SUPPORTING INFORMATION

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Nickel Poisoning of a Cracking Catalyst Unravelled by Single

Particle X-ray Fluorescence-Diffraction-Absorption Tomography

Marianna Gambino,[a] Martin Veselý,[a] Matthias Filez,[a] Ramon Oord,[a] Dario Ferreira Sanchez,[b]

Daniel Grolimund,[b] Nikolai Nesterenko,[c] Delphine Minoux,[c] Marianne Maquet,[d] Florian Meirer*[a] and

Bert M. Weckhuysen*[a]

Table of Contents

S.1 SINGLE PARTICLE SELECTION X-Ray Fluorescence Microscopy using a laboratory X-ray source S.2 EXPERIMENTAL SECTION A. Confocal Fluorescence Microscopy B. X-Ray Fluorescence, Diffraction and Absorption Tomography using Synchrotron Radiation S.3 DATA PROCESSING

A. X-Ray Fluorescence Tomography B. X-Ray Diffraction Tomography C. Crystallographic Phases Identification

D. Radial Distribution Analysis E. Principal Components Analysis and k-means/GMM Clustering

F. Pearson Correlation Coefficient Analysis G. Zeolite Amorphization H. Small Angle XRD Peak

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S.1 SINGLE PARTICLE SELECTION

The FCC catalyst samples under study were provided by Total. Unseparated ECAT1 and ECAT2, respectively exposed in the reactor

to non-hydrotreated and hydrotreated crude oil-based feedstock, were collected from the regenerator and further calcined at 600°C for

24h with a 5°C/min ramp to burn off the residual coke. The unseparated ECAT1 sample was then subjected to density separation and

four fractions (F1, F2, F3 and F4) were collected. The content of the metal poisons, Fe, V and Ni, of these four ECAT1 fractions

compared to the unseparated ECAT1 sample as well as of the ECAT2 sample is reported in Figure 2 of the main text. Since we wanted

to isolate catalyst particles that were enriched in Ni, we have selected the Ni-rich particle from the ECAT1 heaviest fraction, namely

fraction F1 (that will be further denoted as ECAT1-F1 in both the main text as well as the supporting information).

X-Ray Fluorescence Microscopy using a laboratory X-ray source

ECAT1-F1 and unseparated ECAT2 single catalyst particles for X-ray tomography were carefully selected based on X-ray fluorescence

microscopy (further denoted as µXRF) characterization data. The particles were sprinkled on tape using a microscopy slide as support.

µXRF was measured with an Orbis PC SDD instrument, having a Rh-tube as X-ray source (40 kV and 200 nA). FCC catalyst particles

were scanned with a 30 μm beam, using a step size of 15 μm and 300 ms integration time. Batch fitting data analysis procedure was

carried out with Pymca software[1] and single FCC catalyst particles were selected according to their Ni content. Figures S1 and S2

show the multi-particle µXRF results for the ECAT1-F1 and ECAT2 samples. The results reported in Figure 2 of the main text are

obtained using the same µXRF analysis protocol, but on a different field of view containing a higher number of particles (195 for ECAT1-

F1, 140 for ECAT1-F2, 91 for ECAT1-F3, 108 for ECAT1-F4, 104 for unseparated ECAT1 and 165 for unseparated ECAT2).

We can immediately observe in Figure S1 that Fe is present in approximately the same amount in the ECAT1-F1 sample and in the

unseparated ECAT2 sample. Interestingly, Ni and V are found in high concentration in the ECAT1-F1 sample, while these elements

are basically absent in the unseparated ECAT2 sample. In the XRF spectra we observe the typical elements contained in the FCC

catalyst material, such as Al, Si, Ti, La, V, Fe and Ni. The strong Rh peak is related to the X-ray laboratory source, while the strong Cl,

Ca, S and P peaks are mainly related to the tape material used to support the catalyst particles during measurements. However, Ca is

also found in traces as contaminant, while P can be also found in few additive FCC catalyst particles, containing ZSM-5, that are used

to increase the light olefins yield during the FCC process. Figure S2 shows the fitting of the sum XRF spectrum over the whole ECAT1-

F1 and ECAT2 maps: the inset shows the zoomed-in energy region between 4.2 and 6.2 keV, where a strong overlap of La, Ti and V

fluorescence lines can be observed.

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Figure S1. µXRF maps (batch fitting results) for the ECAT1-F1 and ECAT2 samples. The scale bar indicates 300 µm.

