platinum nanoparticles [4]. Experiments have corroborated this, showing that ionomer loading and distribution both
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significantly affect PEFC performance [6–8]. Given the importance of ionomer distribution, there have been several attempts to quantify it using imagining techniques. Both electrons and X-rays have been used to probe ionomer distribution within the PEFC catalyst layer. Ionomer has a low X-ray absorption index, so it is not visible in X-ray absorption contrast imaging. It also has a refractive index decrement that is lower than both Pt and carbon, which means that it will be the dimmest feature on a phase-contrast image. A solution to this imaging problem is to stain (or ion-exchange) the ionomer with heavier elements, such as cesium (Cs) ions. Cs has a high Xray absorption index and therefore it is easy to detect in X-ray absorption-contrast imaging. Lopez-Haro et al. [4] used the technique of ionomer staining with high-angle annular dark-filed scanning transmission electron microscopy (HAADF-STEM). Differentiating between Pt nanoparticles and Cs-stained ionomer in their images is very difficult, since both features would give high absorption contrast compared to the carbon black support. Their solution was to prepare a catalyst ink that did not contain any Pt to have all bright features attributed to Csstained ionomer. Using this technique, they were able to show that only 60–76% of the ionomer in the catalyst ink uniformly covers the carbon black (CB) support, however they were unable to see how the ionomer interacts with the Pt nanoparticles as their catalyst layer was made only with CB and ionomer [4]. Others, such as Rieberer et al., have also used Cs staining with TEM imaging [9]. Scanning electron microscopy (SEM)
Corresponding author at: Department of Chemical and Biomolecular Engineering, University of California Irvine, Irvine, CA 92617, USA. E-mail address: [email protected] (I.V. Zenyuk).
https://doi.org/10.1016/j.ssi.2019.02.017 Received 14 September 2018; Received in revised form 4 February 2019; Accepted 16 February 2019 0167-2738/ © 2019 Elsevier B.V. All rights reserved.
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to support ratio (Wh/S) was 10.0, the ionomer (3 M 825 equivalent weight (EW) PFSA) to support (I/S) ratio was 0.80. The final Pt loading of the electrode was 0.4 mgPt cm−2. High loading and relatively large dimensions of whiskers (40 nm by 0.5 μm) ensured sufficient X-ray attenuation and good visibility, given the resolution limitations of the nano X-ray CT. More details on the fabrication of the dNSTF electrodes can be found in Ref. [12]. Ionomer staining was performed by the procedure described above. It is important to note that samples prepared on an inert substrate, such as Kapton, are more stable during nano X-ray CT imaging than those deposited on a membrane. X-ray damage to membranes during scans can be significant, causing sample to move during the scan, introducing artifacts during the reconstruction procedure.
is another common way to study ionomer distribution. The drawback of the technique is that it does not provide 3D information, except in the case of focused ion beam SEM (FIB-SEM), which is a destructive technique. While TEM imaging is useful for visualizing ionomer in 3D, it has a large disadvantage in that the sample must be very thin, on the order of 100 nm [10]. Another disadvantage of electron beams is that the soft ionomer phase is highly susceptible to electron beam damage. Compensating for this requires cryo-chambers and other difficult samplehandling techniques. Transmission X-ray microscopy (TXM) and its three-dimensional variation, X-ray computed tomography (CT), are ideal for imaging ionomer within the catalyst layer, as X-rays at higher energies interact less with the ionomer than do electrons and therefore cause significantly less damage. X-ray imaging techniques have larger fields of view and lower resolutions than electron-imaging techniques. The ~80 μm field of view of nano X-ray CT is ideal for imaging the bulk ionomer phase along the entire thickness of the catalyst layer; however its ~30 nm resolution is not fine enough to image the thin-film ionomer that covers agglomerates within the catalyst layer. X-ray CT is also nondestructive, which makes it much more attractive than FIB-SEM. Komini Babu et al. [6] demonstrated that Cs staining is an effective method for visualizing ionomer in platinum group metal (PGM) free electrodes using X-ray CT. They avoided the aforementioned challenge of distinguishing between Cs and Pt by using PGM-free electrodes. They found that the ionomer distribution is dependent on loading, with 50 wt % ionomer distributed uniformly and 35 wt% forming large, dense agglomerates. Recently, Cetinbas et al. [11] used absorption contrast X-ray CT to image Cs-stained low-loaded PGM catalyst layers. They neglected to differentiate between the Cs-stained ionomer and the Pt catalyst, both of which appear bright in absorption-contrast imaging. They claimed that the relative scarcity of catalyst in low-PGM catalyst layers (0.092 mgPt cm−2) implies that the fraction of bright objects in their images that is Pt is relatively small and therefore all bright objects can be assumed to be Cs-stained ionomer. While this may hold true for lowloaded Pt electrodes, there is a need to develop a higher fidelity imaging approach, where Pt loading is not a concern. Here, we present an approach of two-energy imaging, where the electrode is imaged below and above the absorption L3-edge of Pt. To the best of the authors' knowledge, this is the first use of two-energy imaging for the separation of Pt from ionomer in fuel cell catalyst layers.
2.2. Imaging procedure The two energy imaging was performed at beamline 6-2 at the Stanford Synchrotron Radiation Lightsource (SSRL) at SLAC National Accelerator Laboratory (SLAC). For each scan, the sample was exposed 180 times for 1 s each as the sample was rotated from 0 to 180° about the axis formed by the pin on which it was mounted. The sample was scanned two times, once at a photon energy of 11.5 keV and again at 11.7 keV. These energies were chosen to take advantage of the L3 absorption edge of platinum as shown in Fig. 2b. At 11.5 keV, the mass attenuation coefficients of Pt and Cs are 80.6 and 136 cm2 g−1 respectively. At 11.7 keV, they are 191 and 132 cm2 g−1 respectively. The imaging for the single energy experiment was performed at Beamtline 32-ID at the Advanced Photon Source (APS) at Argonne National Laboratory. Monochromatic X-rays illuminate the beam shaping condenser, then sample, a Fresnel zone plate (FZ), and are collected at an imaging detector. Gratings of 60 nm for FZ plates were used to achieve resolution of 60 nm. The FOV was approximately 75 μm × 75 μm and the scan-time was 20 min. 1500 projections were recorded with 1 s exposure per projection. Zernike phase contrast was used to detect carbon by placing a phase-ring in the back-focal plane of the ZPs. The phase-ring was removed from the path of x-rays for absorption-contrast imaging. 2.3. Image processing The images collected at SSRL were reconstructed and aligned using TXM Wizard software [13]. The reconstruction produced images that were 15 × 16 × 24 μm with a voxel size of 24 nm. Once reconstructed, they were cropped using the Fiji distribution of ImageJ [14] to a size of 2.4 × 3.9 × 8.0 μm so that only a pristine section of sample was visible. The 11.5 keV image was then subtracted from the 11.7 keV image. Once the subtraction was complete, all three images were filtered using a median filter and thresholded using a combination of ImageJ's default thresholding algorithm and manual adjustments as detailed in the discussion below. The thresholded images were then analyzed to find the volume fraction and tortuosity factor using Tau Factor [15], and the size distribution using the BoneJ plugin in ImageJ [16]. Finally, the images were volume rendered using Avizo (FEI Visualization Sciences Group, Berlin). For the APS data, image phase retrieval and reconstructions were performed using TomoPy (an open-source software package developed by ANL) [17]. The ASTRA toolbox was used for tomographic reconstructions [18–21]. Thresholding and analysis was identical to the data from the SSRL.
