In-Situ Ptychographic Nanotomography Captures Activation, Mobility, and Deactivation of Supported Catalysts

In-Situ Ptychographic Nanotomography Captures Activation, Mobility, and Deactivation of Supported Catalysts | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article In-Situ Ptychographic Nanotomography Captures Activation, Mobility, and Deactivation of Supported Catalysts Arik Beck, Mirko Holler, Tomas Aidukas, Andreas Menzel, Manuel Guizar-Sicairos, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7914877/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Nanoparticles supported on the surface of porous carrier materials are the dominant form of heterogeneous catalysts today. Yet, they suffer from a common deactivation mechanism: the loss of active surface area under industrial use conditions. Deactivation often stems from the sintering of nanoparticles, a mass transport process whose mechanism and operating length scale are a topic of controversy. Investigating this process is challenging, requiring not only a behavioural characterisation of thousands of individual particles within the spatial confines of a hierarchically structured support but also a characterisation of their ensemble behaviour and local support interactions. Here, we introduce in-situ ptychographic X-ray computed nanotomography as a tool to facilitate this characterisation, allowing a local examination of catalysts in their use-geometry under operational-relevant conditions. Applied to methane oxidation over a palladium-on-silica supported catalyst, we reveal two concurrently operating deactivation drivers, short-range ripening and long-range particle migration, each with different temperature and atmosphere dependencies. The latter enables particles to traverse hundreds of nanometres through the support. These observations expand the current understanding of sintering behaviour in supported catalysts and demonstrate PXCT’s capability to resolve restructuring processes within complex porous materials. Physical sciences/Chemistry/Catalysis Physical sciences/Materials science/Techniques and instrumentation Physical sciences/Chemistry/Catalysis/Heterogeneous catalysis Ptychography Tomography Heterogeneous Catalysis Supported Catalyst Methane Oxidation Figures Figure 1 Figure 2 Figure 3 Figure 4 One-Sentence Summary Understanding and preventing the loss of active surface area in supported catalysts due to transport and sintering processes remains an industrial-scale challenge. Here, using in-situ ptychographic nanotomography, we track the formation, mobility and aggregation of 100,000s of catalyst nanoparticles in a supported catalyst under operating conditions. Introduction Heterogeneous catalysts are central pillars of the chemical industry and essential to energy and chemical production as well as environmental remediation. 1 While certain levels of catalytic activity and selectivity are application requirements, industrial and economic viability is often determined by a catalyst’s longevity. Supported catalysts are a prime example of this, finding, for example, application in automobiles for the remediation of exhaust gases. 2 Here, catalytically active nanoparticles, often palladium, are finely dispersed on the surface of a porous support, and are used to transform unburned hydrocarbons and carbon monoxide to carbon dioxide. 2 During this transformation, and for years on end, the catalyst is exposed to high temperatures (> 400°C), which results in a high catalytic activity, but gradually deactivates the catalyst. 3 This deactivation, as in many other catalysts, stems from the loss of active surface area. 4 In supported catalysts, this loss in surface area is typically caused either by Ostwald ripening, where smaller particles dissolve and redeposit onto larger ones, or by particle migration and coalescence (PMC) processes, where entire particles move across the support surface and then fuse. 5,6 Characterization of these degradation processes and their prevention remain a major industrial-scale challenge. In-depth studies yet remain particularly difficult, requiring the observation of thousands of nanoparticles, < 10 nm in diameter, within the confines of millimetre-sized, use-representative catalyst architectures and under application conditions. 7 Traditional, ensemble-averaging in-situ techniques, such as X-ray diffraction and spectroscopy, remain invaluable for identifying bulk structural changes and average chemical states, but provide limited insight into local heterogeneities, spatial dependencies, and particle migration dynamics. 8 High-resolution imaging methods, in contrast, can provide these and allow for a more detailed understanding of catalyst behaviour, including the mobility of individual nanoparticles. 9–11 For example, using in-situ transmission electron microscopy, we showed that the nanoparticles in a supported catalyst can become highly mobile under reaction conditions, questioning a previously suggested pure and local Ostwald Ripening driven deactivation. 12 However, transmission electron microscopy is constrained to sub-micron sample volumes 5 and commonly involves destructive sample preparation steps to obtain electron transparent specimen. This limits its use for studying realistic catalyst architectures and statistically representative particle behaviour. Ptychographic X-ray computed tomography (PXCT) is an emerging complementary investigative method, 13–16 allowing us to measure larger and intact sample volumes with sufficient spatial resolution to identify the nanoparticles within a supported catalysts. 17 Owed to missing instrumentation, PXCT has mainly been employed in an ex-situ manner, i.e. measuring samples before and after catalytic reactions. 16,18,19–22 The removal of the catalyst from the reactor and its operational environment, yet, alters the catalyst, making a use-representative characterisation currently practically impossible. Here, enabled by a custom and PXCT-compatible environmental control system, 23 we present an in-situ ptychographic nanotomography study examining a supported palladium on silica (Pd/SiO 2 ) catalyst across its complete lifecycle (activation–operation–deactivation). By repeatedly capturing the same volume from 25°C to 830°C under alternating methane-rich and oxidizing atmospheres, we quantitatively tracked the formation, growth, redistribution, and mobility of over 100,000 palladium nanoparticles. The experiments revealed two distinct modes of palladium transport feeding catalyst deactivation. A short-range diffusion process consistent with Ostwald ripening, and a long-range particle redistribution mechanism, both leading to losses in surface area. Most strikingly, the experiments revealed that the majority of the palladium nanoparticles remains in motion during the reaction, showing that relocalization, fragmentation, and agglomeration are continuous processes. The experiments further allowed to quantify the average palladium transport velocity within the 3D pore structure, amounting to ~ 100 nm h − 1 under the most severe operating conditions (750°C). These mobility processes are strongly modulated by the gas environment, with oxidizing conditions promoting localized coarsening or ripening processes and methane-rich conditions causing particle mobility across hundreds of nanometres. More broadly, this study highlights the ability of in-situ PXCT to quantitatively resolve nanoscale transformations within large sample volumes and across environmental conditions. This bridges the resolution-statistics gap that has long stalled in-situ characterisation studies. Results The palladium-on-silica (Pd/SiO 2 ) catalyst was prepared by wet impregnation of a mesoporous support 24 with a palladium nitrate solution. 12,17,25 The amorphous silica support possesses an average pore diameter of ~ 110 nm. The impregnation process results in the deposition of a thin film of palladium nitrate on the surfaces of the support, which upon calcination is converted into a dispersion of catalytically active PdO nanoparticles. To evaluate the catalyst’s methane oxidation activity as a function of temperature, the catalyst was then gradually heated to 300°C (initiating precursor decomposition and PdO formation), 450°C, 550°C, 650°C, and finally 750°C under a constant flow of a methane-oxygen gas mixture (1 mol% CH 4 / 4 mol% O 2 / 94 mol% Ar) in a tubular reactor. Following a residence time of 8 hours at each temperature, methane conversion was measured at 300°C using mass spectrometry. The resulting activity profile (Fig. 1 a) shows a gradual decline with increasing treatment temperature, indicating progressive catalyst deactivation. Ex-situ scanning transmission electron microscopy (STEM) and powder X-ray diffraction (PXRD) (Figs. 1 a and S1 –S3) show that this loss in activity correlates with an increase in the average size of the PdO particles, from ~ 5 nm in the as-prepared state to ~ 15 nm after treatment at 550°C. Further, at this elevated temperature, larger sponge-like PdO agglomerates begin to appear. These observations suggest that the loss of catalytically active surface area is indeed the primary deactivation cause. However, ex-situ measurements do not reveal the mechanisms of these structural changes. To obtain a glimpse of these mechanisms, we then examined a 7 µm-wide catalyst pillar (Figure S4) via in-situ ptychographic X-ray computed tomography, 21,26 capturing the evolution of the catalyst from nitrate-rich precursor decomposition to deactivation (Fig. 1 b). Tomograms were sequentially acquired at 25°C and 300°C in air (calcination phase); at 300°C, 450°C, 550°C, 650°C, and 750°C under a constant flow of the methane-oxygen gas mixture to mimic operating conditions; and again at 750°C and 830°C in air to investigate the effect of atmosphere on particle mobility and sintering (Fig. 1 a). The tomograms have a voxel size of (15.5 nm) 3 and a sample average spatial resolution of 35 nm (Figure S5). A schematic of the acquisition setup is provided in Fig. 1 c. Instrumentation and experimental details are provided in Holler et al. 23 and in the Methods section. A key advantage of PXCT is that it provides quantitative electron density tomograms, 14,15,27–30 with each voxel returning an absolute density value. A priori knowledge of the electron densities of the catalyst’s components, ~ 0.00 n e Å −3 for air and argon, 0.55 n e Å −3 for amorphous silica and 2.21 n e Å −3 for PdO (Table S1), allows us then to segment and quantify material phases, respectively track their evolution. 31 Fig. 1 d shows a threshold-segmented volume rendering of the tomogram acquired at 25°C, highlighting the silica support and the distribution of palladium-rich precursor deposits within it. The deposits are heterogeneously distributed and vary in density, reflecting the inherent limitations of wet impregnation processes, yielding here a volume-average Pd loading of ~ 1 wt.%. A consolidated view of the catalyst’s evolution is provided in Fig. 2 a, which shows the electron density histograms of the acquired tomograms. A first look reveals that the silica support is changing with temperature. Observable is a gradual increase in electron density from 0.53 n e Å −3 at 25°C to 0.58 n e Å −3 at 750°C. This densification, more pronounced under oxygen-rich conditions, coincides with a net sample mass increase of ~ 7% (Figure S6). Based on PXRD measurements, literature reports and the apparent high-defect density of the silica support, we currently attribute the observed densification to progressive elimination of volume defects, vacancies or, silanol groups, whereas the concomitant mass gain is most likely due to oxygen uptake e.g., the removal of oxygen vacancies and PdO formation (Figure S7). 32,33 Despite these density changes we observed no spatial deformation of the support within our detection limits. Analysis of the segmented pore network shows that the pore size distribution remains essentially constant, with the average pore diameter decreasing only slightly from 113 at 25°C to 107 at 750°C (Figs. 1 e & S8), i.e. well within the spatial resolution estimate of 35 nm and under a single voxel deviation of 15 nm. A close examination of the histograms reveals that a dominant fraction of PdO particles remains below the voxel size, i.e. the voxel possesses an electron density < 2.21 n e Å⁻³, even at 830°C. Although individual particle morphologies cannot be resolved at the current resolution, changes in electron density at the voxel-level provides a metric for quantifying PdO growth and mobility. An increase in voxel electron density reflects either particle growth or the aggregation of smaller PdO domains within that voxel, whereas a decrease indicates particle dissolution or relocation. Treating voxel electron density as a proxy for a volumetrically equivalent PdO particle size (Figure S9, Fig. 2 a), 31 we derive an average particle diameter of ~ 4.6 nm in the as-prepared catalyst, in agreement with the ~ 5 nm obtained by ex-situ STEM (Figure S2). This assignment is reasonable as palladium particles, whether metallic or oxidized, are the densest and mobile component in the system, meaning that observed density changes can be attributed unambiguously to palladium dynamics. Now, focusing on these Pd-rich voxels, defined here as those exceeding a density of 0.80 ne Å⁻³, or containing ≥ 15 vol.