Figure S2. XRF fitting results for the ECAT1-F1 and ECAT2 samples over the whole map average spectrum (left) and zoomed-in energy region between 4.2 and

6.2 keV showing the deconvolution of Ti K, La L and V K fluorescence lines (right).

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S.2 EXPERIMENTAL SECTION

A. Confocal Fluorescence Microscopy

Figure S3 shows the experimental set-up used in this paper. Before synchrotron measurements, single-particle Confocal Fluorescence Microscopy (CFM) after thiophene staining was measured on a spherical cap of the selected ECAT1-F1 and ECAT2 particles in order to obtain the 3-D distribution of the Brønsted acid sites (Movies MS1 and MS2). Ex-situ staining was carried out using the following protocol: the FCC catalyst single particles selected after µXRF analysis were isolated on a microscopy slide and put in contact with 20 µL of thiophene. The Brønsted acid sites, present in the zeolite domains, catalyzed the thiophene oligomerization reaction, a reaction started by heating at 393 K. The particle was mounted on a needle that was placed on a stage. CFM measurements were performed with a Nikon A1 confocal fluorescence microscope (100x objective) in DU4 mode and a 561 nm laser was used to excite the fluorescent thiophene oligomers, that were detected in the spectral range of 575-635 nm. Since the Brønsted acidity difference was very different in the two catalyst particles it was not possible to use the same laser power for both ECAT1-F1 and ECAT2 samples: Ni-rich ECAT1-F1, which had very low fluorescence signal, was measured using a value of 30 a.u., while Ni-free ECAT2, showing much higher fluorescence, was measured at 7 a.u. Measurements were acquired using 0.125 µm pixel size and 0.482 µm Z-step size. The particle spherical cap was reconstructed in 3-D with an in-house developed MATLAB code, by using a 4x binning factor to decrease the noise.

B. X-Ray Fluorescence, Diffraction and Absorption Tomography

Combined µXRF-µXRD-µXANES tomography measurements were carried out at the X05LA microXAS beamline of the Swiss Light Source (SLS) in Villigen (Switzerland). The µXRF signals for Ni, Fe and La selected elemental channels were measured using two XRF detectors, while a full µXRD pattern/pixel was simultaneously collected using an Eiger4m 2D detector. X-ray tomography data were acquired in the angular range 0-180°, using a step size of 2°. For each rotation angle ω a line scan along Y was collected, using 1 x 1 µm2 beam size and 12.1 keV beam energy. Virtual slices were therefore measured in the XY plane at 18 µm Z depth. In order to minimize beam damage of the zeolite phase, a single point of the particle was irradiated for several minutes and the decrease of intensity of the zeolite [111] main X-ray diffraction (XRD) peak was followed in position and intensity over time. Basing on this information we have chosen a 0.15 s exposure time. The µXANES tomography measurements at Ni K-edge were subsequently collected on the virtual slice at 18 µm depth by collecting 34 energy points in the spectral range 8300-8387 eV and increasing the density of points around the pre-edge and the whiteline features. Ni foil and NiO spectra were measured at the beamline as reference compounds, while the NiAl2O4 reference compound was extracted from literature.[2,3] In order to be able to compare the spectrum from literature with our dataset, we have extracted also NiO and calculated the energy shift compared to the NiO we have measured during the experiment. We finally corrected the NiAl2O4 reference for this shift and used it as a reference in our study. It is important to stress that in our study it was not possible to assess the interaction of V with FCC catalyst components, since during the measurement only selected specific elemental channels are recorded to obtain the metals spatial distributions. This is no problem for the La Lα, Fe Kα and Ni Kα lines as they are isolated fluorescence lines, but the strong overlap of the V Kα fluorescence line with La Lβ and Ti Kα would require an additional peak deconvolution procedure and therefore the analysis of the full XRF spectrum (see section S.1, Figure S2), which is not available.

Figure S3. Outline (left) and pictures (right) of the experimental set-up to measure combined µXRF-µXRD-µXANES tomography as well as laboratory-based confocal fluorescence microscopy after staining with thiophene.

S.3 DATA PROCESSING

A. X-ray Fluorescence Tomography

X-ray Fluorescence (XRF) tomographic slices were reconstructed from the sinograms by using a Python code developed at the microXAS beamline based on the ASTRA library, [4] based on the Simultaneous Iterative Reconstruction Technique (SIRT). Since the measurements were carried out with two XRF detectors, reconstructed slices from each detector were combined together, in order to correct for i) differences in intensity measured by the two XRF detectors and ii) the intensity attenuation observed as function of the distance on the XY plane.