2. Methods 2.1. Sample preparation The catalyst ink was prepared as detailed in the Supplemental material. Here we provide only salient details. Deionized (DI) water, IPA, Aquivion® solution and Pt/C catalyst powder were mixed with a high shear mixer and then placed on a magnetic stir plate to mix. The inks were then deposited via spray deposition onto a Kapton film decal. The resulting catalyst layer was dried in ambient temperature. A 2 mm2 triangle of electrode on Kapton was cut using a fresh razor blade. The sample was stained by soaking in a saturated cesium chloride solution for 24 h. The sample was then dipped into DI water for 5 s to remove residual Cs and allowed to dry. It was then epoxied to a 0.3 mm diameter pin for imaging. The catalyst ink when dried is composed of 32 wt% Aquivion ionomer, 34 wt% carbon black, and 34 wt% Pt. The loading of the catalyst is roughly 0.31 mgPt cm−2, and the ionomer to carbon I/C ratio is 0.95. Using the densities of the constituent components, a rough estimate for the volume fraction of each phase may be formulated as 54% ionomer, 42% carbon black, and 4% Pt. For the dispersed nano-structured thin-film electrode (dNSTF), the NSTF whiskers were shaved off the liner and mixed with ionomer and carbon black support. Then the ink was coated in a roll-to-roll process onto an inert liner. This technology was developed by 3 M. The whisker
3. Optics theory 3.1. Absorption and phase-contrast modes of imaging in TXM In TXM, images are formed by collecting photons on a detector after they have passed through the sample. The brightness of the image is 39
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proportional to the intensity of light (in W m−2) incident on the detector. Features are discerned by comparing their brightness to the brightness of the surrounding light. Since the brightness of light coming off a feature is less than that of the surrounding light, most reconstruction algorithms invert the color contrast so that regions with low intensity appear brightly in the reconstructed image. There are two types of imaging techniques discussed here that rely on different physical processes to vary the intensity of light: absorption contrast imaging and phase contrast imaging. Presented here is an overview of the two techniques. Detailed derivations of the equations can be found in the Supplemental material. In absorption contrast imaging, the intensity of light is reduced by some of the photon energy being absorbed by the material. The phenomenon is known as attenuation and can be predicted with the BeerLambert law [22,23]:
I = I0 exp(−μl)
(1)
μ = 2k 0 β
(2)
3.2. Two-energy imaging XANES technique can be combined with various forms of TXM (such as X-ray CT). It consists of imaging a sample at multiple photon energies in order to take advantage of absorption edges [25]. Absorption edges are the spikes in the absorption index (and by extension the attenuation and mass-attenuation coefficients) (Fig. 1a) caused by electrons becoming photoexcited at discrete frequencies [23,26]. XANES takes advantage of this phenomenon by scanning at energies above and below an absorption edge and comparing the information to isolate the desired chemical information (e.g. oxidation state of species). In combination with TXM, XANES is used to characterize the oxidation state of energy materials during operation, such as in a study by Weker et al. [25]. 3.2.1. Two energy imaging technique with phase vs. absorption contrastimaging As discussed in the theory section, the brightness of a feature in a TXM image is dependent on its optical properties and its thickness. The thickness here is the total length of material through which X-rays must travel. For instance, if a specimen had two carbon agglomerates, each containing 100 nm of Pt length that were oriented in such a way that a photon would pass through both of them on its way from the source to the detector, the Pt thickness would be 200 nm. Here, the materials of interest are Pt and Cs. Using the electrode loading (0.4 mgPt cm−2 in the case of the dNSTF), the density of Pt and an electrode thickness of 10 μm, the volume fraction of Pt was calculated to be 0.0186. Assuming uniform Pt distribution, the total thickness of Pt is 186 nm. In the case of the conventional catalyst sample, a larger Pt volume fraction was reported (4%), which results in a Pt thickness of about twice that for the dNSTF. In general, the thickness of the Pt ranges from 100 to 600 nm, depending on the Pt loading of the catalyst layer. It should also be noted that since Pt nano-particles (~3 nm in size) and Pt aggregates (< 10 nm [27]) are very small in size, the 24 nm resolution of the nano x-ray CT is a limiting factor. For the purpose of estimating the brightness of Pt in xray images, a thickness range of 0.1–1 μm should provide an accurate representation of the possible thickness observed in nano x-ray CT. The catalyst layer thickness of 10 μm provides a solid upper bound for the possible Cs-stained ionomer thickness. The range of ionomer thicknesses was therefore chosen to be 1–10 μm. In order to choose between absorption and phase contrast imaging, we first consider the x-ray properties of Pt and Cs over the available energy range at beamline 6-2 at SSRL (2.36–17.5 keV), shown in Fig. 2. The L3 absorption edge of both elements is within the available range. Thicknesses of 500 nm Pt and 5 μm Cs were chosen for the intensity calculations as they lie in the middle of the estimated thickness range of each element. Additionally, 5 μm of carbon was considered in order to gauge if the rest of the catalyst material would affect the results. When considering the phase contrast estimations, 5 μm of carbon should be brighter than 500 nm of Pt since the carbon is an order of magnitude thicker than the Pt and the difference in δ is less than an order of magnitude. However, in the catalyst layer, x-rays would not be able to pass through just Pt without also passing through other materials. In order to account for this, the phase contrast Pt estimations were based on a 5 μm total thickness that consisted of 500 nm Pt and 4.5 μm carbon. When we refer to 500 nm of Pt it is 500 nm of Pt and 4.5 μm of carbon. δ and β are independent of thickness and are plotted as Fig. 2a and b, respectively. δ almost continuously decreases (with small spikes near the L3-edge of the material), whereas β shows significant change in value, at the energy of the L3-edge. From Fig. 2c, it is evident that over the 8–12 keV energy range that is most commonly used in nano x-ray CT, Pt and Cs-stained ionomer will show up similarly in a phase-contrast mode for the selected thicknesses. It also shows that it will be difficult to differentiate between carbon and Pt and Cs in this range. From Fig. 2c, it is difficult to
where the attenuated intensity I (which is equal to the intensity incident on the detector I = Idetector), is dependent on the incident intensity I0, the thickness of the material l, and the attenuation coefficient μ. The attenuation coefficient is a function of the wavenumber k0 and the absorption index β, which is a function of photon energy and can be found tabulated in references such as the Lawrence Berkeley National Laboratory (LBNL) X-Ray Data Booklet [24]. Phase contrast imaging relies on the phase shift of the wave that travels through the sample relative to the wave that travels through the environment (such as air for X-ray imaging, where path lines are not isolated by vacuum) around the sample. This phase shift can be predicted using Eq. (3), and the corresponding attenuation drop by Eq. (4) [22].
ϕ = k 0 (1 − δair ) l +
π − k 0 (1 − δ ) l 2
Idetector = I0 + I + 2 I0 I cos(ϕ)
(3) (4)
where Idetector is the intensity of light incident on the detector, I is the intensity of light after passing through the sample (calculated using the Beer-Lambert Law (1)), I0 is the intensity of light that passed around the sample (assuming no attenuation from the air), ϕ is the phase shift in radians, l is the thickness of the material, k0 is the wavenumber, and δ is the refractive index decrement. δ can be found in tabulated form along with β [24]. It should be noted that the relationship between the calculated attenuation of an object and its brightness in the reconstructed image might not be linear, as the contrast of the image must be adjusted in order to be seen with the human eye. X-ray absorption near edge spectroscopy (XANES), on the other hand, relies on exact values of the intensity incident upon the detector. Since the image brightness is proportional to the difference in intensity between the light that passed through the sample and the light that passed around the sample, it is convenient to define a term called the intensity drop:
Idrop = Iaroundsample − Ithroughsample
(5)
for which a higher value will correspond to a brighter feature in the reconstructed image. Normalizing the intensity drop on a 0 to 1 scale by dividing both sides by Iaroundsample provides a convenient way to express the relative brightness of materials as a function of photon energy and thickness. It should be noted that for absorption contrast imaging, Iaroundsample = I0 however for phase contrast imaging Iaroundsample = 4I0 since the phase ring superimposes the incident waves. Two in-phase waves of intensity I0 will have an intensity of 4I0 when superimposed by Eq. (4). Fig. 1 shows several optical properties for Pt of various thicknesses. Normalized intensity drop increases non-uniformly for both imaging types as Pt thickness increases. 40
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Fig. 1. Optical properties of Pt of logarithmically spaced thicknesses from 10 nm to 100 nm over a range of energies pertinent to nano X-ray TXM a) attenuation coefficient, b) phase shift c) normalized intensity drop in absorption contrast d) normalized intensity drop in phase contrast.