% PdO (Figure S9), we observe a steady increase in their number and average density (or effective particle size) with increasing temperature. Based on the changes of the histograms, the formation of PdO particles is initially driven by precursor consumption, while at higher temperatures their continued growth involves coalescence and long-range migration, with increasingly isolated PdO domains growing at the expense of smaller ones. Surprisingly, upon switching from the methane-rich reaction atmosphere to air at 750°C we observe a marked collapse of the left-side tail of the silica peak in the histogram and a concurrent rise in palladium-rich voxels. We believe this change is caused by oxidation-driven reorganization of previously porous, fragmented, or partially reduced palladium particles into more densely packed and well-defined PdO particles. Building on the histogram analysis of the PdO-rich voxels, we visualized their spatial distribution as a function of temperature and atmosphere. Figure 2 b and Movies S1 & S2 present volume renderings of the electron density differences between adjacent environmental conditions. This subtraction removes the constant contributions of the support and pore space, thereby highlighting locations where palladium accumulates or relocates to within the sample volume. Prominently visible in Fig. 2 c ( i ) – showing the difference between the as-prepared catalyst and the catalyst after activation at 300°C in air – is the decomposition of the deposited precursor and the formation of PdO particles; a first growth process of palladium particles. Continued treatment at 300°C under methane oxidation conditions ( ii ) leads to a notable increase in the number of PdO-rich voxels across the support, visually resembling a typical supported catalyst. Importantly, no significant electron density loss is detected elsewhere, indicating that particle formation arises from redox-driven densification of highly dispersed Pd-rich material into stable PdO nanoparticles rather than the coarsening of visible crystallites. Given the relatively low temperature and the presence of both oxidizing and reducing gases, partial redox cycling (Pd 2+ /Pd 0 ) may facilitate redistribution and nucleation at this stage. 34 These processes precede the onset of classical and here visually detected Ostwald ripening or PMC, 5,35 which becomes increasingly evident at higher temperatures ( iii ), where particle growth is accompanied by shrinkage and or disappearance of smaller particles in localized regions. ( iv-vi ) The stepwise examination up to a temperature of 750°C under methane oxidation conditions showed a gradual but limited increase in both particle size and number consistent with continued coarsening. However, this stage is also marked by abrupt shifts in the spatial distribution of palladium-rich voxels, suggesting the presence of an additional, longer-range palladium redistribution mechanism. The emergence of new Pd-rich domains, often hundreds of nanometers away from regions of simultaneous depletion, points to palladium relocation via the long-range migration of particles, aggregates, or fragments. In parallel, we further observe the emergence of large, spatially fixed Pd-rich agglomerates, often porous and spanning multiple voxels, which appear to condense from this redistributed material. ( vii-viii ) Continued heating to 830°C and, importantly, a change to a purely oxidizing atmosphere appears to supress this long-range redistribution. Instead, we observe a distinct increase in newly resolvable PdO-rich voxels (Fig. 3 c). This behavior may reflect a transition in dominant growth or transport mechanism. Under methane-rich conditions, limited surface mobility is observed while selected Pd particles remained mobile enabling long-range redistribution. In contrast, under fully oxidizing conditions, surface and gas phase diffusion of PdO molecules and local restructuring is enhanced resulting in an increase in Ostwald ripening dominated growth. 36 To investigate possible spatial and mechanistic dependencies of these transport processes, we identified the location of mobile and stationary palladium-rich voxels. Figure 3 a shows the location of permanently and temporarily occupied regions – defined here as voxels that showed a Pd signal consistently or intermittently across the in-situ measurement. The permanently occupied voxels (stationary particles) are found preferentially near pore throats. Temporarily occupied voxels (transient particles) appear predominantly at the outskirts of stationary particle agglomerates or near open pore channels (Movies S3 & S4). Analysis further revealed a temperature-dependent increase in both voxel populations (Fig. 3 b), reflective of the thermally activated PdO particle formation and mobility. Mobility is also influenced by both particle size and atmosphere (Fig. 3 c). While stationary particles are on average only ~ 2 nm larger than mobile ones, no particle with an inferred or volumetrically equivalent diameter > 9 nm was observed to be mobile (Figure S10). The observed size-dependent mobility is consistent with models of particle transport, in which surface diffusion or gas-phase migration becomes increasingly restricted with particle size due to increasing particle-support interactions. 8 Further analysis of the stationary voxels revealed a non-monotonic growth behavior, i.e. the same voxel might record gains in electron density or Pd content across consecutive temperatures just to display a loss in the next. A behavior captured in the voxel-level growth rate distributions shown in Fig. 3 c, plotted here as a function of initial electron density for both the methane oxidation (300–750°C) and oxidizing (750–830°C) operation windows. Under methane oxidation conditions, we observed a relatively narrow distribution, with positive growth rates in smaller particles and an initially unexpected net loss in larger ones. A likely result of fragments or particle hopping events as those seen in Figs. 2 b iv-vi . Upon switching to a purely oxidizing atmosphere, the growth rate distribution becomes broader and overall positive, with enhanced growth for smaller particles. Finally, to determine the palladium transport length and migration velocity through the support, we applied a fractional volume sub-sampling approach (Fig. 4 a, Figure S12). By calculating the net electron density change within progressively smaller sub-volumes, we identified the volume size below which mass redistribution becomes detectable. For volumes larger than the palladium transport length, density changes average out; below this threshold, local gains or losses become visible. The edge length of this transition volume serves as a proxy for the maximum transport length. This analysis reveals a temperature-dependent increase in transport length under methane-rich conditions: from ~ 200 nm at 450°C to ~ 830 nm at 750°C. Heating in air to 830°C further enhances the distance to 850 nm. Using these transport lengths together with the tomogram acquisition time, we can approximate the average palladium migration velocities, which increase from ~ 30 nm h − 1 to ~ 105 nm h − 1 (Fig. 4 b). These values provide a kinetic measure of palladium redistribution and are critical for the prediction of catalyst stability and industrial catalyst body design. The velocities reveal a strong exponential temperature dependence. Accordingly, Fig. 4 c presents an Arrhenius-type plot with two distinct regimes. In air, at higher temperatures, the apparent transport activation barrier is low (~ 10 kJ mol − 1 ) and matches previous studies that have shown a size independent gas phase transport of palladium leading to strong and rapid sintering in Pd/SiO 2 catalysts. 36 Under methane oxidation conditions a substantially higher barrier of 32 kJ mol − 1 is found, reflecting the distinctly different migration/transport processes. Discussion In-situ ptychographic nanotomography enabled us to monitor the evolution of a supported catalyst across a full activation–operation–deactivation cycle, from room temperature up to 830°C under oxidizing and methane-rich atmospheres. The tomograms, encompassing hundreds of thousands of individual catalyst particles, reveal a complex and environment-dependent picture of catalyst activation, particle mobility and deactivation. During activation (25–300°C), PXCT reveals the decomposition of the palladium nitrate precursor and the formation of finely dispersed PdO nanoparticles, which are non-uniform in size and heterogeneously distributed across the silica support. Under operational methane oxidation conditions (300–750°C) two particle growth and mobility regimes are detectable. At lower temperatures, the particle growth is dominated by classical Ostwald ripening and PMC processes. Nanoparticles increase gradually in size, initially through the consumption of residual precursor material or particles with a size below the detection limit, and subsequently via the coalescence or aggregation of smaller particles. At higher temperatures, an unexpected long-range palladium redistribution process becomes dominant. This is evident by the appearance and disappearance of palladium oxide particles at spatially separated sites on the support, with inferred transport lengths reaching up to 800 nm at 750°C. This long-range migration of what looks to be entire particles exceeds the typical surface diffusion lengths and importantly migration does not always lead to immediate sintering. Instead, some Pd species appear to remain mobile without coalescing, while others condense into porous aggregates. Upon switching the sample atmosphere to air at 750°C and regardless of further heating to 830°C, the particle dynamics change markedly. The long-range mobility is suddenly strongly suppressed, and particle growth becomes again more localized. Additional larger PdO particles emerge via renewed ripening, consistent with an increased surface diffusion length under oxidizing conditions. This enhanced mobility essentially allows previously sub-resolution, or porous palladium species to migrate across the support and condense into stable, well-defined and now detectable nanoparticles. These findings indicate two distinct transport and deactivation pathways: (1) a short-range, surface-mediated coarsening process, e.g. a combination of Ostwald ripening and PCM, that governs initial nanoparticle formation and growth, and (2) a long-range particle redistribution mechanism that operates beyond the scale of conventional surface diffusion. The short-range process is both spatially confined and chemically modulated. Even at elevated temperatures, particle diameters rarely exceed ~ 15 nm, with numerous sub-6 nm PdO particles persisting adjacent to larger aggregates (Figs. 4 and S1 ) – sometimes separated by only one to two voxels – rather than merging. Assuming full precursor support surface coverage, the dominant absence of particles larger than ~ 15 nm or the diameter of a voxel allows us to estimate the effective surface mobility to be ~ 30–60 nm. This is consistent with literature reports of limited (< 100 nm) surface mobility on oxide supports. 37 We attribute this confined transport length to a chemical stabilization or strong-surface interaction under methane-rich conditions, rather than topological barriers of the support. As upon switching to a purely oxidizing atmosphere, the number of resolvable PdO voxels increases sharply, consistent with enhanced mobility driven by gas-phase–mediated Ostwald ripening at high temperatures. 36,38,39 This limited transport length and the associated growth of particles is yet sufficient to deactivate the catalyst, as the resulting decrease in surface-to-volume ratio drastically reduces the catalytically active surface area. The long-range redistribution of PdO particles is more active under methane-rich conditions. Between 300°C and 750°C, Pd‐rich voxels appear and disappear across distances of hundreds of nanometers between tomogram acquisitions, far exceeding the expected range of surface diffusion. We speculate that entire nanoparticles or small clusters detach from the support, migrate through the connected pore space and re-adsorb in new locations and eventually cluster. Based on the apparent suppression of this transport under fully oxidizing conditions, this particulate migration may be driven by redox‐induced changes in metal–support adhesion, temporarily “unlocking” particles so they can traverse the pore network. 40 We currently speculate that heterogeneity of the amorphous oxide support surface 34,41,42 as well as possible gas-phase inhomogeneities, particularly gradients in local product concentrations (e.g., H 2 O) 43 under methane oxidation conditions, may influence which particles detach from the support and become mobile or remain stable. Thus, modifying the surface by strongly binding anchor has shown to stabilize metal particles in place for methane oxidation. 