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B. X-ray Diffraction Tomography

X-ray Diffraction (XRD) tomographic reconstructions were carried out using in-house developed Python routines developed at the microXAS beamline based on the ASTRA library.[4] 1-D X-ray diffraction patterns obtained by azimuthal integration of the detector images, utilizing pyFAI,[5,6] were analyzed as a function of position and rotation to reconstruct one sinogram per 2θ angle (0-42.68° with a ~0.01° step), producing 4334 sinograms. A Filtered Back Projection (FBP) algorithm was applied to obtain tomographic reconstructions of virtual slices. Finally, the data were reorganized in a way that a full diffractogram for each pixel was obtained.

C. Crystallographic phases identification

The structures used to simulate XRD reference pattern were selected from the Inorganic Crystal Structure Database (ICSD), Crystallography Open Database (COD) and American Mineralogist Crystal Structure Database (AMCSD).[7–9] The identification codes are indicated in the captions of Figures S5, S6 and S7. The analysis of the average pattern over the whole virtual slice allowed the clear identification of faujasite type (FAU) zeolite Y-zeolite (Fd-3m), anatase (I41/amd) and rutile (P42/mnm) TiO2 polymorphs (Figure S4). A broad peak centered at about 30° is clearly detectable on the average pattern and is related to the nano-sized γ-Al2O3 matrix component, having cubic defective spinel-type structure (Fd-3m). Moreover, the background observed in the range 10-25° is compatible with the presence of amorphous SiO2, which is another component of the FCC catalyst matrix. Peaks related to the sillimanite phase SiAl2O5 , a precursor of mullite, are also found in the pattern.[10] Concerning the poisoning metals related phases, no XRD peak indicating the presence of e.g. Ni or NiO could be detected (Figure S7). We cannot exclude the presence of these phases by XRD, since they can be present in very low amount and/or have poor crystalline structure and being not efficiently detected by XRD. This is the reason why we have collected also µXANES at Ni K-edge, that gave us indication of a prevalent spinel-type local structure for Ni. Moreover, the high correlation between µXRF elemental distribution and the XRD phases, pinpoints that Ni is found in correlation with the γ-Al2O3 matrix indicating a preferential interaction with its defective spinel type structure. It is important to highlight that, as shown in Figure S6a, the position of NiAl2O4 peaks is very similar to γ-Al2O3. Usually, in order to obtain pure crystalline NiAl2O4 phases, calcination temperatures above 850°C are required: these temperatures are higher than those used during regeneration and this could explain why we still see a dominant γ-Al2O3 pattern with broad XRD peaks, but we also observe an increase of intensity of the [400] reflection in the regions that are highly spatially correlated with Ni. Moreover, we also have to keep in mind that in the regions where γ-Al2O3 and Ni are co-localized, we can also detect the presence of Fe: if also Fe enters the spinel structure this might increase the structural disorder of these phases, damping the long-range order. No peaks from the clay mineral are clearly detectable in the average XRD pattern for the ECAT1-F1 and ECAT2 samples, most probably due to the amorphization of this crystalline phase over the catalytic cycles.

Figure S6b shows the average XRD pattern over ECAT1-F1 γ-Al2O3 hotspots together with NiAl2O4, FeAl2O4, NiFeAlO4 and some other phases related to deactivation, such as SiAl2O5, and the Fe-containing phases hematite and magnetite. We note that, based on the peak positions, all these phases might be present in the sample, corroborating the hypothesis that Fe is also reacting with the catalyst matrix. However, the strong peak overlaps (probably also related to the presence of solid solutions with intermediate Ni(FexAl1-

x)2O4 composition and to the low crystallinity of these phases due to the experienced reactor temperatures), prevents decomposition of these single components.