Fig. 2. Optical properties of Pt (blue), Cs (red) and carbon (green) over the available energy range at beamline 6-2 at SSRL. a) Refractive index decrement b) absorption index with the L3 edges labeled. Normalized intensity drop of Pt (500 nm Pt and 4.5 μm carbon), 5 μm Cs and 5 μm carbon in phase contrast (c) and absorption contrast (d). Lower values of intensity provide higher contrast to the surrounding light and correspond to brighter features on the reconstructed image. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
41
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materials, such as carbon well and hence is well suited to overall represent the sample (Fig. 4a). According to our theoretical calculations, the phase-contrast image should show in decreasing order of brightness: Pt, carbon, Cs, and void space (Fig. 2c). The calculated brightness differences are small compared to those in absorption-contrast imaging. Additionally, these calculations are highly dependent on the estimated material thicknesses, and small variations can change the order of the above list. Furthermore, Zernike's phase-contrast method is prone to light leaking onto the phase ring as detailed in the Supplementary material. This leaked light causes halo artifacts surrounding features, which adds further uncertainty to the identity of materials in the phase contrast image [28,29]. Despite the uncertainty in the identity of bright features, phase-contrast imaging is very good for distinguishing between solid features and void space, as all solid features regardless of density will show up brightly compared to the dark background. The use of a local thresholding algorithm prevents the bright Pt from overshadowing the less bright carbon (Fig. 4b) [30]. The absorption contrast image is best fit for visualizing bright features such as Pt and Cs stained ionomer (Fig. 4c). Since they have the highest attenuation coefficient, the brightest features in the image are Pt. The threshold is set manually based on the suggested threshold value from Otsu's method and a rough estimate of the predicted volume fraction based on the Wh/S and the densities of the constituent materials (Fig. 4d). The same procedure is repeated for the ionomer. The ionomer is easier to threshold since all of the bright features in the image are either Pt or Cs stained ionomer, making them easy to distinguish from the dark carbon. To separate the Pt from the ionomer, the Pt image (Fig. 4d) is subtracted from the Pt/ionomer image to leave just the ionomer (Fig. 4e). Finally, in order to present a visual representation of the ionomer distribution, the ionomer image is converted to an outline and overlain on the grayscale image (Fig. 4f). The method presented here to threshold the Pt and Cs stained ionomer in the absorption contrast image is educated guesswork. As seen in Fig. S5, Supplementary material, the histogram of the absorption contrast image shows no local brightness peaks that can be used to differentiate between Pt and Cs stained ionomer. The selected thresholds are therefore arbitrary and may not be consistent across samples. This will severely affect the results and highlights the need for a more accurate way to differentiate between Pt and Cs stained ionomer.
choose two energies where normalized phase intensity drops will be significantly different for Pt and Cs. In phase-contrast mode, the energy must be calibrated precisely, as if it is off by even a small amount (10 eV), the narrow energy spike will be missed and the image will be identical to the reference image (away-from-spike). Another problem with differentiating between Pt and Cs in phase-contrast is that the carbon will be brighter than the Pt and Cs at energies above 6 keV, making thresholding difficult. From Fig. 2d there is a 10% difference in normalized detected intensity from absorption-contrast imaging near the Pt L3 edge at 11.56 keV. A larger intensity difference is observed for the Cs L3 edge at 5.01 keV, however for beamline hardware reasons imaging at this energy is more difficult. 3.2.2. Identifying imaging window Since the attenuation of an object is dependent equally on the attenuation coefficient and the thickness of the material (Beer-Lambert law), the brightness changes that two-energy imaging relies on only exist within a certain material thickness range. The intensity drop for Cs must be greater than that for Pt below the edge and less than that of Pt above the edge. This will result in Cs being brighter than Pt below the edge and Pt being brighter than Cs above the edge. Eq. (5) describes this relationship mathematically.
exp(−μPt11.7keV lPt ) < exp(−μCs lCs ) < exp(−μPt11.5keV lPt )
(6)
where μ is the linear attenuation coefficient and l is the material thickness. Since the attenuation coefficient of Cs does not change drastically between 11.5 and 11.7 keV, the average attenuation coefficient over that range is used to simplify the equation. If the thickness of Pt or Cs is averaged across the entire sample, then it can be expressed as a function of the volume fraction of that phase
lPt = t ∗ VFPt
(7)
where t is the sample thickness and VF is the volume fraction (the same holds true for Cs). Eq. (6) can be substituted into Eq. (5) and plotted for a sample thickness of 10 μm. The shaded region in Fig. 3 shows the volume fraction range where this inequality holds. 4. Results/discussion 4.1. Single energy imaging with phase and absorption contrast
4.2. Separating Pt from Cs by two-energy imaging
As noted in the Experimental Section the dNSTF electrode was imaged in both absorption and phase-contrast modes at a photon energy of 8 keV. Fig. 4 shows the resulting grey-scale cross-section tomographs and thresholded images. The phase-contrast tomograph captures soft
The use of two-energy imaging results in two reconstructed images for conventional Pt/C catalyst layer. The high-energy (11.7 keV) scan shows Pt and Cs as bright (Fig. 5b), whereas the low-energy (11.5 keV) scan shows Cs only as bright (Fig. 5a). While the 11.5 keV scan does still show Pt, it is much darker than in the 11.7 keV scan and can be excluded by setting the threshold value correctly. The sample was measured to be 4.0 μm thick. Using that thickness and the volume fractions of Pt and Cs in Eq. (5) validates the use of two-energy imaging in the case of this material. The Pt is brighter than the Cs in the 11.7 keV image, and the Cs is brighter in the 11.5 keV image. This means that the subtracted image will show Pt only (Fig. 5c). The salt and pepper noise was eliminated with the Despeckle operation in ImageJ, which is a 3 × 3 median filter that replaces each pixel with the median value in its 3 × 3 neighborhood [14]. Fig. 5d–f shows the thresholded tomographs of the images represented by Fig. 5a–c, respectively. From the thresholded tomographs, it is more evident that Pt is a minor phase, and that most of the bright pixels correspond to ionomer phase (Cs).
Fig. 3. Relationship between the volume fractions of Pt and Cs for a 10 μm thick sample. The range of volume fractions where Cs is brighter below the Pt L3 edge and Pt is brighter above the edge is shown in yellow. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
4.3. Volume rendering and morphology quantification Fig. 6 shows a three-dimensional volume rendering of the Pt (green) and ionomer (blue) and the distribution of the two throughout the 42
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Fig. 4. Thresholding procedure a) phase contrast image b) thresholded phase contrast image (solid phase white) c) absorption contrast image d) thresholded absorption contrast image (platinum white) e) thresholded absorption contrast image (ionomer white) f) absorption contrast image with ionomer highlighted. dNSTF catalyst layer, Wh/S = 10.0, 3 M 825 EW ionomer with I/S = 0.8, 0.4 mgPt cm−2.
morphological properties of the catalyst layer imaged. Volume fraction, tortuosity, and size distribution are the parameters chosen to describe the sample morphology. Table 1 shows that neglecting to separate Pt from ionomer when performing these calculations results in overestimating the volume fraction and average size of the ionomer and underestimating the tortuosity factor. Supplementary material, Fig. S7 shows the ionomer size distributions and tortuosity factors. Ionomer size, when separated from Pt is 48.6 nm, whereas when combined with Pt it is 66.2 nm. No connectivity between Pt particles was observed and hence the tortuosity factor was not defined. Although well distributed, the connectivity of ionomer is not as high, a value of 8.3. This value is based on separating Pt and Cs, however tortuosity factor is much lower (value of 3.0) for combined Pt and Cs domain, which can result in significant error in morphology interpretation. Comparing the results in Table 1 to the predictions (shown in the column 5 of Table 1), the volume fraction of Pt (4.1%) is almost exactly
sample. Observing by eye, the two phases are well distributed within the electrode. This uniformity can be quantified by comparing the volume fraction of Pt or ionomer for each cross section along an axis and finding the standard deviation of those values. Averaging the standard deviations of the volume fractions of the three coordinate directions gives values of 0.01 and 0.06 for Pt and ionomer respectively. These values are acceptable compared to the respective volume fractions of 0.04 and 0.30, which indicates that spatial variations in volume fraction are not high. The platinum here is also in good contact with the ionomer, as shown in Fig. 6d. The performance of this type of electrode was reported by Garsany et al. [31], when compared to electrodes with conventional ionomer, the electrodes with low-equivalent weight ionomer, imaged here showed improved performance at high current densities across variety of conditions. This might be due to the welldistributed ionomer as shown in this study. Further quantitative analysis is performed to understand the 43
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Fig. 5. a) 11.7 keV image b) 11.5 keV image c) result of subtracting (b) from (a) d–f) thresholded images of respective scans. The bright spot in (a) could be either Pt or Cs. By subtracting (b) which Cs only, (c) shows Pt only. The grayscale images (a–c) were filtered using a two iteration 3 × 3 median filter. 50 wt% Pt/CB, with Aquivion® ionomer, I/C = 0.95, 0.31 mgPt cm−2.