40 Similar evidence for cluster mobility has been reported for Pt/TiO 2 under reactive atmospheres suggesting that long‐range particle migration may be a general phenomenon in harsh catalytic environments. 12 Furthermore, we obtained a first estimate of the velocity of long-range PdO migration, which is strongly temperature dependent and ranges from 20–100 nm h − 1 . To put this into perspective, real-life catalyst bodies are typically millimetre-sized: for instance, at a migration rate of 100 nm h − 1 a PdO particle would require ~ 1.1 years to traverse 1 mm through the support. A time scale well within the common lifetime of several years for many heterogeneous catalysts. 44,45 In combination, these observations not only query the optimal strategies to prevent catalyst deactivation but also challenge the notion that nanoparticles are inherently immobilized or only weakly mobile on support surfaces. Accordingly, strategies that rely solely on optimizing interparticle distances or initial dispersion patterns 46,47 may prove insufficient to prevent deactivation. Instead, more comprehensive approaches are needed: anchoring particles through tailored metal–support interactions 40,48,49 and designing support architectures that physically restrict mobility, e.g., via tortuosity engineering or controlled confinement may offer more robust stabilization under harsh conditions. While quantitative in-situ nanotomography facilitates a more use-representative and holistic characterisation of heterogeneous catalysts, the approach is currently bounded by spatial and temporal resolution as well as chemical specificity. These limitations currently prevent us from directly probing local metal-support interactions, 25,50,51 i.e. probe the morphology and chemistry of individual particles and the surrounding support, or the kinetics of migration events at the single-particle level. For example, while ex-situ PXRD and PXCT indicate only the presence of PdO throughout, PdO is known to autoreduce above 600°C to metallic palladium in oxygen-rich atmospheres. 52 Although such transient metallic phases are likely minor in terms of overall composition, their possible presence and relevance highlights the need for greater chemical specificity and sensitivity. Ongoing advances in instrumentation, 23,53–56 dynamic tomography, 21,57,58 and chemical imaging 20,21,28,59,60 will alleviate these limitations in the near future. Follow-up experiments at a 4th generation synchrotron, 55 will enable combining dynamic PXCT 61 with X-ray absorption spectroscopy 21 allowing real-time, chemistry specific tracking of particle evolution and metal–support interactions at previously inaccessible scales. Conclusion This study presents the first demonstration of in-situ ptychographic nanotomography of a heterogenous catalyst. By monitoring the evolution of over 100,000 individual catalyst particles in a geometry representative of their actual usage and under conditions that approach their real-world application, we revealed that catalyst deactivation is governed not only by localized coarsening via ripening and coalescence but also by long-range redistribution of entire nanoparticles across hundreds of nanometers. This atmosphere-dependent mobility revises the picture of nanoparticle stability and highlights the need for strategies that anchor particles, and engineer supports to restrict migration. The ability to bridge or even narrow the information gap between in-situ electron microscopy 3,12 and the statistical relevance of averaging in-situ methods 62 is further expected to provide new, length-scale overarching, insights in heterogeneous catalysis. Importantly, the presented approach is not limited to catalysis: its applicability extends to any reactive porous material, including battery electrodes, fuel cells, and degradation-prone nanocomposites, laying the groundwork for more predictive materials design across disciplines. Materials and Methods Materials : Nanoporous glass beads were obtained from the Bundesanstalt für Materialforschung und –Prüfung (BAM) and used as the catalyst support matrix. The beads possess an average pore diameter of 139 nm and a specific surface area of 26.6 m 2 g -1 . 24,29 Analytical grade palladium nitrate dihydrate, Pd(NO 3 ) 2 2H 2 O, was purchased from Sigma Aldrich. The synthetic gas mixture (1 mol.% CH 4 / 4 mol.% O 2 / 94 mol.% Ar) was purchased from Carbagas. P alladium Deposition/ Supported Catalyst Preparation: Pd/SiO 2 catalysts were prepared via an incipient wetness impregnation process. Specifically, 1 g of the glass beads were first immersed in a Pd(NO 3 ) 2 solution (12.7 mg mL -1 ) prepared using MiliQ water. The resulting slurry was next transferred into a vacuum desiccator to fully infiltrate the pores with the Pd solution. To then anchor the Pd species on the support surface and evaporate water we removed the beads from the solution and placed them into a preheated oven for 10 min at 200˚C. This process was repeated 6 times yielding a Pd/SiO 2 catalyst with a theoretical Pd loading of 2.9 wt.% based on a monolayer coverage in each cycle. A comparison of the integrated electron density between tomograms of the bare and loaded support suggests an average Pd loading of ~ 1 wt.%, assuming the density increase results solely from the added precursor. The lower-than-expected value suggests that precursor deposition was incomplete and uneven across the support. This is supported by Figure 1d, which shows extended regions where no Pd signal is detected. General Material Characterization Catalytic Activity Tests: Methane oxidation tests were conducted using a combined microreactor and mass spectrometry system (Hiden Analytical), consisting of a heated quartz reactor tube (3 mm inner diameter) coupled to a mass spectrometer. For each experiment, 10 mg of the supported catalyst (crushed beads, 125–250 µm in diameter) were loaded between two quartz wool plugs inside the reactor. The reactor was flushed with helium (50 mL min⁻¹), and the catalyst was then heated to 300 °C at a rate of 5 °C min⁻¹ under helium flow. Upon reaching 300 °C, the catalyst was exposed to a reaction gas mixture containing 1 mol% CH₄, 4 mol% O₂, and 94 mol% He at a total flow rate of 50 mL min⁻¹ for 8 hours, corresponding to the PXCT tomogram acquisition time. Under these conditions, carbon dioxide and water were the only detectable reaction products. Activity or Methane conversion degree was calculated as stated in Equation (1): In follow-up experiments, the same protocol was applied with additional thermal ageing steps. After the initial 300 °C exposure, the catalyst was heated to 450 °C and held under reaction conditions for 8 hours. It was then cooled to 300 °C, and the catalytic activity was re-evaluated. This procedure was repeated for 550 °C, 650 °C, and 750 °C treatments. Catalyst deactivation was calculated from the loss in conversion at 300 °C after each thermal step, as described in Equation (2): Following each test cycle, a fraction of the spent catalyst was retrieved and analysed by STEM and XRD to track nanoparticle sintering, phase evolution, and structural degradation associated with deactivation. Powder X-ray diffraction (PXRD): Powder X-ray diffraction (PXRD) data were acquired using a Cu-K alpha radiation source with a scan step size of 0.02 2theta (Figure S3). Instrument broadening was accounted for. Electron Microscopy: Scanning electron micrographs (SEM) were acquired using a Zeiss NVision-40. The scanning transmission electron micrographs (STEM) were acquired with an aberration-corrected Hitachi HD-2700CS microscope operated at 200 kV. High-angle annular dark-field (HAADF) images were acquired to facilitate compositional and morphological interpretation. Operando Ptychographic Tomography Tomography Sample Preparation: To prepare the PXCT examined sample pillar we mounted a single, millimetre-sized, empty glass bead on top of an aluminium tomography pin using a carbon adheasive. 63 The pin was then placed in a furnace preheated to 200 °C and held for 90 minutes to fully cure the adhesive. After curing, the bead was shaped into a cylindrical pillar (~30 µm diameter, ~50 µm height) using a micro-lathe. 26 The upper portion of this pillar was subsequently thinned to ~7 µm in diameter via focused ion beam (FIB) milling (Supplementary Fig. S4). The resulting glass pillar was then subjected to the catalyst preparation procedure outlined above. Ptychographic X-ray Computed Tomography (PXCT) is the combination of ptychography and X-ray computed tomography. 13–15 Ptychography is a lensless coherent imaging technique where the sample is scanned across a coherent X-ray beam and a diffraction image is acquired at each scanning position. By ensuring that the neighbouring beam illuminations overlap with each other, the resulting redundancy encoded within the diffraction images enables the reconstruction of both the sample and the X-ray beam through iterative optimization algorithms. 15 By performing ptychography at multiple sample rotation angles, the resulting ptychographic projections enable tomographic reconstructions of both phase and amplitude contrast with nanometre resolution, ideal for local component identification in functional materials. 19,21,30,31 The phase tomogram when acquired away from sample-relevant X-Xray absorption edges can be converted to a value absolute electron density tomogram. 30 PXCT 13,14 experiments were carried out 6.2 keV at the cSAXS beamline of the Swiss Light Source, Paul Scherrer Institut, Switzerland. The photon energy was selected using a double-crystal Si(111) monochromator. The horizontal aperture slits, located 22 m upstream of the sample was set to 20 μm in width, to create a horizontal virtual source point that coherently illuminated a Fresnel zone-plate, 200 μm in diameter, with an outermost zone width of 60 nm. The Fresnel zone-plate was designed with locally displaced zones to improve imaging quality. 64 Coherent diffraction patterns were acquired using an in-vacuum Eiger 1.5M area detector, with a 75 µm pixel size, placed 5.225 m downstream of the sample inside in an evacuated flight tube. For sample positioning and environment regulation we used the flexible tOMography Nano Imaging endstation (flOMNI) 29,65 with modifications for environmental control. 23 For achieving fast scanning speeds a Fresnel zone plate scanner utilizing a combined motion of sample and illuminating FZP was used. 66 The field of view of each projection, or ptychographic scan, was 11 x 7 μm 2 (width x height). The sample was scanned using a Fermat-spiral scanning pattern with an average step size of 0.7 µm. The exposure time per scanning point was 0.05 seconds. For each ptychographic scan or image reconstruction, a detector region of 900 × 900 pixels was used, resulting in a reconstructed image pixel size of 15.48 nm. Reconstructions were performed using the PtychoShelves package 67 with 500 iterations of the difference map algorithm 13 followed by 600 iterations of maximum likelihood refinement. 68 All the tomograms mentioned in the main text were reconstructed using ~550 ptychographic projections, sufficient for a tomogram spatial resolution of 20 nm for a 7 µm (non-porous) sample according to the Crowther criterion. Tomography projection acquisition followed a nested approach, specifically we acquired 30 equally spaced projections over 180º at a time and then repeated the acquisition with an angular offset based on the golden ratio. The approach was chosen to accommodate possible sample stabilization delays. Following ptychographic image reconstruction and alignment of the projections, tomograms for each environmental condition were reconstructed separately by first aligning the projections, 69 followed by tomogram reconstruction using a modified filtered back-projection algorithm (FBP). 70 To investigate nanoparticle formation, mobility and catalyst deactivation we examined the prepared sample pillar across 9 environmental conditions. In sequence, we examined the pillar (1-2) at 25˚C and 300˚C under a constant flow of air, (3-7) at 300˚C, 450˚C, 550˚C, 650˚C and 750˚C under of a constant flow of a methane gas mixture (1 mol.% CH 4 / 4 mol.% O 2 / 94 mol.% Ar), and (8-9) at 750˚C and 830˚C under a constant flow of air. See Supplementary Figure 1 for a graphical representation of the tested conditions and associated catalyst performance. Using the environmental control system 23 integrated mass flow controllers we ensured that the gas flow across measurements was kept constant. The flow rate was set to 1 L min -1 . While tomogram acquisition commenced after a 30 minute wait period after each change in environmental condition, we excluded the 6 initially acquired sub-sets of projections from the tomogram reconstruction of a given environmental condition. This exclusion introduced a sample stabilization or thermodynamic equilibration time of ~2.0 hours per condition and tomogram acquisition. Tomogram Dose Estimation: The imparted X-ray dose during a single tomogram acquisition was estimated to be on the order of ~ 10 8 Gy. The estimated dose is based on the average area flux density of each ptychographic scan and the mass density of the specimen. 