We also have checked for the possible presence of hydrotalcite, often used in the FCC catalyst manufacture as SO2 and SO3 sorbent, since sulfur can replace carbonate anions in the structure.[11] This material has a brucite structure typically made by layers of magnesia and alumina, each layer typically separated by carbonate anions. Pérez-Ramírez et al. observed upon heating around 423-473 K the formation of an intermediate highly disordered, dehydrated phase and around 623 K the formation of an Mg(Al)Ox mixed oxide phase with periclase structure.[12] They also found that the intermediate dehydrated phase reverts into hydrotalcite in a fast way at RT upon contact with water vapor. On the other side, when the hydrotalcite is calcined at 723 K the return to the original structure is much slower and the reconstruction does not go through the layered dehydrated phase (hydrotalcite → dehydrated layered phase → mixed oxide), but it occurs in a single step (mixed oxide → meixnerite – which contains interlayer hydroxide anions instead of carbonate). No clear XRD peaks related to periclase MgO can be univocally detected and the average laboratory-based XRF spectrum over the FCC catalyst batch does not reveal a significant amount of Mg (see Figure S2). The complexity of the multicomponent FCC catalyst material and the phases modifications occurring over several catalytic cycles do not allow to clearly detect this phase. Nevertheless, due to its composition (MgO and γ-Al2O3) we can believe that, if present, it perfectly blends with the FCC catalyst matrix, giving the same type of interaction with the poisoning metals.

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Figure S4. Left: Average X-ray diffraction (XRD) pattern of an ECAT1-F1 (bottom) and ECAT2 (top) virtual slices. Zeolite (pink), γ-alumina (gray), rutile (orange),

anatase (green) and sillimanite SiAl2O5 (blue) phases were found. Right: The µXRD tomography maps showing zeolite and matrix distribution for the ECAT1-F1

and ECAT2 samples.

Figure S5. Average X-ray Diffraction (XRD) pattern of an ECAT1-F1 (black) and ECAT2 (red) virtual slices. Simulated XRD pattern of γ-alumina (ICSD 603780 -

purple), faujasite (COD 7224243 - blue), rutile (AMCSD 0019092 - magenta), anatase (AMCSD 0019093 - green) and sillimanite SiAl2O5 (COD1532332 - navy).

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Figure S6. a) Average X-ray Diffraction (XRD) pattern of an ECAT1-F1 slice (blue), ECAT2 (red) and ECAT1-F1 Ni-enriched hotspot (black). Simulated XRD

patterns of γ-alumina (ICSD 603780 - wine), Ni (COD 9012968 - dark yellow), NiO (COD 1010093 - orange), NiAl2O4 (COD 9006038 - magenta), FeO (AMCSD

0013893 - green), magnetite Fe3O4 (ICSD 26410 - navy) and hematite Fe2O3 (ICSD 15840 - purple). b) Average diffraction pattern over ECAT1-F1 γ-alumina

hotspots compared to faujasite (COD 7224243 - blue), γ-alumina (ICSD 603780 - red), NiAl2O4 (COD 9006038 - green), hercynite FeAl2O4 (AMCSD 0002031 -

purple), NiFeAlO4 (from J. C. Chen et al.[13] - yellow), magnetite Fe3O4 (ICSD 26410 - orange), hematite Fe2O3 (ICSD 15840 -light blue) and sillimanite SiAl2O5

(COD1532332 - purple).

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Figure S7. Average X-ray Diffraction (XRD) pattern over an ECAT1-F1 slice (red), ECAT2 (blue) and ECAT1-F1 Ni-enriched hotspot (black). Simulated XRD

patterns of γ-alumina (ICSD 603780 - magenta), hydrotalcite (AMCSD 0014738 - green), periclase MgO (AMCSD 0000501 - navy), faujasite (COD 7224243 -

purple).

D. Radial Distribution Analysis

The Radial Distribution Analysis (RDA) was carried out on the Ni and Fe distribution from the µXRF tomography dataset using an in-

house developed MATLAB code. The results show a Ni and Fe gradient with a maximum concentration value at around 3 µm from the

surface.

E. Principal Components Analysis and k-means/GMM Clustering

a. µXRD tomography dataset

Principal Components Analysis (PCA) and Cluster Analysis (CA) were applied to the XRD tomography dataset using the TXM XANES

Wizard as software.[14] This analysis allowed spatially resolved pixel by pixel peaks deconvolution in selected 2θ regions, without losing

information about nano-crystalline components and zeolite crystallographic changes.

Two 2θ regions were considered:

a) zeolite [1 1 1] peak;

c) γ-Al2O3 [4 0 0] peak.