Ni/C catalyst is shown imaged at near the K-edge. The disadvantage of the method is that both density and thickness of the material play role, and sometimes (Fig. 3) one has to understand the composition of two phases well to ensure that the resulting brightness is consistent with the expectations. The method is insensitive to very small volume fractions of material, and to well-dispersed nano-particles, as they will be below the nano-CT resolution. The other challenge is that the Pt L3-edge is at the boundary of the optical elements losing their efficiency. Thus not every beamtime has this sufficiently broad energy range. XANES imaging, which is an enhanced two-energy imaging approach can provide similar information, in addition to the oxidation state of the material. The two energy-imaging is relatively not time-consuming, as only two scans are needed, whereas XANES tomography can take many hours.
equal to the predicted (4%). Note that the volume fraction of Pt with single energy imaging will be zero, as the method attributes all the bright features to combined phase (Cs and Pt). The volume fraction of ionomer (30%) is lower than predicted (54%). It is possible that not all ionomer domains were stained during sample preparation, as Cs staining procedure is highly sensitive. If the sample is oversaturated with Cs and not dipped in DI water for sufficient time, large Cs crystals form on the surface of the material as seen in Fig. S4, Supplementary material. These crystals are very bright, due to the large thickness of the crystals, and they overshadow all other features in the image. In order to combat this, the sample is rinsed with DI water to remove excess Cs. An alternative explanation is that the nano-CT imaging does not capture the thin-film ionomers that surround the carbon agglomerates and are thinner than the resolution of the nano-CT (which is ~24 nm/voxel for SSRL beamline). Overall, the two energy imaging technique is based on absorption contrast and utilizes X-ray absorption edges of elements to dim (below the edge) or enhance (above the edge) the element of interest. This method is very well fit for elements that have very similar density (such as Pt and Cs). For novel catalysts such as Pt-alloys (Co, Ni etc.), again imaging about Pt absorption edge will separate Pt and ionomer phases. To separate Pt and Ni elements, imaging above and below the Ni edge has to be performed. In the Supplementary material, an example of a
5. Conclusion X-ray computed tomography is a non-intrusive method based on transmission x-ray microscopy (TXM) technique to image samples in three-dimensions. Here, we present the single energy imaging results of a Cs-stained electrode in absorption and phase-contrast imaging. From the phase-contrast imaging, it is possible to separate the carbon material from the void, whereas absorption-contrast imaging is a better fit to separate Pt and Cs from the rest of the phases. Here, for the first time, 44
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Fig. 6. Volume renderings of a) Platinum b) ionomer c) Platinum and ionomer. d) Cross-section image with Pt (green) and ionomer (blue) highlighted. 50 wt% Pt/CB, with Aquivion® ionomer, I/C = 0.95, 0.31 mgPt cm−2. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Table 1 Properties of scans at the two energies. The reported tortuosity is averaged across the three coordinate directions. The calculated volume fractions are reported. The standard deviations are reported for some of the values too. Scan
11.7 keV
11.5 keV
Difference
Calculated (from densities and composition)
Visible features Volume fraction above threshold
Platinum and cesium 0.463 ± 0.06
Cesium only (ionomer) 0.301 ± 0.06
Platinum only 0.041 ± 0.01
Average tortuosity factor Average size, radius
3.0 ± 0.7 66.2 nm
8.3 ± 4.6 48.6 nm
N/A 44.1 nm
All phases Ionomer: 0.54 Platinum: 0.04 N/A N/A
under Award Number DE-EE0007270. Use of the Stanford Synchrotron Radiation Lightsource at SLAC National Accelerator Laboratory is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Contract No. DE-AC02-76SF00515. This research used resources of the Advanced Photon Source, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DEAC02-06CH11357. We thank Dr. Yannick Garsany and Dr. Karen Swider-Lyons, Naval Research Laboratory for Pt/C catalyst layer preparation. We thank Dr. Vincent De Andrade and Dr. Johanna Nelson Weker for the beamtime support at the APS and SSRL, respectively.
we present a method for imaging the ionomer distribution in Pt-containing electrodes to separate Pt from Cs-stained ionomer. The method is based on two-energy imaging: below and above the absorption edge of the element (here we chose Pt). We provide a theoretical analysis to prove that for given length-scales of Pt and Cs-stained ionomer, the twoenergy method is valid, as light intensity detected by the detector depends on both the attenuation coefficient and the thickness of the material. By imaging the sample below and above the L3 absorption edge of Pt, the Pt phase shows up darker than Cs and brighter than Cs below and above the edge respectively. With this method, we quantify several important properties of the ionomer morphology within the electrode, such as the volume fraction and the tortuosity. For the sample studied, the ionomer distribution was uniform and Pt was in contact with the ionomer. The ionomer volume fraction was lower (30%) than that predicted by ink composition calculations (54%), which is due to incomplete Cs-wetting of the ionomer or due to insensitivity of the method to the thin films. Furthermore, the work presents the derivations and guidelines for the selection of absorption or phase contrast imaging. Materials with a high absorption index should be imaged using absorption contrast, whereas those with a low absorption index should be imaged in phase contrast. Predicting the relative brightness of objects in an image relies on both the x-ray properties of the material and its thickness and requires complex mathematical expressions to resolve the dependency on both that are also presented in this work.
Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ssi.2019.02.017. References [1] M.K. Debe, Electrocatalyst approaches and challenges for automotive fuel cells, Nature 486 (7401) (2012) 43–51. [2] A.J. Steinbach, et al., Anode-design strategies for improved performance of polymer-electrolyte fuel cells with ultra-thin electrodes, Joule, 2018. [3] I.V. Zenyuk, P.K. Das, A.Z. Weber, Understanding impacts of catalyst-layer thickness on fuel-cell performance via mathematical modeling, J. Electrochem. Soc. 163 (7) (2016) F691–F703. [4] M. Lopez-Haro, et al., Three-dimensional analysis of Nafion layers in fuel cell electrodes, Nat. Commun. 5 (2014) 5229. [5] A. Kusoglu, A.Z. Weber, New insights into perfluorinated sulfonic-acid ionomers, Chem. Rev. 117 (3) (2017) 987–1104. [6] S. Komini Babu, et al., Resolving electrode Morphology's impact on platinum group
Acknowledgement This material is based upon work supported by the Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE), 45
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[7] [8]
[9] [10] [11] [12] [13]
[14] [15] [16] [17] [18]
[19] D.M. Pelt, et al., Integration of TomoPy and the ASTRA toolbox for advanced processing and reconstruction of tomographic synchrotron data, J. Synchrotron Radiat. 23 (3) (2016) 842–849. [20] F. De Carlo, et al., Scientific data exchange: a schema for HDF5-based storage of raw and analyzed data, J. Synchrotron Radiat. 21 (6) (2014) 1224–1230. [21] V. De Andrade, et al., Nanoscale 3D imaging at the advanced photon source, (2016). [22] M. Born, E. Wolf, Principles of Optics, 7 ed., Cambridge UP, Cambridge, UK, 1959. [23] M. Fox, Optical Properties of Solids, Oxford UP, Oxford, UK, 2001. [24] A. Thompson, et al., L.B.N. Laboratory (Ed.), X-Ray Data Booklet, 2009 (Berkeley, CA). [25] J.N. Weker, M.F. Toney, Emerging in situ and operando nanoscale X-ray imaging techniques for energy storage materials, Adv. Funct. Mater. 25 (11) (2015) 1622–1637. [26] J. Simmons, K. Potter, Optical Materials, Academic Press, San Diego, CA, 2000. [27] A. Honji, et al., Agglomeration of platinum particles supported on carbon in phosphoric acid, J. Electrochem. Soc. 135 (1988) 355–359. [28] A. Tkachuk, et al., X-ray computed tomography in Zernike phase contrast mode at 8 keV with 50-nm resolution using Cu rotating anode X-ray source, Z. Krist. 222 (11/2007) (2007). [29] Z. Yin, T. Kanade, M. Chen, Understanding the phase contrast optics to restore artifact-free microscopy images for segmentation, Med. Image Anal. 16 (5) (2012) 1047–1062. [30] N. Otsu, A. Threshold Selection, Method for gray-level histograms, SPIE Newsroom (1979), https://doi.org/10.1117/2.1201604.006461 (published online 12 May 2016). [31] Y. Garsany, et al., Improving PEMFC performance using short-side-chain lowequivalent-weight PFSA ionomer in the cathode catalyst layer, J. Electrochem. Soc. 165 (5) (2018) F381–F391.