71 For this calculation the sample was assumed to consist entirely of silica. Tomogram Spatial Resolution Evaluation: Tomogram analysis was performed solely on the phase component of the acquired PXCT datasets, due to its superior spatial-resolution and signal-to-noise ratio at the selected X-ray energy. 60,72 Spatial resolution estimates for each of the reconstructed tomograms were obtained using Fourier shell correlation (FSC). 73 The acquired projections per conditions were alternatively separated into two sets and individually reconstructed. To estimate the tomogram average spatial resolution, we then calculated the correlation function between these two tomograms in the Fourier domain. The achieved resolution is estimated based on the first intersection of the correlation function with the half-bit threshold criteria (Figure S5). The tomogram spatial resolution averaged across all environmental conditions according to FSC is 35 nm. Voxel-level Electron Density Uncertainty: To estimate the error of the retrieved electron density, we calculated the standard deviation (σ) of a region of air/argon surrounding the imaged pillar. Assuming the region to possess a uniform known density. The average electron density uncertainty was calculated to be ~0.008 n e Å - ³. Tomogram Analysis Tomogram analysis and 3D rendering were performed using in-house developed Matlab routines or using Avizo. Prior to analysis, the tomograms were registered via a subpixel image registration approach using a mutual information metric and resampled onto a common gird. Tomography analysis was limited to a common sample volume present in all acquired tomograms. 23 Further, to exclude possible FIB sample preparation artefacts from the tomogram analysis we excluded the outermost micrometre of the imaged sample cylinder from analysis. Pore Analysis: Isolated pores and pore networks were identified through threshold-based segmentation of the electron density tomograms. An upper electron density threshold of 0.28 e⁻ Å⁻³ was applied. The threshold, selected in view of the electron density of the silica support (0.56 n e Å - ³ Table S1), classifies all voxel which are at minimum filled with 50 vol.% with air or argon as pores. Silica is the lightest material in the sample. The isolated volumes were then subjected to a morphological closing operation to refine the segmentation and following to 3D thickness map calculations to retrieve a pore size distribution for each tomogram/ environmental condition. Shown in Supplementary Figure 8 are a subset of the obtained, volume-weighted, pore diameter distributions. Pores with diameters below 50 nm were excluded from the thickness map analysis. Effect of the Wet Impregnation Process on the Silica Support Structure: To evaluate whether the Pd impregnation process altered the silica support structure, and to establish a baseline for histogram interpretation and Pd feature identification, a tomogram of the pure silica support material was acquired prior to catalyst loading. Figure S13 presents a comparison of electron density histograms extracted from tomograms of the silica support before and after wet impregnation. Extraction and Analysis of Environment Induced Sample Changes: Following the spatial registration and resampling of the tomograms onto a common grid, we segmented the sample into two principal components: the silica support and voxels at one point occupied by Pd across the measurement series. To isolate the silica support from the pore space, we applied a lower threshold of 0.28 n e Å - ³ and an upper threshold of 0.8 n e Å⁻³. Values were informed by the electron density histogram of the bare support, Figure S13. Voxels with densities exceeding 0.8 n e Å⁻³ were classified as Pd-containing, corresponding to a minimum voxel occupancy of 15 vol% PdO, Figure S9. This separation allows us then to monitor evolution both support and the growth and mobility of already existing or newly forming nanoparticles. (1) Silica Support Changes and Metal-Support Interactions. Having isolated the support in all tomograms we first confirmed that the silica support did not undergo spatial deformation on the observable level (Table S1 and Figure S8 – Pore Size Distribution) over the course of the measurement series. This justifies the use of a constant support mask for the succeeding Pd nanoparticle analysis steps. While no spatial deformation of the support was detected, minor electron density changes of radial and environmental dependency were detectable, Figure S6 & 7. 21 We currently believe these changes to stem from the removal of oxygen vacancies from the silica support. (2) Pd Nanoparticle Formation, Growth, and Migration . To track the evolution of Pd particles across the measurement series, we first generated a “Pd location mask” by summing all segmented tomograms. This produced a binary map identifying all voxels that contained Pd at any point during the experiment. The resulting mask was then applied to all tomograms to enable voxel-wise analysis across conditions. To provide a first qualitative impression of particle growth and mobility, we subtracted tomograms acquired under adjacent environmental conditions (e.g., subtracting the 450 °C tomogram from the 550 °C tomogram). The resulting differential maps, visualized using a divergent colormap scaled across the full dataset, highlight regions of Pd accumulation and depletion (Figure 2, Movie S1). For quantitative analysis (Figure 3, Movie S3), we evaluated the electron density of each Pd-containing voxel individually across the series. This voxel-level analysis allowed us to determine growth and dissolution rates, as well as the fraction of stationary versus transient Pd-occupied voxels. Being a voxel-level analysis and as a dominant fraction of the initially present and newly forming Pd particles are smaller than the spatial resolution, growth rates here refer to net Pd density fluctuations within individual voxels. (3) Transport length. To estimate the volume or distance over which Pd can migrate within the support under the tested conditions, we employed a volume-subsampling approach. A central volume of approximately 40 µm³ was used for this analysis. The previously defined Pd-location mask was applied to this volume to exclude contributions from the silica support. For each environmental condition in the measurement series, we calculated the integrated electron density within this volume. By incrementally subsampling this region into smaller nested volumes and performing the same integration, we identified changes in the rate of electron density gain or loss as a function of volume size. The key assumption is that, for a fixed condition, the rate of Pd accumulation or depletion should remain constant across nested volumes -unless Pd species begin migrating into or out of that volume. A deviation in growth rate exceeding ±5% between adjacent sub-volumes was used as a cut-off to define the maximum effective transport distance under each condition. Declarations Acknowledgements General: PXCT experiments were performed at the coherent small-angle x-ray scattering (cSAXS) beamline of the Swiss Light Source (SLS). The construction of the utilized instrumentation was supported by the Swiss National Science Foundation (SNF) (R′EQUIP, 145056, OMNY) and the Competence Centre for Materials Science and Technology (CCMX) of the ETH-Board. We thank X. Donath and L. Heller for technical support. Electron microscopy work was performed at the Scientific Centre for Optical and Electron Microscopy (ScopeM) at ETH Zurich and the Electron Microscopy Facility at PSI. We want to thank F. Krumeich from ETH Zurich for his STEM measurements of the powder catalyst samples. We further would like to thank E. A. Mueller Gubler and J. Reuteler for assistance with the FIB sample preparation. Finally, we thank the anonymous reviewers of an earlier version of this manuscript for suggestions that helped improve the data analysis and framing. Funding: A.B., T.A. and J.I. are funded by the Swiss National Science Foundation (SNF), Project Numbers 200021_178943, 200021_196898 and PZ00P2_179886. Author Contributions: A.B., M.H. and J.I. conceived the study. M.H. designed and led the construction of the environmental control system. T.A., M.G.S., M.H. and J.I. performed PXCT experiments. T.A. and J.I. reconstructed tomograms. A.B. and J.I. analysed data. A.B. prepared samples, performed performance tests. A.B. and F.K. performed electron microscopy experiments. A.B. and J.I. wrote the manuscript. Ethics declarations: The authors declare no financial, ethical or other competing interests relating to the contents of the manuscript. Data Availability: Data needed to evaluate the presented conclusions are provided in the manuscript and/or the Supplementary Materials. The raw data and reconstructed projections can be accessed at the following address, doi.xyz ( to be populated during final manuscript revisions ), or obtained from the corresponding authors upon reasonable request. Code Availability: The code and scripts developed and used for this study can be accessed at the following address https://www.psi.ch/en/sls/csaxs/software, or obtained from the corresponding authors upon reasonable request. References Schlögl, R. Heterogeneous Catalysis. Angewandte Chemie - International Edition 54 , 3465–3520 (2015). Lox, E. S. J. Automotive Exhaust Treatment. in Handbook of Heterogeneous Catalysis 2274–2345 (Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany, 2008). doi:10.1002/9783527610044.hetcat0120. Aitbekova, A. et al. Templated encapsulation of platinum-based catalysts promotes high-temperature stability to 1,100 °C. Nature Materials 21 , 1290–1297 (2022). Martín, A. J., Mitchell, S., Mondelli, C., Jaydev, S. & Pérez-Ramírez, J. Unifying views on catalyst deactivation. Nature Catalysis 5 , 854–866 (2022). Hansen, T. W., DeLaRiva, A. T., Challa, S. R. & Datye, A. K. Sintering of Catalytic Nanoparticles: Particle Migration or Ostwald Ripening? Accounts of Chemical Research 46 , 1720–1730 (2013). Oh, J., Boucly, A., van Bokhoven, J. A., Artiglia, L. & Cargnello, M. Palladium Catalysts for Methane Oxidation: Old Materials, New Challenges. Accounts of Chemical Research (2023) doi:10.1021/acs.accounts.3c00454. Datye, A. K. & Votsmeier, M. Opportunities and challenges in the development of advanced materials for emission control catalysts. Nature Materials 20 , 1049–1059 (2021). Xu, Q., Kharas, K. C., Croley, B. J. & Datye, A. K. The Sintering of Supported Pd Automotive Catalysts. ChemCatChem 3 , 1004–1014 (2011). Tait, S. L., Ngo, L. T., Yu, Q., Fain, S. C., Jr. & Campbell, C. T. Growth and sintering of Pd clusters on α-Al2O3(0001). J. Chem. Phys. 122 , 064712 (2005). Kawaguchi, T. et al. Gas-Induced Segregation in Pt-Rh Alloy Nanoparticles Observed by In Situ Bragg Coherent Diffraction Imaging. Phys. Rev. Lett. 123 , 246001 (2019). Smith, J. et al. Sintering Mechanism of Pt/Al2O3 in Complex Emission Gases Elucidated via In Situ Environmental STEM. ACS Materials Lett. 3301–3311 (2024) doi:10.1021/acsmaterialslett.4c00422. Frey, H., Beck, A., Huang, X., van Bokhoven, J. A. & Willinger, M. G. Dynamic interplay between metal nanoparticles and oxide support under redox conditions. Science 376 , 982–987 (2022). Thibault, P. et al. High-Resolution Scanning X-ray Diffraction Microscopy. Science 321 , 379–382 (2008). Dierolf, M. et al. Ptychographic X-ray computed tomography at the nanoscale. Nature 467 , 436–439 (2010). Miao, J., Ishikawa, T., Robinson, I. K. & Murnane, M. M. Beyond crystallography: Diffractive imaging using coherent X-ray light sources. Science 348 , 530–535 (2015). Sheppard, T. L. et al. In Situ Multimodal 3D Chemical Imaging of a Hierarchically Structured Core@Shell Catalyst. Journal of the American Chemical Society 139 , 7855–7863 (2017). Ihli, J. et al. Hierarchical Structure of NiMo Hydrodesulfurization Catalysts Determined by Ptychographic X-Ray Computed Tomography. Angewandte Chemie - International Edition 59 , 17266–17271 (2020). Fam, Y. et al. Correlative Multiscale 3D Imaging of a Hierarchical Nanoporous Gold Catalyst by Electron, Ion and X‐ray Nanotomography. ChemCatChem 10 , 2858–2867 (2018). Ihli, J. et al. A three-dimensional view of structural changes caused by deactivation of fluid catalytic cracking catalysts. Nature Communications 8 , (2017). Hirose, M. et al. Oxygen-diffusion-driven oxidation behavior and tracking areas visualized by X-ray spectro-ptychography with unsupervised learning. Communications Chemistry 2 , 1–7 (2019). Gao, Z. et al. Sparse ab initio x-ray transmission spectrotomography for nanoscopic compositional analysis of functional materials. Science Advances 7 , 1–12 (2021). Weber, S. et al. Evolution of Hierarchically Porous Nickel Alumina Catalysts Studied by X-Ray Ptychography. Advanced Science 9 , 1–12 (2022). Holler, M. et al. Environmental control for X-ray nanotomography. Journal of Synchrotron Radiation 29 , 1223–1231 (2022). BAM Federal Institute for Materials Research and Testing SS, Germany, E. reference material E. F. 2000 [cited]Available from: http://www.bam.de/de/rm-certificates_media/rm_cert_porous_materials/erm_fd120_121_122rep.pdf. No Title . Reddy, G. K., Ling, C., Peck, T. C. & Jia, H. Understanding the chemical state of palladium during the direct NO decomposition-influence of pretreatment environment and reaction temperature. RSC Advances 7 , 19645–19655 (2017). Holler, M. et al. A lathe system for micrometre-sized cylindrical sample preparation at room and cryogenic temperatures. Journal of Synchrotron Radiation 27 , 472–476 (2020). Celestre, R. et al. Nanosurveyor 2: A Compact Instrument for Nano-Tomography at the Advanced Light Source. Journal of Physics: Conference Series 849 , 012047 (2017). Michelson, A. et al. Three-dimensional visualization of nanoparticle lattices and multimaterial frameworks. Science 376 , 203–207 (2022). Holler, M. et al. X-ray ptychographic computed tomography at 16 nm isotropic 3D resolution. Scientific Reports 4 , 3857 (2015). Diaz, A. et al. Quantitative x-ray phase nanotomography. Physical Review B 85 , 020104 (2012). Ihli, J. et al. Ptychographic X-ray tomography reveals additive zoning in nanocomposite single crystals. Chemical Science 11 , 355–363 (2020). Munde, M. S., Gao, D. Z. & Shluger, A. L. Diffusion and aggregation of oxygen vacancies in amorphous silica. J. Phys.: Condens. Matter 29 , 245701 (2017). Sacks, M. D. & Tseng, T.