PCA using Singular Value Decomposition (SVD) of the filtered and mean centered data matrix was first used to reduce the dataset to

3-4 Principal Components (PCs) in each of the analyzed 2θ regions. Relevant PCs were selected based upon inspection of

eigenspectra and eigenimages where PCs containing mainly noise were discarded. The centroid linkage method for k-means clustering

was then applied. Pixels belonging to the virtual slice were clustered according to their Euclidean distance from cluster centers and

therefore assigned to a specific cluster. The result is a segmented image displaying k clusters, each one representing virtual slice

regions with most similar XRD pattern. Once the center position of each cluster was obtained, the Gaussian Mixture Model (GMM)

method was applied to the k-means result in order to refine the clustering according to the density of points in PC space. The

expectation-maximization (EM) algorithm was used for the GMM iterative refinement.

As a following step, for each cluster, a binary mask was created and used as filters to extract the average XRD pattern in the whole 2θ

range: results for the zeolite [111] reflection and for the spinel [400] reflection are reported in Figure 6 and S8.

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Figure S8. Average X-ray Diffraction (XRD) pattern for each cluster extracted in the whole 2θ range for the ECAT1-F1 (left) and ECAT2 (right) sample.

b. µXANES Tomography

PCA and CA were carried out also on the normalized µXANES dataset of the Ni-rich ECAT1-F1 particle. Results are shown in Figure S9. From this analysis it is possible to observe that the central region of the slice (clusters 1 and 4) is affected by self-absorption: in this region the XANES spectra are strongly damped and no information can be extracted. Therefore, we have considered only clusters 2 and 3 and compared their XANES profile with the reference compounds. The whiteline position as well as the XANES profile shape are similar to the spinel-type NiAl2O4 compound.

Figure S9 µXANES Principal Component Analysis (PCA) and Cluster Analysis (CA) results (Ni K-edge) of ECAT1-F1. Left: Image segmentation. Center: average

XRD pattern for each cluster. Right: average µXANES for each cluster in the considered energy range. Ni, NiO and NiAl2O4 references[2,3] are reported with dotted

lines.

F. Pearson Correlation Coefficient Analysis

Correlation analysis was carried out in order to find similarities in the spatial distribution of Ni, Fe and zeolite components. The results are summarized in Figure S10. The Ni, Fe and zeolite data matrices were firstly reshaped in vector arrays and correlation plots were

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subsequently created for all the possible Fe, Ni and zeolite pair combinations. Moreover, the Pearson Correlation Coefficient (PCC) was calculated for the Fe-Ni, Fe-zeolite, Ni-zeolite, Ni-spinel, Fe-spinel and spinel-zeolite distributions.

Figure S10. Ni-Fe, zeolite-Fe, zeolite-Ni, spinel-Ni, spinel-Fe and spinel-zeolite correlation plots for the ECAT1 (left) and ECAT2 (right) samples. Pearson Correlation

Coefficients are reported for each pair.

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G. Zeolite Phase Amorphization

Since La is added to the zeolite active phase to improve its hydrothermal stability, La (Lα) map was used as a specific marker to locate

pristine zeolite distribution within a FCC catalyst particle. The zeolite (red) and La (green) maps were plotted together in an RGB map

and the results for ECAT1-F1 and ECAT2 are shown in Figure S11. It is clear that the zeolite phase was completely subjected to

amorphization in the near-surface region in both ECAT1-F1 and ECAT2. Ni-free ECAT2 also shows more amorphization in the inner

part of the FCC catalyst particle when compared to the Ni-rich ECAT1-F1 material. Pearson correlation coefficient (PCC) analysis show

high La-zeolite spatial correlation (i.e., ECAT1-F1 = 0.7533 and ECAT2 = 0.7681).

Figure S11. Zeolite (red) – La (green) RGB maps and Pearson correlation plots for ECAT1-F1 (top) and ECAT2 (bottom).

H. Small-Angle X-ray Diffraction Peak

Principal Component Analysis (PCA) and clustering analysis was also applied to the small angle X-ray diffraction (XRD) peak detected

for both samples in the 2θ range 0.8-1.8°. The results are shown in Figure S12. This XRD peak suggests an overall higher mesoporosity

for ECAT2, compatible with less reacted nanosized matrix at negligible Ni concentration. ECAT2 also shows an outer layer with reduced

mesoporosity that is correlated with Fe distribution and with those regions where zeolite undergoes complete amorphization.[15]

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Figure S12. Principal Component Analysis (PCA) and Cluster Analysis (CA) results for the small angle X-ray diffraction (XRD) peak (0.8-1.8°). From left to right:

The average XRD map, the image segmentation and the corresponding XRD average patterns.

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