metal-free cathode performance using nano-CT of 3D hierarchical pore and ionomer distribution, ACS Appl. Mater. Interfaces 8 (48) (2016) 32764–32777. S.J. Lee, et al., Effects of Nafion impregnation on performances of PEMFC electrodes, Electrochim. Acta 43 (24) (1998) 3693–3701. I.V. Zenyuk, J. Lee, S. Litster, Modeling ion transport in fuel cell electrodes including water vertical bar electrolyte interfaces and electric double layers, Polymer Electrolyte Fuel Cells 11 41 (1) (2011) 179–188. S. Rieberer, K. Norian, Analytical electron microscopy of Nafion ion exchange membranes, Ultramicroscopy 41 (1–3) (1992) 225–233. C. Lang, et al., Local thickness and composition analysis of TEM lamellae in the FIB, Microelectron. Reliab. 54 (9–10) (2014) 1790–1793. F.C. Cetinbas, et al., Microstructural analysis and transport resistances of low-platinum-loaded PEFC electrodes, J. Electrochem. Soc. 164 (14) (2017) F1596–F1607. A.T. Haug, Novel ionomers and electrode structures for improved PEMFC electrode performance at low PGM loading, Annual Merit Review, 2018 (Washington DC). Y. Liu, et al., TXM-Wizard: a program for advanced data collection and evaluation in full-field transmission X-ray microscopy, J. Synchrotron Radiat. 19 (2) (2012) 281–287. J. Schindelin, et al., Fiji: an open-source platform for biological-image analysis, Nat. Methods 9 (7) (2012) 676–682. S.J. Cooper, et al., TauFactor: an open-source application for calculating tortuosity factors from tomographic data, SoftwareX 5 (2016) 203–210. M. Doube, et al., BoneJ: free and extensible bone image analysis in ImageJ, Bone 47 (6) (2010) 1076–1079. D. Gursoy, et al., TomoPy: a framework for the analysis of synchrotron tomographic data, J. Synchrotron Radiat. 21 (Pt 5) (2014) 1188–1193. D. Gürsoy, et al., TomoPy: a framework for the analysis of synchrotron tomographic data, J. Synchrotron Radiat. 21 (Pt 5) (2014) 1188–1193.
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Solid State Ionics journal homepage: www.elsevier.com/locate/ssi
Imaging ionomer in fuel cell catalyst layers with synchrotron nano transmission x-ray microscopy Stanley J. Normilea, Iryna V. Zenyuka,b, a b
T
⁎
Department of Mechanical Engineering, Tufts University, Medford, MA 02155, USA Department of Chemical and Biomolecular Engineering, National Fuel Cells Research Center, University of California Irvine, Irvine, CA 92617, USA
A R T I C LE I N FO
A B S T R A C T
Keywords: Transmission x-ray microscopy X-ray computed tomography Fuel cells Catalyst layer Ionomer distribution
This work presents a novel characterization method for distinguishing ionomer phase within porous composite catalyst layer. Quantifying ionomer distribution in a catalyst layer of polymer electrolyte fuel cells (PEFCs) is critical to understanding the morphological and transport properties of this key component. Current methods to image ionomer rely on staining it with heavy ions, such as cesium, Cs, to enable detection with hard X-rays, however if the catalyst layer contains electrocatalyst, such as platinum, Pt, then the challenge is to distinguish between Cs-stained ionomer and Pt. These two materials have very similar X-ray attenuation coefficients. Using synchrotron transmission x-ray microscopy (TXM) and two energy imaging, above and below Pt electrocatalyst absorption edge, the ionomer distribution is quantified. The method is applied to a PEFC catalyst layer and compared against the method of single energy imaging, which is not able to separate the two phases.
1. Introduction Polymer electrolyte fuel cells (PEFCs) are a promising alternative to traditional internal combustion engines for automotive applications due to their high efficiency and zero tailpipe emissions [1]. Developing cathode catalyst layers with high electrocatalytic activity and low transport resistance is critical to ensuring high power densities of PEFCs [2,3]. Fast proton transport through the membrane electrode assembly (MEA) of the PEFC is essential, as protons are reactants in the oxygen reduction reaction. The catalyst layer of a state-of-the-art conventional PEFC is prepared as an ink consisting of carbon black, platinum (Pt) nanoparticles, and ionomer. The carbon black acts as an electrocatalyst support material and also as the electron conducting phase, the Pt acts as the electrocatalyst, and the ionomer is both the binder and the electrolyte through which the protons conduct [1,4]. Perfluorinated sulfonic acid ionomers (PFSA) are the most commonly used ionomers in PEFCs due to their exceptionally high ionic conductivity when solvated and their mechanical stability [5]. PFSA ionomers separate into hydrophilic ion-conducting sulfonic acid groups and hydrophobic matrices of polytetrafluoroethylene (PTFE) domains. It is essential that the ionomer be uniformly distributed within the catalyst layer as ionomer provides a path for the proton reactants to reach the catalyst sites on the surface of the platinum nanoparticles [4]. Experiments have corroborated this, showing that ionomer loading and distribution both
⁎
significantly affect PEFC performance [6–8]. Given the importance of ionomer distribution, there have been several attempts to quantify it using imagining techniques. Both electrons and X-rays have been used to probe ionomer distribution within the PEFC catalyst layer. Ionomer has a low X-ray absorption index, so it is not visible in X-ray absorption contrast imaging. It also has a refractive index decrement that is lower than both Pt and carbon, which means that it will be the dimmest feature on a phase-contrast image. A solution to this imaging problem is to stain (or ion-exchange) the ionomer with heavier elements, such as cesium (Cs) ions. Cs has a high Xray absorption index and therefore it is easy to detect in X-ray absorption-contrast imaging. Lopez-Haro et al. [4] used the technique of ionomer staining with high-angle annular dark-filed scanning transmission electron microscopy (HAADF-STEM). Differentiating between Pt nanoparticles and Cs-stained ionomer in their images is very difficult, since both features would give high absorption contrast compared to the carbon black support. Their solution was to prepare a catalyst ink that did not contain any Pt to have all bright features attributed to Csstained ionomer. Using this technique, they were able to show that only 60–76% of the ionomer in the catalyst ink uniformly covers the carbon black (CB) support, however they were unable to see how the ionomer interacts with the Pt nanoparticles as their catalyst layer was made only with CB and ionomer [4]. Others, such as Rieberer et al., have also used Cs staining with TEM imaging [9]. Scanning electron microscopy (SEM)
Corresponding author at: Department of Chemical and Biomolecular Engineering, University of California Irvine, Irvine, CA 92617, USA. E-mail address: [email protected] (I.V. Zenyuk).
https://doi.org/10.1016/j.ssi.2019.02.017 Received 14 September 2018; Received in revised form 4 February 2019; Accepted 16 February 2019 0167-2738/ © 2019 Elsevier B.V. All rights reserved.
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to support ratio (Wh/S) was 10.0, the ionomer (3 M 825 equivalent weight (EW) PFSA) to support (I/S) ratio was 0.80. The final Pt loading of the electrode was 0.4 mgPt cm−2. High loading and relatively large dimensions of whiskers (40 nm by 0.5 μm) ensured sufficient X-ray attenuation and good visibility, given the resolution limitations of the nano X-ray CT. More details on the fabrication of the dNSTF electrodes can be found in Ref. [12]. Ionomer staining was performed by the procedure described above. It is important to note that samples prepared on an inert substrate, such as Kapton, are more stable during nano X-ray CT imaging than those deposited on a membrane. X-ray damage to membranes during scans can be significant, causing sample to move during the scan, introducing artifacts during the reconstruction procedure.
is another common way to study ionomer distribution. The drawback of the technique is that it does not provide 3D information, except in the case of focused ion beam SEM (FIB-SEM), which is a destructive technique. While TEM imaging is useful for visualizing ionomer in 3D, it has a large disadvantage in that the sample must be very thin, on the order of 100 nm [10]. Another disadvantage of electron beams is that the soft ionomer phase is highly susceptible to electron beam damage. Compensating for this requires cryo-chambers and other difficult samplehandling techniques. Transmission X-ray microscopy (TXM) and its three-dimensional variation, X-ray computed tomography (CT), are ideal for imaging ionomer within the catalyst layer, as X-rays at higher energies interact less with the ionomer than do electrons and therefore cause significantly less damage. X-ray imaging techniques have larger fields of view and lower resolutions than electron-imaging techniques. The ~80 μm field of view of nano X-ray CT is ideal for imaging the bulk ionomer phase along the entire thickness of the catalyst layer; however its ~30 nm resolution is not fine enough to image the thin-film ionomer that covers agglomerates within the catalyst layer. X-ray CT is also nondestructive, which makes it much more attractive than FIB-SEM. Komini Babu et al. [6] demonstrated that Cs staining is an effective method for visualizing ionomer in platinum group metal (PGM) free electrodes using X-ray CT. They avoided the aforementioned challenge of distinguishing between Cs and Pt by using PGM-free electrodes. They found that the ionomer distribution is dependent on loading, with 50 wt % ionomer distributed uniformly and 35 wt% forming large, dense agglomerates. Recently, Cetinbas et al. [11] used absorption contrast X-ray CT to image Cs-stained low-loaded PGM catalyst layers. They neglected to differentiate between the Cs-stained ionomer and the Pt catalyst, both of which appear bright in absorption-contrast imaging. They claimed that the relative scarcity of catalyst in low-PGM catalyst layers (0.092 mgPt cm−2) implies that the fraction of bright objects in their images that is Pt is relatively small and therefore all bright objects can be assumed to be Cs-stained ionomer. While this may hold true for lowloaded Pt electrodes, there is a need to develop a higher fidelity imaging approach, where Pt loading is not a concern. Here, we present an approach of two-energy imaging, where the electrode is imaged below and above the absorption L3-edge of Pt. To the best of the authors' knowledge, this is the first use of two-energy imaging for the separation of Pt from ionomer in fuel cell catalyst layers.