-Y. Preparation of SiO2 Glass from Model Powder Compacts: I, Formation and Characterization of Powders, Suspensions, and Green Compacts. Journal of the American Ceramic Society 67 , 526–532 (1984). Yu, X. et al. Anchoring PdOx clusters on defective alumina for improved catalytic methane oxidation. Nat Commun 15 , 6494 (2024). Ostwald, W. Studien über die Bildung und Umwandlung fester Körper. Zeitschrift für Physikalische Chemie 22U , 289–330 (1897). Goodman, E. D. et al. Size-controlled nanocrystals reveal spatial dependence and severity of nanoparticle coalescence and Ostwald ripening in sintering phenomena. Nanoscale 13 , 930–938 (2021). Li, L. et al. Modeling the Migration of Platinum Nanoparticles on Surfaces Using a Kinetic Monte Carlo Approach. J. Phys. Chem. C 121 , 4261–4269 (2017). Plessow, P. N. & Abild-Pedersen, F. Sintering of Pt Nanoparticles via Volatile PtO 2 : Simulation and Comparison with Experiments. ACS Catalysis 6 , 7098–7108 (2016). Oh, J. et al. Colloidally Engineered Pd and Pt Catalysts Distinguish Surface- and Vapor-Mediated Deactivation Mechanisms. ACS Catalysis 1812–1822 (2023) doi:10.1021/acscatal.2c04683. Becker, M., Frey, H., Batool, S. R., Van Bokhoven, J. A. & Beck, A. Al-anchored platinum catalysts on reducible supports: High-temperature stability against redispersion during methane oxidation. Applied Catalysis B: Environment and Energy 373 , 125323 (2025). Goodman, E. D. et al. Catalyst deactivation via decomposition into single atoms and the role of metal loading. Nature Catalysis 2 , 748–755 (2019). Lee, J. et al. Aggregation of CeO 2 particles with aligned grains drives sintering of Pt single atoms in Pt/CeO 2 catalysts. Journal of Materials Chemistry A 10 , 7029–7035 (2022). Kočí, P., Štěpánek, F., Kubíček, M. & Marek, M. Modelling of micro/nano-scale concentration and temperature gradients in porous supported catalysts. Chemical Engineering Science 62 , 5380–5385 (2007). Barrow, N. et al. Doubling the life of Cu/ZnO methanol synthesis catalysts via use of Si as a structural promoter to inhibit sintering. Science Advances 10 , 1–12 (2024). Moulijn, J. A., Van Diepen, A. E. & Kapteijn, F. Catalyst deactivation: is it predictable? What to do? Applied Catalysis A: General 212 , 3–16 (2001). Goodman, E. D., Schwalbe, J. A. & Cargnello, M. Mechanistic Understanding and the Rational Design of Sinter-Resistant Heterogeneous Catalysts. ACS Catalysis 7 , 7156–7173 (2017). Holm, A. et al. Nanoscale Spatial Distribution of Supported Nanoparticles Controls Activity and Stability in Powder Catalysts for CO Oxidation and Photocatalytic H 2 Evolution. Journal of the American Chemical Society 142 , 14481–14494 (2020). van Deelen, T. W., Hernández Mejía, C. & de Jong, K. P. Control of metal-support interactions in heterogeneous catalysts to enhance activity and selectivity. Nature Catalysis 2 , 955–970 (2019). Yang, Q. et al. Single Carbon Vacancy Traps Atomic Platinum for Hydrogen Evolution Catalysis. Journal of the American Chemical Society 144 , 2171–2178 (2022). Beck, A. et al. The dynamics of overlayer formation on catalyst nanoparticles and strong metal-support interaction. Nature Communications 11 , 3220 (2020). Tauster, S. J., Fung, S. C., Baker, R. T. K. & Horsley, J. A. Strong-Interactions in Supported-Metal Catalysts. Science 211 , 1121–1125 (1981). Salomonsson, P., Johansson, S. & Kasemo, B. Methane oxidation over PdOx : on the mechanism for the hysteresis in activity and oxygen content. Catal Lett 33 , 1–13 (1995). Becher, J. et al. Sample Environment for Operando Hard X-ray Tomography—An Enabling Technology for Multimodal Characterization in Heterogeneous Catalysis. Catalysts 11 , 459 (2021). Sidorenko, P. & Cohen, O. Single-shot ptychography. Optica 3 , 9 (2016). Streun, A. et al. SLS-2 – the upgrade of the Swiss Light Source. Journal of Synchrotron Radiation 25 , 631–641 (2018). Raimondi, P. ESRF-EBS: The Extremely Brilliant Source Project. Synchrotron Radiation News 29 , 8–15 (2016). García-Moreno, F. et al. Tomoscopy: Time-Resolved Tomography for Dynamic Processes in Materials. Advanced Materials 33 , (2021). Zhang, J., Lee, W. K. & Ge, M. Sub-10 second fly-scan nano-tomography using machine learning. Communications Materials 3 , 1–9 (2022). Lo, Y. H. et al. X-ray linear dichroic ptychography. Proceedings of the National Academy of Sciences of the United States of America 118 , 1–8 (2021). Gao, Z. et al. Nanoscale crystal grain characterization: Via linear polarization X-ray ptychography. Chemical Communications 56 , 13373–13376 (2020). Gao, Z. et al. Dynamic sparse x-ray nanotomography reveals ionomer hydration mechanism in polymer electrolyte fuel-cell catalyst. Science Advances 10 , eadp3346 (2024). Beck, A. et al. Following the structure of copper-zinc-alumina across the pressure gap in carbon dioxide hydrogenation. Nature Catalysis 4 , 488–497 (2021). Holler, M. et al. OMNY PIN - A versatile sample holder for tomographic measurements at room and cryogenic temperatures. Review of Scientific Instruments 88 , (2017). Odstrčil, M., Lebugle, M., Guizar-Sicairos, M., David, C. & Holler, M. Towards optimized illumination for high-resolution ptychography. Opt. Express, OE 27 , 14981–14997 (2019). Holler, M. & Raabe, J. Error motion compensating tracking interferometer for the position measurement of objects with rotational degree of freedom. Optical Engineering 54 , 054101 (2015). Odstrcil, M., Lebugle, M., Lachat, T., Raabe, J. & Holler, M. Fast positioning for X-ray scanning microscopy by a combined motion of sample and beam-defining optics. J Synchrotron Rad 26 , 504–509 (2019). Wakonig, K. et al. PtychoShelves, a versatile high-level framework for high-performance analysis of ptychographic data. Journal of Applied Crystallography 53 , 574–586 (2020). Thibault, P. & Guizar-Sicairos, M. Maximum-likelihood refinement for coherent diffractive imaging. New Journal of Physics 14 , (2012). Odstrčil, M., Holler, M., Raabe, J. & Guizar-Sicairos, M. Alignment methods for nanotomography with deep subpixel accuracy. Optics Express 27 , 36637 (2019). Guizar-Sicairos, M. et al. Phase tomography from x-ray coherent diffractive imaging projections. Optics Express 19 , 21345 (2011). Howells, M. R. et al. An assessment of the resolution limitation due to radiation-damage in X-ray diffraction microscopy. Journal of Electron Spectroscopy and Related Phenomena 170 , 4–12 (2009). Ihli, J. et al. Resonant Ptychographic Tomography Facilitates Three-Dimensional Quantitative Colocalization of Catalyst Components and Chemical Elements. Journal of Physical Chemistry C 122 , 22920–22929 (2018). Van Heel, M. & Schatz, M. Fourier shell correlation threshold criteria. Journal of Structural Biology 151 , 250–262 (2005). Holler, M. et al. An instrument for 3D x-ray nano-imaging. Review of Scientific Instruments 83 , (2012). Gooch, J. W. Silica, amorphous [MAK Value Documentation, 1991]. in The MAK-Collection for Occupational Health and Safety 158–179 (Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany, 2012). doi:10.1002/3527600418.mb763186e0002. Additional Declarations There is NO Competing Interest. 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2","display":"","copyAsset":false,"role":"figure","size":637277,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIn-situ Ptychographic Nanotomography of a Pd/SiO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e Catalyst.\u0026nbsp; \u003c/strong\u003e(a) In-situ tomogram extracted, and frequency normalized electron density (n\u003csub\u003ee\u003c/sub\u003e Å\u003csup\u003e-3\u003c/sup\u003e) histograms. Shown is the gradual evolution of the catalyst structure and composition as a function of temperature and atmosphere. Provided is a linear (left) and log-scale (right) representation of the histograms. The nominal electron densities of the main catalyst’s components and the tomogram segmentation threshold (\u003cstrong\u003e-\u003c/strong\u003e) utilized in the classification of support and Pd-rich voxel are provided. (b) Concept of difference electron density tomograms. (c) Shown is a series of volume renderings depicting the location and evolution of Pd-rich or particle carrying voxels in the examined sample volume. Specifically shown is the difference between adjacent environmental conditions. Increases in ED, corresponding to nanoparticle growth or movement to a specific location, are depicted using a colour map ranging from orange to red. Conversely, decreases in ED, corresponding to disintegration or a particle migrating away from its original location, are depicted using a colour map ranging from blue to green. The scalebar is 1000 nm.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7914877/v1/ee4894a9abd9339e6dbef5d9.png"},{"id":95182044,"identity":"d52d1f1c-9fba-489b-b229-2d2e32a0e470","added_by":"auto","created_at":"2025-11-05 08:37:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":230585,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMobility of Palladium Particles in the Supported Catalyst.\u003c/strong\u003e \u0026nbsp;(a) Provided are virtual cuts through the 4D tomogram showing the location of voxels permanently (stationary particles) and temporarily (transient particles) occupied by palladium particles. Voxels that consistently display an electron density greater than 0.8 n\u003csub\u003ee\u003c/sub\u003e Å\u003csup\u003e-3\u003c/sup\u003e from the first temperature at which this threshold was reached are classified as permanently occupied by palladium particle(s), the remainder as temporarily occupied. Locations are shown on top of the silica support (grey). The scalebar is 1000 nm. (b) Analysis of the permanently and temporarily occupied voxel. Plotted is the number of stationary and mobile palladium particles as a function of temperature and atmosphere. Further provided the evolution of the population-average particle diameter, both for the stationary and mobile palladium particles. The error bars represent the measured electron density standard deviation. (c) Kernel density plots showing the voxel-level growth rate (n\u003csub\u003ee\u003c/sub\u003e Å\u003csup\u003e-3\u003c/sup\u003e ºC\u003csup\u003e -1\u003c/sup\u003e) distribution of stationary Pd-rich voxel (\u0026gt;0.8 n\u003csub\u003ee\u003c/sub\u003e Å\u003csup\u003e-3\u003c/sup\u003e) as a function of initial particle size or electron density. The relationship is plotted for methane oxidation and the purely oxidizing operation windows. Included are particles initially present in the sample and those that have formed at elevated temperatures. Growth rates, represent a linear fit across the considered temperature range.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7914877/v1/a8ca6fd172fcfa0fd9ac638c.png"},{"id":95182046,"identity":"2af8627d-ce60-4be1-8be5-7e773ed950f6","added_by":"auto","created_at":"2025-11-05 08:37:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":107996,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTransport Length and Migration Velocity. \u003c/strong\u003e(a) Palladium transport volume, correlated subvolume edge length, and migration velocity as a function of temperature and atmosphere. (b) Derived Arrhenius-type plots for the migration velocity. Details on the calculation of the traverse volume by sub-volume sampling can be found in Supplementary Figure S12. In short: A central volume was iteratively sub-sampled into progressively smaller sub-volumes. For each sub-volume, the integrated electron density change (ΔED) across a defined temperature window was then calculated. The maximum Pd displacement length is inferred from the smallest sub-volume size at which a ≥5% deviation in normalized ΔED appears, indicating non-local Pd redistribution.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7914877/v1/9879c377c7a11dd4ce6850f7.png"},{"id":95312208,"identity":"da67c0ac-6d53-49fa-9a71-530e0faee133","added_by":"auto","created_at":"2025-11-06 15:48:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2272077,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7914877/v1/99641995-48a5-474c-a471-1a60adfa4b10.pdf"},{"id":95182055,"identity":"db6e8149-aff2-4b75-a0f3-77c546c8c7dc","added_by":"auto","created_at":"2025-11-05 08:37:47","extension":"avi","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":21759134,"visible":true,"origin":"","legend":"Supporting Movie S3","description":"","filename":"MovieS3.avi","url":"https://assets-eu.researchsquare.com/files/rs-7914877/v1/3321b213967303c57e8cb78f.avi"},{"id":95182042,"identity":"665a34c9-53cd-4fbf-8346-e5008084422d","added_by":"auto","created_at":"2025-11-05 08:37:47","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2239459,"visible":true,"origin":"","legend":"Cover Art Suggestion","description":"","filename":"CoverArt.png","url":"https://assets-eu.researchsquare.com/files/rs-7914877/v1/b2c078259087488b7c9ff9fc.png"},{"id":95182066,"identity":"5195c5a3-ab5e-47ff-9516-5b8622fac0e4","added_by":"auto","created_at":"2025-11-05 08:37:48","extension":"avi","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":29225306,"visible":true,"origin":"","legend":"Supporting Movie S4","description":"","filename":"MovieS4.avi","url":"https://assets-eu.researchsquare.com/files/rs-7914877/v1/5d01f370ad6a2c6c6b315cec.avi"},{"id":95182092,"identity":"135286e0-fcf1-40b3-93ee-6fcfc01e2154","added_by":"auto","created_at":"2025-11-05 08:37:51","extension":"avi","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":305040756,"visible":true,"origin":"","legend":"Supporting Movie S2","description":"","filename":"MovieS2.avi","url":"https://assets-eu.researchsquare.com/files/rs-7914877/v1/a80d7e7bb1fa524824ca624d.avi"},{"id":95182093,"identity":"a070b7fb-4f7e-4fa3-9c29-28144db5b950","added_by":"auto","created_at":"2025-11-05 08:37:56","extension":"avi","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":565929604,"visible":true,"origin":"","legend":"Supporting Movie S1","description":"","filename":"MovieS1.avi","url":"https://assets-eu.researchsquare.com/files/rs-7914877/v1/18e0705e342eb0b9eddc60b2.avi"},{"id":95227242,"identity":"246d2de8-9aff-44d6-bb2f-bd11d36a0336","added_by":"auto","created_at":"2025-11-05 16:32:17","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":2938193,"visible":true,"origin":"","legend":"","description":"","filename":"TheSupplementaryInformationcontains.docx","url":"https://assets-eu.researchsquare.com/files/rs-7914877/v1/eb1edbfeab5addc86d7cd035.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"In-Situ Ptychographic Nanotomography Captures Activation, Mobility, and Deactivation of Supported Catalysts","fulltext":[{"header":"One-Sentence Summary","content":"\u003cp\u003eUnderstanding and preventing the loss of active surface area in supported catalysts due to transport and sintering processes remains an industrial-scale challenge. Here, using in-situ ptychographic nanotomography, we track the formation, mobility and aggregation of 100,000s of catalyst nanoparticles in a supported catalyst under operating conditions.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eHeterogeneous catalysts are central pillars of the chemical industry and essential to energy and chemical production as well as environmental remediation.\u003csup\u003e1\u003c/sup\u003e While certain levels of catalytic activity and selectivity are application requirements, industrial and economic viability is often determined by a catalyst\u0026rsquo;s longevity. Supported catalysts are a prime example of this, finding, for example, application in automobiles for the remediation of exhaust gases.\u003csup\u003e2\u003c/sup\u003e Here, catalytically active nanoparticles, often palladium, are finely dispersed on the surface of a porous support, and are used to transform unburned hydrocarbons and carbon monoxide to carbon dioxide.\u003csup\u003e2\u003c/sup\u003e During this transformation, and for years on end, the catalyst is exposed to high temperatures (\u0026gt;\u0026thinsp;400\u0026deg;C), which results in a high catalytic activity, but gradually deactivates the catalyst.\u003csup\u003e3\u003c/sup\u003e This deactivation, as in many other catalysts, stems from the loss of active surface area.\u003csup\u003e4\u003c/sup\u003e In supported catalysts, this loss in surface area is typically caused either by Ostwald ripening, where smaller particles dissolve and redeposit onto larger ones, or by particle migration and coalescence (PMC) processes, where entire particles move across the support surface and then fuse.\u003csup\u003e5,6\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eCharacterization of these degradation processes and their prevention remain a major industrial-scale challenge. In-depth studies yet remain particularly difficult, requiring the observation of thousands of nanoparticles, \u0026lt;\u0026thinsp;10 nm in diameter, within the confines of millimetre-sized, use-representative catalyst architectures and under application conditions.\u003csup\u003e7\u003c/sup\u003e Traditional, ensemble-averaging in-situ techniques, such as X-ray diffraction and spectroscopy, remain invaluable for identifying bulk structural changes and average chemical states, but provide limited insight into local heterogeneities, spatial dependencies, and particle migration dynamics.\u003csup\u003e8\u003c/sup\u003e High-resolution imaging methods, in contrast, can provide these and allow for a more detailed understanding of catalyst behaviour, including the mobility of individual nanoparticles.\u003csup\u003e9\u0026ndash;11\u003c/sup\u003e For example, using in-situ transmission electron microscopy, we showed that the nanoparticles in a supported catalyst can become highly mobile under reaction conditions, questioning a previously suggested pure and local Ostwald Ripening driven deactivation.\u003csup\u003e12\u003c/sup\u003e However, transmission electron microscopy is constrained to sub-micron sample volumes\u003csup\u003e5\u003c/sup\u003e and commonly involves destructive sample preparation steps to obtain electron transparent specimen. This limits its use for studying realistic catalyst architectures and statistically representative particle behaviour. Ptychographic X-ray computed tomography (PXCT) is an emerging complementary investigative method,\u003csup\u003e13\u0026ndash;16\u003c/sup\u003e allowing us to measure larger and intact sample volumes with sufficient spatial resolution to identify the nanoparticles within a supported catalysts.\u003csup\u003e17\u003c/sup\u003e Owed to missing instrumentation, PXCT has mainly been employed in an ex-situ manner, i.e. measuring samples before and after catalytic reactions.\u003csup\u003e16,18,19\u0026ndash;22\u003c/sup\u003e The removal of the catalyst from the reactor and its operational environment, yet, alters the catalyst, making a use-representative characterisation currently practically impossible.\u003c/p\u003e\u003cp\u003eHere, enabled by a custom and PXCT-compatible environmental control system,\u003csup\u003e23\u003c/sup\u003e we present an in-situ ptychographic nanotomography study examining a supported palladium on silica (Pd/SiO\u003csub\u003e2\u003c/sub\u003e) catalyst across its complete lifecycle (activation\u0026ndash;operation\u0026ndash;deactivation). By repeatedly capturing the same volume from 25\u0026deg;C to 830\u0026deg;C under alternating methane-rich and oxidizing atmospheres, we quantitatively tracked the formation, growth, redistribution, and mobility of over 100,000 palladium nanoparticles.\u003c/p\u003e\u003cp\u003eThe experiments revealed two distinct modes of palladium transport feeding catalyst deactivation. A short-range diffusion process consistent with Ostwald ripening, and a long-range particle redistribution mechanism, both leading to losses in surface area. Most strikingly, the experiments revealed that the majority of the palladium nanoparticles remains in motion during the reaction, showing that relocalization, fragmentation, and agglomeration are continuous processes. The experiments further allowed to quantify the average palladium transport velocity within the 3D pore structure, amounting to ~\u0026thinsp;100 nm h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e under the most severe operating conditions (750\u0026deg;C). These mobility processes are strongly modulated by the gas environment, with oxidizing conditions promoting localized coarsening or ripening processes and methane-rich conditions causing particle mobility across hundreds of nanometres. More broadly, this study highlights the ability of in-situ PXCT to quantitatively resolve nanoscale transformations within large sample volumes and across environmental conditions. This bridges the resolution-statistics gap that has long stalled in-situ characterisation studies.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe palladium-on-silica (Pd/SiO\u003csub\u003e2\u003c/sub\u003e) catalyst was prepared by wet impregnation of a mesoporous support\u003csup\u003e24\u003c/sup\u003e with a palladium nitrate solution.\u003csup\u003e12,17,25\u003c/sup\u003e The amorphous silica support possesses an average pore diameter of ~\u0026thinsp;110 nm. The impregnation process results in the deposition of a thin film of palladium nitrate on the surfaces of the support, which upon calcination is converted into a dispersion of catalytically active PdO nanoparticles.\u003c/p\u003e\u003cp\u003eTo evaluate the catalyst\u0026rsquo;s methane oxidation activity as a function of temperature, the catalyst was then gradually heated to 300\u0026deg;C (initiating precursor decomposition and PdO formation), 450\u0026deg;C, 550\u0026deg;C, 650\u0026deg;C, and finally 750\u0026deg;C under a constant flow of a methane-oxygen gas mixture (1 mol% CH\u003csub\u003e4\u003c/sub\u003e / 4 mol% O\u003csub\u003e2\u003c/sub\u003e / 94 mol% Ar) in a tubular reactor. Following a residence time of 8 hours at each temperature, methane conversion was measured at 300\u0026deg;C using mass spectrometry. The resulting activity profile (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea) shows a gradual decline with increasing treatment temperature, indicating progressive catalyst deactivation.\u003c/p\u003e\u003cp\u003eEx-situ scanning transmission electron microscopy (STEM) and powder X-ray diffraction (PXRD) (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u0026ndash;S3) show that this loss in activity correlates with an increase in the average size of the PdO particles, from ~\u0026thinsp;5 nm in the as-prepared state to ~\u0026thinsp;15 nm after treatment at 550\u0026deg;C. Further, at this elevated temperature, larger sponge-like PdO agglomerates begin to appear. These observations suggest that the loss of catalytically active surface area is indeed the primary deactivation cause. However, ex-situ measurements do not reveal the mechanisms of these structural changes.\u003c/p\u003e\u003cp\u003eTo obtain a glimpse of these mechanisms, we then examined a 7 \u0026micro;m-wide catalyst pillar (Figure S4) via in-situ ptychographic X-ray computed tomography,\u003csup\u003e21,26\u003c/sup\u003e capturing the evolution of the catalyst from nitrate-rich precursor decomposition to deactivation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Tomograms were sequentially acquired at 25\u0026deg;C and 300\u0026deg;C in air (calcination phase); at 300\u0026deg;C, 450\u0026deg;C, 550\u0026deg;C, 650\u0026deg;C, and 750\u0026deg;C under a constant flow of the methane-oxygen gas mixture to mimic operating conditions; and again at 750\u0026deg;C and 830\u0026deg;C in air to investigate the effect of atmosphere on particle mobility and sintering (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). The tomograms have a voxel size of (15.5 nm)\u003csup\u003e3\u003c/sup\u003e and a sample average spatial resolution of 35 nm (Figure S5). A schematic of the acquisition setup is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec. Instrumentation and experimental details are provided in Holler et al.\u003csup\u003e23\u003c/sup\u003e and in the Methods section. A key advantage of PXCT is that it provides quantitative electron density tomograms,\u003csup\u003e14,15,27\u0026ndash;30\u003c/sup\u003e with each voxel returning an absolute density value. A priori knowledge of the electron densities of the catalyst\u0026rsquo;s components, ~\u0026thinsp;0.00 n\u003csub\u003ee\u003c/sub\u003e \u0026Aring;\u003csup\u003e\u0026minus;3\u003c/sup\u003e for air and argon, 0.55 n\u003csub\u003ee\u003c/sub\u003e \u0026Aring;\u003csup\u003e\u0026minus;3\u003c/sup\u003e for amorphous silica and 2.21 n\u003csub\u003ee\u003c/sub\u003e \u0026Aring;\u003csup\u003e\u0026minus;3\u003c/sup\u003e for PdO (Table S1), allows us then to segment and quantify material phases, respectively track their evolution.