2.2. Imaging procedure The two energy imaging was performed at beamline 6-2 at the Stanford Synchrotron Radiation Lightsource (SSRL) at SLAC National Accelerator Laboratory (SLAC). For each scan, the sample was exposed 180 times for 1 s each as the sample was rotated from 0 to 180° about the axis formed by the pin on which it was mounted. The sample was scanned two times, once at a photon energy of 11.5 keV and again at 11.7 keV. These energies were chosen to take advantage of the L3 absorption edge of platinum as shown in Fig. 2b. At 11.5 keV, the mass attenuation coefficients of Pt and Cs are 80.6 and 136 cm2 g−1 respectively. At 11.7 keV, they are 191 and 132 cm2 g−1 respectively. The imaging for the single energy experiment was performed at Beamtline 32-ID at the Advanced Photon Source (APS) at Argonne National Laboratory. Monochromatic X-rays illuminate the beam shaping condenser, then sample, a Fresnel zone plate (FZ), and are collected at an imaging detector. Gratings of 60 nm for FZ plates were used to achieve resolution of 60 nm. The FOV was approximately 75 μm × 75 μm and the scan-time was 20 min. 1500 projections were recorded with 1 s exposure per projection. Zernike phase contrast was used to detect carbon by placing a phase-ring in the back-focal plane of the ZPs. The phase-ring was removed from the path of x-rays for absorption-contrast imaging. 2.3. Image processing The images collected at SSRL were reconstructed and aligned using TXM Wizard software [13]. The reconstruction produced images that were 15 × 16 × 24 μm with a voxel size of 24 nm. Once reconstructed, they were cropped using the Fiji distribution of ImageJ [14] to a size of 2.4 × 3.9 × 8.0 μm so that only a pristine section of sample was visible. The 11.5 keV image was then subtracted from the 11.7 keV image. Once the subtraction was complete, all three images were filtered using a median filter and thresholded using a combination of ImageJ's default thresholding algorithm and manual adjustments as detailed in the discussion below. The thresholded images were then analyzed to find the volume fraction and tortuosity factor using Tau Factor [15], and the size distribution using the BoneJ plugin in ImageJ [16]. Finally, the images were volume rendered using Avizo (FEI Visualization Sciences Group, Berlin). For the APS data, image phase retrieval and reconstructions were performed using TomoPy (an open-source software package developed by ANL) [17]. The ASTRA toolbox was used for tomographic reconstructions [18–21]. Thresholding and analysis was identical to the data from the SSRL.
2. Methods 2.1. Sample preparation The catalyst ink was prepared as detailed in the Supplemental material. Here we provide only salient details. Deionized (DI) water, IPA, Aquivion® solution and Pt/C catalyst powder were mixed with a high shear mixer and then placed on a magnetic stir plate to mix. The inks were then deposited via spray deposition onto a Kapton film decal. The resulting catalyst layer was dried in ambient temperature. A 2 mm2 triangle of electrode on Kapton was cut using a fresh razor blade. The sample was stained by soaking in a saturated cesium chloride solution for 24 h. The sample was then dipped into DI water for 5 s to remove residual Cs and allowed to dry. It was then epoxied to a 0.3 mm diameter pin for imaging. The catalyst ink when dried is composed of 32 wt% Aquivion ionomer, 34 wt% carbon black, and 34 wt% Pt. The loading of the catalyst is roughly 0.31 mgPt cm−2, and the ionomer to carbon I/C ratio is 0.95. Using the densities of the constituent components, a rough estimate for the volume fraction of each phase may be formulated as 54% ionomer, 42% carbon black, and 4% Pt. For the dispersed nano-structured thin-film electrode (dNSTF), the NSTF whiskers were shaved off the liner and mixed with ionomer and carbon black support. Then the ink was coated in a roll-to-roll process onto an inert liner. This technology was developed by 3 M. The whisker
3. Optics theory 3.1. Absorption and phase-contrast modes of imaging in TXM In TXM, images are formed by collecting photons on a detector after they have passed through the sample. The brightness of the image is 39
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proportional to the intensity of light (in W m−2) incident on the detector. Features are discerned by comparing their brightness to the brightness of the surrounding light. Since the brightness of light coming off a feature is less than that of the surrounding light, most reconstruction algorithms invert the color contrast so that regions with low intensity appear brightly in the reconstructed image. There are two types of imaging techniques discussed here that rely on different physical processes to vary the intensity of light: absorption contrast imaging and phase contrast imaging. Presented here is an overview of the two techniques. Detailed derivations of the equations can be found in the Supplemental material. In absorption contrast imaging, the intensity of light is reduced by some of the photon energy being absorbed by the material. The phenomenon is known as attenuation and can be predicted with the BeerLambert law [22,23]:
I = I0 exp(−μl)
(1)
μ = 2k 0 β
(2)
3.2. Two-energy imaging XANES technique can be combined with various forms of TXM (such as X-ray CT). It consists of imaging a sample at multiple photon energies in order to take advantage of absorption edges [25]. Absorption edges are the spikes in the absorption index (and by extension the attenuation and mass-attenuation coefficients) (Fig. 1a) caused by electrons becoming photoexcited at discrete frequencies [23,26]. XANES takes advantage of this phenomenon by scanning at energies above and below an absorption edge and comparing the information to isolate the desired chemical information (e.g. oxidation state of species). In combination with TXM, XANES is used to characterize the oxidation state of energy materials during operation, such as in a study by Weker et al. [25]. 3.2.1. Two energy imaging technique with phase vs. absorption contrastimaging As discussed in the theory section, the brightness of a feature in a TXM image is dependent on its optical properties and its thickness. The thickness here is the total length of material through which X-rays must travel. For instance, if a specimen had two carbon agglomerates, each containing 100 nm of Pt length that were oriented in such a way that a photon would pass through both of them on its way from the source to the detector, the Pt thickness would be 200 nm. Here, the materials of interest are Pt and Cs. Using the electrode loading (0.4 mgPt cm−2 in the case of the dNSTF), the density of Pt and an electrode thickness of 10 μm, the volume fraction of Pt was calculated to be 0.0186. Assuming uniform Pt distribution, the total thickness of Pt is 186 nm. In the case of the conventional catalyst sample, a larger Pt volume fraction was reported (4%), which results in a Pt thickness of about twice that for the dNSTF. In general, the thickness of the Pt ranges from 100 to 600 nm, depending on the Pt loading of the catalyst layer. It should also be noted that since Pt nano-particles (~3 nm in size) and Pt aggregates (< 10 nm [27]) are very small in size, the 24 nm resolution of the nano x-ray CT is a limiting factor. For the purpose of estimating the brightness of Pt in xray images, a thickness range of 0.1–1 μm should provide an accurate representation of the possible thickness observed in nano x-ray CT. The catalyst layer thickness of 10 μm provides a solid upper bound for the possible Cs-stained ionomer thickness. The range of ionomer thicknesses was therefore chosen to be 1–10 μm. In order to choose between absorption and phase contrast imaging, we first consider the x-ray properties of Pt and Cs over the available energy range at beamline 6-2 at SSRL (2.36–17.5 keV), shown in Fig. 2. The L3 absorption edge of both elements is within the available range. Thicknesses of 500 nm Pt and 5 μm Cs were chosen for the intensity calculations as they lie in the middle of the estimated thickness range of each element. Additionally, 5 μm of carbon was considered in order to gauge if the rest of the catalyst material would affect the results. When considering the phase contrast estimations, 5 μm of carbon should be brighter than 500 nm of Pt since the carbon is an order of magnitude thicker than the Pt and the difference in δ is less than an order of magnitude. However, in the catalyst layer, x-rays would not be able to pass through just Pt without also passing through other materials. In order to account for this, the phase contrast Pt estimations were based on a 5 μm total thickness that consisted of 500 nm Pt and 4.5 μm carbon. When we refer to 500 nm of Pt it is 500 nm of Pt and 4.5 μm of carbon. δ and β are independent of thickness and are plotted as Fig. 2a and b, respectively. δ almost continuously decreases (with small spikes near the L3-edge of the material), whereas β shows significant change in value, at the energy of the L3-edge. From Fig. 2c, it is evident that over the 8–12 keV energy range that is most commonly used in nano x-ray CT, Pt and Cs-stained ionomer will show up similarly in a phase-contrast mode for the selected thicknesses. It also shows that it will be difficult to differentiate between carbon and Pt and Cs in this range. From Fig. 2c, it is difficult to
where the attenuated intensity I (which is equal to the intensity incident on the detector I = Idetector), is dependent on the incident intensity I0, the thickness of the material l, and the attenuation coefficient μ. The attenuation coefficient is a function of the wavenumber k0 and the absorption index β, which is a function of photon energy and can be found tabulated in references such as the Lawrence Berkeley National Laboratory (LBNL) X-Ray Data Booklet [24]. Phase contrast imaging relies on the phase shift of the wave that travels through the sample relative to the wave that travels through the environment (such as air for X-ray imaging, where path lines are not isolated by vacuum) around the sample. This phase shift can be predicted using Eq. (3), and the corresponding attenuation drop by Eq. (4) [22].