\u003csup\u003e31\u003c/sup\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed shows a threshold-segmented volume rendering of the tomogram acquired at 25\u0026deg;C, highlighting the silica support and the distribution of palladium-rich precursor deposits within it. The deposits are heterogeneously distributed and vary in density, reflecting the inherent limitations of wet impregnation processes, yielding here a volume-average Pd loading of ~\u0026thinsp;1 wt.%.\u003c/p\u003e\u003cp\u003eA consolidated view of the catalyst\u0026rsquo;s evolution is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, which shows the electron density histograms of the acquired tomograms. A first look reveals that the silica support is changing with temperature. Observable is a gradual increase in electron density from 0.53 n\u003csub\u003ee\u003c/sub\u003e \u0026Aring;\u003csup\u003e\u0026minus;3\u003c/sup\u003e at 25\u0026deg;C to 0.58 n\u003csub\u003ee\u003c/sub\u003e \u0026Aring;\u003csup\u003e\u0026minus;3\u003c/sup\u003e at 750\u0026deg;C. This densification, more pronounced under oxygen-rich conditions, coincides with a net sample mass increase of ~\u0026thinsp;7% (Figure S6). Based on PXRD measurements, literature reports and the apparent high-defect density of the silica support, we currently attribute the observed densification to progressive elimination of volume defects, vacancies or, silanol groups, whereas the concomitant mass gain is most likely due to oxygen uptake e.g., the removal of oxygen vacancies and PdO formation (Figure S7).\u003csup\u003e32,33\u003c/sup\u003e Despite these density changes we observed no spatial deformation of the support within our detection limits. Analysis of the segmented pore network shows that the pore size distribution remains essentially constant, with the average pore diameter decreasing only slightly from 113 at 25\u0026deg;C to 107 at 750\u0026deg;C (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee \u0026amp; S8), i.e. well within the spatial resolution estimate of 35 nm and under a single voxel deviation of 15 nm.\u003c/p\u003e\u003cp\u003eA close examination of the histograms reveals that a dominant fraction of PdO particles remains below the voxel size, i.e. the voxel possesses an electron density\u0026thinsp;\u0026lt;\u0026thinsp;2.21 n\u003csub\u003ee\u003c/sub\u003e \u0026Aring;⁻\u0026sup3;, even at 830\u0026deg;C. Although individual particle morphologies cannot be resolved at the current resolution, changes in electron density at the voxel-level provides a metric for quantifying PdO growth and mobility. An increase in voxel electron density reflects either particle growth or the aggregation of smaller PdO domains within that voxel, whereas a decrease indicates particle dissolution or relocation. Treating voxel electron density as a proxy for a volumetrically equivalent PdO particle size (Figure S9, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea),\u003csup\u003e31\u003c/sup\u003e we derive an average particle diameter of ~\u0026thinsp;4.6 nm in the as-prepared catalyst, in agreement with the ~\u0026thinsp;5 nm obtained by ex-situ STEM (Figure S2). This assignment is reasonable as palladium particles, whether metallic or oxidized, are the densest and mobile component in the system, meaning that observed density changes can be attributed unambiguously to palladium dynamics. Now, focusing on these Pd-rich voxels, defined here as those exceeding a density of 0.80 ne \u0026Aring;⁻\u0026sup3;, or containing\u0026thinsp;\u0026ge;\u0026thinsp;15 vol.% PdO (Figure S9), we observe a steady increase in their number and average density (or effective particle size) with increasing temperature. Based on the changes of the histograms, the formation of PdO particles is initially driven by precursor consumption, while at higher temperatures their continued growth involves coalescence and long-range migration, with increasingly isolated PdO domains growing at the expense of smaller ones. Surprisingly, upon switching from the methane-rich reaction atmosphere to air at 750\u0026deg;C we observe a marked collapse of the left-side tail of the silica peak in the histogram and a concurrent rise in palladium-rich voxels. We believe this change is caused by oxidation-driven reorganization of previously porous, fragmented, or partially reduced palladium particles into more densely packed and well-defined PdO particles.\u003c/p\u003e\u003cp\u003eBuilding on the histogram analysis of the PdO-rich voxels, we visualized their spatial distribution as a function of temperature and atmosphere. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb and Movies S1 \u0026amp; S2 present volume renderings of the electron density differences between adjacent environmental conditions. This subtraction removes the constant contributions of the support and pore space, thereby highlighting locations where palladium accumulates or relocates to within the sample volume.\u003c/p\u003e\u003cp\u003eProminently visible in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec (\u003cb\u003ei\u003c/b\u003e) \u0026ndash; showing the difference between the as-prepared catalyst and the catalyst after activation at 300\u0026deg;C in air \u0026ndash; is the decomposition of the deposited precursor and the formation of PdO particles; a first growth process of palladium particles. Continued treatment at 300\u0026deg;C under methane oxidation conditions (\u003cb\u003eii\u003c/b\u003e) leads to a notable increase in the number of PdO-rich voxels across the support, visually resembling a typical supported catalyst. Importantly, no significant electron density loss is detected elsewhere, indicating that particle formation arises from redox-driven densification of highly dispersed Pd-rich material into stable PdO nanoparticles rather than the coarsening of visible crystallites. Given the relatively low temperature and the presence of both oxidizing and reducing gases, partial redox cycling (Pd\u003csup\u003e2+\u003c/sup\u003e/Pd\u003csup\u003e0\u003c/sup\u003e) may facilitate redistribution and nucleation at this stage.\u003csup\u003e34\u003c/sup\u003e These processes precede the onset of classical and here visually detected Ostwald ripening or PMC,\u003csup\u003e5,35\u003c/sup\u003e which becomes increasingly evident at higher temperatures (\u003cb\u003eiii\u003c/b\u003e), where particle growth is accompanied by shrinkage and or disappearance of smaller particles in localized regions. (\u003cb\u003eiv-vi\u003c/b\u003e) The stepwise examination up to a temperature of 750\u0026deg;C under methane oxidation conditions showed a gradual but limited increase in both particle size and number consistent with continued coarsening. However, this stage is also marked by abrupt shifts in the spatial distribution of palladium-rich voxels, suggesting the presence of an additional, longer-range palladium redistribution mechanism. The emergence of new Pd-rich domains, often hundreds of nanometers away from regions of simultaneous depletion, points to palladium relocation via the long-range migration of particles, aggregates, or fragments. In parallel, we further observe the emergence of large, spatially fixed Pd-rich agglomerates, often porous and spanning multiple voxels, which appear to condense from this redistributed material. (\u003cb\u003evii-viii\u003c/b\u003e) Continued heating to 830\u0026deg;C and, importantly, a change to a purely oxidizing atmosphere appears to supress this long-range redistribution. Instead, we observe a distinct increase in newly resolvable PdO-rich voxels (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). This behavior may reflect a transition in dominant growth or transport mechanism. Under methane-rich conditions, limited surface mobility is observed while selected Pd particles remained mobile enabling long-range redistribution. In contrast, under fully oxidizing conditions, surface and gas phase diffusion of PdO molecules and local restructuring is enhanced resulting in an increase in Ostwald ripening dominated growth.\u003csup\u003e36\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eTo investigate possible spatial and mechanistic dependencies of these transport processes, we identified the location of mobile and stationary palladium-rich voxels. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea shows the location of permanently and temporarily occupied regions \u0026ndash; defined here as voxels that showed a Pd signal consistently or intermittently across the in-situ measurement. The permanently occupied voxels (stationary particles) are found preferentially near pore throats. Temporarily occupied voxels (transient particles) appear predominantly at the outskirts of stationary particle agglomerates or near open pore channels (Movies S3 \u0026amp; S4). Analysis further revealed a temperature-dependent increase in both voxel populations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb), reflective of the thermally activated PdO particle formation and mobility. Mobility is also influenced by both particle size and atmosphere (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). While stationary particles are on average only\u0026thinsp;~\u0026thinsp;2 nm larger than mobile ones, no particle with an inferred or volumetrically equivalent diameter\u0026thinsp;\u0026gt;\u0026thinsp;9 nm was observed to be mobile (Figure S10). The observed size-dependent mobility is consistent with models of particle transport, in which surface diffusion or gas-phase migration becomes increasingly restricted with particle size due to increasing particle-support interactions.\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eFurther analysis of the stationary voxels revealed a non-monotonic growth behavior, i.e. the same voxel might record gains in electron density or Pd content across consecutive temperatures just to display a loss in the next. A behavior captured in the voxel-level growth rate distributions shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, plotted here as a function of initial electron density for both the methane oxidation (300\u0026ndash;750\u0026deg;C) and oxidizing (750\u0026ndash;830\u0026deg;C) operation windows. Under methane oxidation conditions, we observed a relatively narrow distribution, with positive growth rates in smaller particles and an initially unexpected net loss in larger ones. A likely result of fragments or particle hopping events as those seen in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb \u003cb\u003eiv-vi\u003c/b\u003e. Upon switching to a purely oxidizing atmosphere, the growth rate distribution becomes broader and overall positive, with enhanced growth for smaller particles.\u003c/p\u003e\u003cp\u003eFinally, to determine the palladium transport length and migration velocity through the support, we applied a fractional volume sub-sampling approach (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, Figure S12). By calculating the net electron density change within progressively smaller sub-volumes, we identified the volume size below which mass redistribution becomes detectable. For volumes larger than the palladium transport length, density changes average out; below this threshold, local gains or losses become visible. The edge length of this transition volume serves as a proxy for the maximum transport length. This analysis reveals a temperature-dependent increase in transport length under methane-rich conditions: from ~\u0026thinsp;200 nm at 450\u0026deg;C to ~\u0026thinsp;830 nm at 750\u0026deg;C. Heating in air to 830\u0026deg;C further enhances the distance to 850 nm. Using these transport lengths together with the tomogram acquisition time, we can approximate the average palladium migration velocities, which increase from ~\u0026thinsp;30 nm h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to ~\u0026thinsp;105 nm h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). These values provide a kinetic measure of palladium redistribution and are critical for the prediction of catalyst stability and industrial catalyst body design. The velocities reveal a strong exponential temperature dependence. Accordingly, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec presents an Arrhenius-type plot with two distinct regimes. In air, at higher temperatures, the apparent transport activation barrier is low (~\u0026thinsp;10 kJ mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and matches previous studies that have shown a size independent gas phase transport of palladium leading to strong and rapid sintering in Pd/SiO\u003csub\u003e2\u003c/sub\u003e catalysts.\u003csup\u003e36\u003c/sup\u003e Under methane oxidation conditions a substantially higher barrier of 32 kJ mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e is found, reflecting the distinctly different migration/transport processes.