ϕ = k 0 (1 − δair ) l +
π − k 0 (1 − δ ) l 2
Idetector = I0 + I + 2 I0 I cos(ϕ)
(3) (4)
where Idetector is the intensity of light incident on the detector, I is the intensity of light after passing through the sample (calculated using the Beer-Lambert Law (1)), I0 is the intensity of light that passed around the sample (assuming no attenuation from the air), ϕ is the phase shift in radians, l is the thickness of the material, k0 is the wavenumber, and δ is the refractive index decrement. δ can be found in tabulated form along with β [24]. It should be noted that the relationship between the calculated attenuation of an object and its brightness in the reconstructed image might not be linear, as the contrast of the image must be adjusted in order to be seen with the human eye. X-ray absorption near edge spectroscopy (XANES), on the other hand, relies on exact values of the intensity incident upon the detector. Since the image brightness is proportional to the difference in intensity between the light that passed through the sample and the light that passed around the sample, it is convenient to define a term called the intensity drop:
Idrop = Iaroundsample − Ithroughsample
(5)
for which a higher value will correspond to a brighter feature in the reconstructed image. Normalizing the intensity drop on a 0 to 1 scale by dividing both sides by Iaroundsample provides a convenient way to express the relative brightness of materials as a function of photon energy and thickness. It should be noted that for absorption contrast imaging, Iaroundsample = I0 however for phase contrast imaging Iaroundsample = 4I0 since the phase ring superimposes the incident waves. Two in-phase waves of intensity I0 will have an intensity of 4I0 when superimposed by Eq. (4). Fig. 1 shows several optical properties for Pt of various thicknesses. Normalized intensity drop increases non-uniformly for both imaging types as Pt thickness increases. 40
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Fig. 1. Optical properties of Pt of logarithmically spaced thicknesses from 10 nm to 100 nm over a range of energies pertinent to nano X-ray TXM a) attenuation coefficient, b) phase shift c) normalized intensity drop in absorption contrast d) normalized intensity drop in phase contrast.
Fig. 2. Optical properties of Pt (blue), Cs (red) and carbon (green) over the available energy range at beamline 6-2 at SSRL. a) Refractive index decrement b) absorption index with the L3 edges labeled. Normalized intensity drop of Pt (500 nm Pt and 4.5 μm carbon), 5 μm Cs and 5 μm carbon in phase contrast (c) and absorption contrast (d). Lower values of intensity provide higher contrast to the surrounding light and correspond to brighter features on the reconstructed image. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
41
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materials, such as carbon well and hence is well suited to overall represent the sample (Fig. 4a). According to our theoretical calculations, the phase-contrast image should show in decreasing order of brightness: Pt, carbon, Cs, and void space (Fig. 2c). The calculated brightness differences are small compared to those in absorption-contrast imaging. Additionally, these calculations are highly dependent on the estimated material thicknesses, and small variations can change the order of the above list. Furthermore, Zernike's phase-contrast method is prone to light leaking onto the phase ring as detailed in the Supplementary material. This leaked light causes halo artifacts surrounding features, which adds further uncertainty to the identity of materials in the phase contrast image [28,29]. Despite the uncertainty in the identity of bright features, phase-contrast imaging is very good for distinguishing between solid features and void space, as all solid features regardless of density will show up brightly compared to the dark background. The use of a local thresholding algorithm prevents the bright Pt from overshadowing the less bright carbon (Fig. 4b) [30]. The absorption contrast image is best fit for visualizing bright features such as Pt and Cs stained ionomer (Fig. 4c). Since they have the highest attenuation coefficient, the brightest features in the image are Pt. The threshold is set manually based on the suggested threshold value from Otsu's method and a rough estimate of the predicted volume fraction based on the Wh/S and the densities of the constituent materials (Fig. 4d). The same procedure is repeated for the ionomer. The ionomer is easier to threshold since all of the bright features in the image are either Pt or Cs stained ionomer, making them easy to distinguish from the dark carbon. To separate the Pt from the ionomer, the Pt image (Fig. 4d) is subtracted from the Pt/ionomer image to leave just the ionomer (Fig. 4e). Finally, in order to present a visual representation of the ionomer distribution, the ionomer image is converted to an outline and overlain on the grayscale image (Fig. 4f). The method presented here to threshold the Pt and Cs stained ionomer in the absorption contrast image is educated guesswork. As seen in Fig. S5, Supplementary material, the histogram of the absorption contrast image shows no local brightness peaks that can be used to differentiate between Pt and Cs stained ionomer. The selected thresholds are therefore arbitrary and may not be consistent across samples. This will severely affect the results and highlights the need for a more accurate way to differentiate between Pt and Cs stained ionomer.
choose two energies where normalized phase intensity drops will be significantly different for Pt and Cs. In phase-contrast mode, the energy must be calibrated precisely, as if it is off by even a small amount (10 eV), the narrow energy spike will be missed and the image will be identical to the reference image (away-from-spike). Another problem with differentiating between Pt and Cs in phase-contrast is that the carbon will be brighter than the Pt and Cs at energies above 6 keV, making thresholding difficult. From Fig. 2d there is a 10% difference in normalized detected intensity from absorption-contrast imaging near the Pt L3 edge at 11.56 keV. A larger intensity difference is observed for the Cs L3 edge at 5.01 keV, however for beamline hardware reasons imaging at this energy is more difficult. 3.2.2. Identifying imaging window Since the attenuation of an object is dependent equally on the attenuation coefficient and the thickness of the material (Beer-Lambert law), the brightness changes that two-energy imaging relies on only exist within a certain material thickness range. The intensity drop for Cs must be greater than that for Pt below the edge and less than that of Pt above the edge. This will result in Cs being brighter than Pt below the edge and Pt being brighter than Cs above the edge. Eq. (5) describes this relationship mathematically.
exp(−μPt11.7keV lPt ) < exp(−μCs lCs ) < exp(−μPt11.5keV lPt )
(6)
where μ is the linear attenuation coefficient and l is the material thickness. Since the attenuation coefficient of Cs does not change drastically between 11.5 and 11.7 keV, the average attenuation coefficient over that range is used to simplify the equation. If the thickness of Pt or Cs is averaged across the entire sample, then it can be expressed as a function of the volume fraction of that phase
lPt = t ∗ VFPt
(7)
where t is the sample thickness and VF is the volume fraction (the same holds true for Cs). Eq. (6) can be substituted into Eq. (5) and plotted for a sample thickness of 10 μm. The shaded region in Fig. 3 shows the volume fraction range where this inequality holds. 4. Results/discussion 4.1. Single energy imaging with phase and absorption contrast
4.2. Separating Pt from Cs by two-energy imaging
As noted in the Experimental Section the dNSTF electrode was imaged in both absorption and phase-contrast modes at a photon energy of 8 keV. Fig. 4 shows the resulting grey-scale cross-section tomographs and thresholded images. The phase-contrast tomograph captures soft
The use of two-energy imaging results in two reconstructed images for conventional Pt/C catalyst layer. The high-energy (11.7 keV) scan shows Pt and Cs as bright (Fig. 5b), whereas the low-energy (11.5 keV) scan shows Cs only as bright (Fig. 5a). While the 11.5 keV scan does still show Pt, it is much darker than in the 11.7 keV scan and can be excluded by setting the threshold value correctly. The sample was measured to be 4.0 μm thick. Using that thickness and the volume fractions of Pt and Cs in Eq. (5) validates the use of two-energy imaging in the case of this material. The Pt is brighter than the Cs in the 11.7 keV image, and the Cs is brighter in the 11.5 keV image. This means that the subtracted image will show Pt only (Fig. 5c). The salt and pepper noise was eliminated with the Despeckle operation in ImageJ, which is a 3 × 3 median filter that replaces each pixel with the median value in its 3 × 3 neighborhood [14]. Fig. 5d–f shows the thresholded tomographs of the images represented by Fig. 5a–c, respectively. From the thresholded tomographs, it is more evident that Pt is a minor phase, and that most of the bright pixels correspond to ionomer phase (Cs).
Fig. 3. Relationship between the volume fractions of Pt and Cs for a 10 μm thick sample. The range of volume fractions where Cs is brighter below the Pt L3 edge and Pt is brighter above the edge is shown in yellow. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
4.3. Volume rendering and morphology quantification Fig. 6 shows a three-dimensional volume rendering of the Pt (green) and ionomer (blue) and the distribution of the two throughout the 42
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Fig. 4. Thresholding procedure a) phase contrast image b) thresholded phase contrast image (solid phase white) c) absorption contrast image d) thresholded absorption contrast image (platinum white) e) thresholded absorption contrast image (ionomer white) f) absorption contrast image with ionomer highlighted. dNSTF catalyst layer, Wh/S = 10.0, 3 M 825 EW ionomer with I/S = 0.8, 0.4 mgPt cm−2.
morphological properties of the catalyst layer imaged. Volume fraction, tortuosity, and size distribution are the parameters chosen to describe the sample morphology. Table 1 shows that neglecting to separate Pt from ionomer when performing these calculations results in overestimating the volume fraction and average size of the ionomer and underestimating the tortuosity factor. Supplementary material, Fig. S7 shows the ionomer size distributions and tortuosity factors. Ionomer size, when separated from Pt is 48.6 nm, whereas when combined with Pt it is 66.2 nm. No connectivity between Pt particles was observed and hence the tortuosity factor was not defined. Although well distributed, the connectivity of ionomer is not as high, a value of 8.3. This value is based on separating Pt and Cs, however tortuosity factor is much lower (value of 3.0) for combined Pt and Cs domain, which can result in significant error in morphology interpretation. Comparing the results in Table 1 to the predictions (shown in the column 5 of Table 1), the volume fraction of Pt (4.1%) is almost exactly
sample. Observing by eye, the two phases are well distributed within the electrode. This uniformity can be quantified by comparing the volume fraction of Pt or ionomer for each cross section along an axis and finding the standard deviation of those values. Averaging the standard deviations of the volume fractions of the three coordinate directions gives values of 0.01 and 0.06 for Pt and ionomer respectively. These values are acceptable compared to the respective volume fractions of 0.04 and 0.30, which indicates that spatial variations in volume fraction are not high. The platinum here is also in good contact with the ionomer, as shown in Fig. 6d. The performance of this type of electrode was reported by Garsany et al. [31], when compared to electrodes with conventional ionomer, the electrodes with low-equivalent weight ionomer, imaged here showed improved performance at high current densities across variety of conditions. This might be due to the welldistributed ionomer as shown in this study. Further quantitative analysis is performed to understand the 43
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Fig. 5. a) 11.7 keV image b) 11.5 keV image c) result of subtracting (b) from (a) d–f) thresholded images of respective scans. The bright spot in (a) could be either Pt or Cs. By subtracting (b) which Cs only, (c) shows Pt only. The grayscale images (a–c) were filtered using a two iteration 3 × 3 median filter. 50 wt% Pt/CB, with Aquivion® ionomer, I/C = 0.95, 0.31 mgPt cm−2.
Ni/C catalyst is shown imaged at near the K-edge. The disadvantage of the method is that both density and thickness of the material play role, and sometimes (Fig. 3) one has to understand the composition of two phases well to ensure that the resulting brightness is consistent with the expectations. The method is insensitive to very small volume fractions of material, and to well-dispersed nano-particles, as they will be below the nano-CT resolution. The other challenge is that the Pt L3-edge is at the boundary of the optical elements losing their efficiency. Thus not every beamtime has this sufficiently broad energy range. XANES imaging, which is an enhanced two-energy imaging approach can provide similar information, in addition to the oxidation state of the material. The two energy-imaging is relatively not time-consuming, as only two scans are needed, whereas XANES tomography can take many hours.
equal to the predicted (4%). Note that the volume fraction of Pt with single energy imaging will be zero, as the method attributes all the bright features to combined phase (Cs and Pt). The volume fraction of ionomer (30%) is lower than predicted (54%). It is possible that not all ionomer domains were stained during sample preparation, as Cs staining procedure is highly sensitive. If the sample is oversaturated with Cs and not dipped in DI water for sufficient time, large Cs crystals form on the surface of the material as seen in Fig. S4, Supplementary material. These crystals are very bright, due to the large thickness of the crystals, and they overshadow all other features in the image. In order to combat this, the sample is rinsed with DI water to remove excess Cs. An alternative explanation is that the nano-CT imaging does not capture the thin-film ionomers that surround the carbon agglomerates and are thinner than the resolution of the nano-CT (which is ~24 nm/voxel for SSRL beamline). Overall, the two energy imaging technique is based on absorption contrast and utilizes X-ray absorption edges of elements to dim (below the edge) or enhance (above the edge) the element of interest. This method is very well fit for elements that have very similar density (such as Pt and Cs). For novel catalysts such as Pt-alloys (Co, Ni etc.), again imaging about Pt absorption edge will separate Pt and ionomer phases. To separate Pt and Ni elements, imaging above and below the Ni edge has to be performed. In the Supplementary material, an example of a
5. Conclusion X-ray computed tomography is a non-intrusive method based on transmission x-ray microscopy (TXM) technique to image samples in three-dimensions. Here, we present the single energy imaging results of a Cs-stained electrode in absorption and phase-contrast imaging. From the phase-contrast imaging, it is possible to separate the carbon material from the void, whereas absorption-contrast imaging is a better fit to separate Pt and Cs from the rest of the phases. Here, for the first time, 44
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Fig. 6. Volume renderings of a) Platinum b) ionomer c) Platinum and ionomer. d) Cross-section image with Pt (green) and ionomer (blue) highlighted. 50 wt% Pt/CB, with Aquivion® ionomer, I/C = 0.95, 0.31 mgPt cm−2. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Table 1 Properties of scans at the two energies. The reported tortuosity is averaged across the three coordinate directions. The calculated volume fractions are reported. The standard deviations are reported for some of the values too. Scan
11.7 keV
11.5 keV
Difference
Calculated (from densities and composition)
Visible features Volume fraction above threshold
Platinum and cesium 0.463 ± 0.06
Cesium only (ionomer) 0.301 ± 0.06
Platinum only 0.041 ± 0.01
Average tortuosity factor Average size, radius
3.0 ± 0.7 66.2 nm
8.3 ± 4.6 48.6 nm
N/A 44.1 nm
All phases Ionomer: 0.54 Platinum: 0.04 N/A N/A
under Award Number DE-EE0007270. Use of the Stanford Synchrotron Radiation Lightsource at SLAC National Accelerator Laboratory is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Contract No. DE-AC02-76SF00515. This research used resources of the Advanced Photon Source, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DEAC02-06CH11357. We thank Dr. Yannick Garsany and Dr. Karen Swider-Lyons, Naval Research Laboratory for Pt/C catalyst layer preparation. We thank Dr. Vincent De Andrade and Dr. Johanna Nelson Weker for the beamtime support at the APS and SSRL, respectively.
we present a method for imaging the ionomer distribution in Pt-containing electrodes to separate Pt from Cs-stained ionomer. The method is based on two-energy imaging: below and above the absorption edge of the element (here we chose Pt). We provide a theoretical analysis to prove that for given length-scales of Pt and Cs-stained ionomer, the twoenergy method is valid, as light intensity detected by the detector depends on both the attenuation coefficient and the thickness of the material. By imaging the sample below and above the L3 absorption edge of Pt, the Pt phase shows up darker than Cs and brighter than Cs below and above the edge respectively. With this method, we quantify several important properties of the ionomer morphology within the electrode, such as the volume fraction and the tortuosity. For the sample studied, the ionomer distribution was uniform and Pt was in contact with the ionomer. The ionomer volume fraction was lower (30%) than that predicted by ink composition calculations (54%), which is due to incomplete Cs-wetting of the ionomer or due to insensitivity of the method to the thin films. Furthermore, the work presents the derivations and guidelines for the selection of absorption or phase contrast imaging. Materials with a high absorption index should be imaged using absorption contrast, whereas those with a low absorption index should be imaged in phase contrast. Predicting the relative brightness of objects in an image relies on both the x-ray properties of the material and its thickness and requires complex mathematical expressions to resolve the dependency on both that are also presented in this work.
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Acknowledgement This material is based upon work supported by the Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE), 45
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