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn-situ ptychographic nanotomography enabled us to monitor the evolution of a supported catalyst across a full activation\u0026ndash;operation\u0026ndash;deactivation cycle, from room temperature up to 830\u0026deg;C under oxidizing and methane-rich atmospheres. The tomograms, encompassing hundreds of thousands of individual catalyst particles, reveal a complex and environment-dependent picture of catalyst activation, particle mobility and deactivation.\u003c/p\u003e\u003cp\u003eDuring activation (25\u0026ndash;300\u0026deg;C), PXCT reveals the decomposition of the palladium nitrate precursor and the formation of finely dispersed PdO nanoparticles, which are non-uniform in size and heterogeneously distributed across the silica support. Under operational methane oxidation conditions (300\u0026ndash;750\u0026deg;C) two particle growth and mobility regimes are detectable. At lower temperatures, the particle growth is dominated by classical Ostwald ripening and PMC processes. Nanoparticles increase gradually in size, initially through the consumption of residual precursor material or particles with a size below the detection limit, and subsequently via the coalescence or aggregation of smaller particles. At higher temperatures, an unexpected long-range palladium redistribution process becomes dominant. This is evident by the appearance and disappearance of palladium oxide particles at spatially separated sites on the support, with inferred transport lengths reaching up to 800 nm at 750\u0026deg;C. This long-range migration of what looks to be entire particles exceeds the typical surface diffusion lengths and importantly migration does not always lead to immediate sintering. Instead, some Pd species appear to remain mobile without coalescing, while others condense into porous aggregates. Upon switching the sample atmosphere to air at 750\u0026deg;C and regardless of further heating to 830\u0026deg;C, the particle dynamics change markedly. The long-range mobility is suddenly strongly suppressed, and particle growth becomes again more localized. Additional larger PdO particles emerge via renewed ripening, consistent with an increased surface diffusion length under oxidizing conditions. This enhanced mobility essentially allows previously sub-resolution, or porous palladium species to migrate across the support and condense into stable, well-defined and now detectable nanoparticles. These findings indicate two distinct transport and deactivation pathways: (1) a short-range, surface-mediated coarsening process, e.g. a combination of Ostwald ripening and PCM, that governs initial nanoparticle formation and growth, and (2) a long-range particle redistribution mechanism that operates beyond the scale of conventional surface diffusion.\u003c/p\u003e\u003cp\u003eThe short-range process is both spatially confined and chemically modulated. Even at elevated temperatures, particle diameters rarely exceed\u0026thinsp;~\u0026thinsp;15 nm, with numerous sub-6 nm PdO particles persisting adjacent to larger aggregates (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) \u0026ndash; sometimes separated by only one to two voxels \u0026ndash; rather than merging. Assuming full precursor support surface coverage, the dominant absence of particles larger than ~\u0026thinsp;15 nm or the diameter of a voxel allows us to estimate the effective surface mobility to be ~\u0026thinsp;30\u0026ndash;60 nm. This is consistent with literature reports of limited (\u0026lt;\u0026thinsp;100 nm) surface mobility on oxide supports.\u003csup\u003e37\u003c/sup\u003e We attribute this confined transport length to a chemical stabilization or strong-surface interaction under methane-rich conditions, rather than topological barriers of the support. As upon switching to a purely oxidizing atmosphere, the number of resolvable PdO voxels increases sharply, consistent with enhanced mobility driven by gas-phase\u0026ndash;mediated Ostwald ripening at high temperatures.\u003csup\u003e36,38,39\u003c/sup\u003e This limited transport length and the associated growth of particles is yet sufficient to deactivate the catalyst, as the resulting decrease in surface-to-volume ratio drastically reduces the catalytically active surface area.\u003c/p\u003e\u003cp\u003eThe long-range redistribution of PdO particles is more active under methane-rich conditions. Between 300\u0026deg;C and 750\u0026deg;C, Pd‐rich voxels appear and disappear across distances of hundreds of nanometers between tomogram acquisitions, far exceeding the expected range of surface diffusion. We speculate that entire nanoparticles or small clusters detach from the support, migrate through the connected pore space and re-adsorb in new locations and eventually cluster. Based on the apparent suppression of this transport under fully oxidizing conditions, this particulate migration may be driven by redox‐induced changes in metal\u0026ndash;support adhesion, temporarily \u0026ldquo;unlocking\u0026rdquo; particles so they can traverse the pore network.\u003csup\u003e40\u003c/sup\u003e We currently speculate that heterogeneity of the amorphous oxide support surface\u003csup\u003e34,41,42\u003c/sup\u003e as well as possible gas-phase inhomogeneities, particularly gradients in local product concentrations (e.g., H\u003csub\u003e2\u003c/sub\u003eO)\u003csup\u003e43\u003c/sup\u003e under methane oxidation conditions, may influence which particles detach from the support and become mobile or remain stable. Thus, modifying the surface by strongly binding anchor has shown to stabilize metal particles in place for methane oxidation.\u003csup\u003e40\u003c/sup\u003e Similar evidence for cluster mobility has been reported for Pt/TiO\u003csub\u003e2\u003c/sub\u003e under reactive atmospheres suggesting that long‐range particle migration may be a general phenomenon in harsh catalytic environments.\u003csup\u003e12\u003c/sup\u003e Furthermore, we obtained a first estimate of the velocity of long-range PdO migration, which is strongly temperature dependent and ranges from 20\u0026ndash;100 nm h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. To put this into perspective, real-life catalyst bodies are typically millimetre-sized: for instance, at a migration rate of 100 nm h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e a PdO particle would require\u0026thinsp;~\u0026thinsp;1.1 years to traverse 1 mm through the support. A time scale well within the common lifetime of several years for many heterogeneous catalysts.\u003csup\u003e44,45\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIn combination, these observations not only query the optimal strategies to prevent catalyst deactivation but also challenge the notion that nanoparticles are inherently immobilized or only weakly mobile on support surfaces. Accordingly, strategies that rely solely on optimizing interparticle distances or initial dispersion patterns\u003csup\u003e46,47\u003c/sup\u003e may prove insufficient to prevent deactivation. Instead, more comprehensive approaches are needed: anchoring particles through tailored metal\u0026ndash;support interactions \u003csup\u003e40,48,49\u003c/sup\u003e and designing support architectures that physically restrict mobility, e.g., via tortuosity engineering or controlled confinement may offer more robust stabilization under harsh conditions.\u003c/p\u003e\u003cp\u003eWhile quantitative in-situ nanotomography facilitates a more use-representative and holistic characterisation of heterogeneous catalysts, the approach is currently bounded by spatial and temporal resolution as well as chemical specificity. These limitations currently prevent us from directly probing local metal-support interactions,\u003csup\u003e25,50,51\u003c/sup\u003e i.e. probe the morphology and chemistry of individual particles and the surrounding support, or the kinetics of migration events at the single-particle level. For example, while ex-situ PXRD and PXCT indicate only the presence of PdO throughout, PdO is known to autoreduce above 600\u0026deg;C to metallic palladium in oxygen-rich atmospheres.\u003csup\u003e52\u003c/sup\u003e Although such transient metallic phases are likely minor in terms of overall composition, their possible presence and relevance highlights the need for greater chemical specificity and sensitivity. Ongoing advances in instrumentation,\u003csup\u003e23,53\u0026ndash;56\u003c/sup\u003e dynamic tomography,\u003csup\u003e21,57,58\u003c/sup\u003e and chemical imaging\u003csup\u003e20,21,28,59,60\u003c/sup\u003e will alleviate these limitations in the near future. Follow-up experiments at a 4th generation synchrotron,\u003csup\u003e55\u003c/sup\u003e will enable combining dynamic PXCT\u003csup\u003e61\u003c/sup\u003e with X-ray absorption spectroscopy\u003csup\u003e21\u003c/sup\u003e allowing real-time, chemistry specific tracking of particle evolution and metal\u0026ndash;support interactions at previously inaccessible scales.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study presents the first demonstration of in-situ ptychographic nanotomography of a heterogenous catalyst. By monitoring the evolution of over 100,000 individual catalyst particles in a geometry representative of their actual usage and under conditions that approach their real-world application, we revealed that catalyst deactivation is governed not only by localized coarsening via ripening and coalescence but also by long-range redistribution of entire nanoparticles across hundreds of nanometers. This atmosphere-dependent mobility revises the picture of nanoparticle stability and highlights the need for strategies that anchor particles, and engineer supports to restrict migration. The ability to bridge or even narrow the information gap between in-situ electron microscopy\u003csup\u003e3,12\u003c/sup\u003e and the statistical relevance of averaging in-situ methods\u003csup\u003e62\u003c/sup\u003e is further expected to provide new, length-scale overarching, insights in heterogeneous catalysis. Importantly, the presented approach is not limited to catalysis: its applicability extends to any reactive porous material, including battery electrodes, fuel cells, and degradation-prone nanocomposites, laying the groundwork for more predictive materials design across disciplines.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMaterials\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eNanoporous glass beads were obtained from the \u003cem\u003eBundesanstalt f\u0026uuml;r Materialforschung und \u0026ndash;Pr\u0026uuml;fung\u0026nbsp;\u003c/em\u003e(BAM) and used as the catalyst support matrix. The beads possess an average pore diameter of 139 nm and a specific surface area of 26.6 m\u003csup\u003e2\u003c/sup\u003e g\u003csup\u003e-1\u003c/sup\u003e.\u003csup\u003e24,29\u003c/sup\u003e Analytical grade palladium nitrate dihydrate, Pd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e 2H\u003csub\u003e2\u003c/sub\u003eO, was purchased from Sigma Aldrich. The synthetic gas mixture (1 mol.% CH\u003csub\u003e4\u003c/sub\u003e / 4 mol.% O\u003csub\u003e2\u003c/sub\u003e / 94 mol.% Ar)\u0026nbsp;was purchased from Carbagas.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003ealladium\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;Deposition/ Supported Catalyst Preparation:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003ePd/SiO\u003csub\u003e2\u003c/sub\u003e catalysts were prepared via an incipient wetness impregnation process. Specifically, 1 g of the glass beads were first immersed in a Pd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u0026nbsp;\u003c/sub\u003esolution (12.7 mg mL\u003csup\u003e-1\u003c/sup\u003e) prepared using MiliQ water. The resulting slurry was next transferred into a vacuum desiccator to fully infiltrate the pores with the Pd solution. To then anchor the Pd species on the support surface and evaporate water we removed the beads from the solution and placed them into a preheated oven for 10 min at 200˚C. This process was repeated 6 times yielding a Pd/SiO\u003csub\u003e2\u003c/sub\u003e catalyst with a theoretical Pd loading of 2.9 wt.% based on a monolayer coverage in each cycle. A comparison of the integrated electron density between tomograms of the bare and loaded support suggests an average Pd loading of ~ 1 wt.%, assuming the density increase results solely from the added precursor. The lower-than-expected value suggests that precursor deposition was incomplete and uneven across the support. This is supported by Figure 1d, which shows extended regions where no Pd signal is detected.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGeneral Material Characterization\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCatalytic Activity Tests:\u003c/em\u003e\u003c/strong\u003e Methane oxidation tests were conducted using a combined microreactor and mass spectrometry system (Hiden Analytical), consisting of a heated quartz reactor tube (3 mm inner diameter) coupled to a mass spectrometer. For each experiment, 10 mg of the supported catalyst (crushed beads, 125\u0026ndash;250 \u0026micro;m in diameter) were loaded between two quartz wool plugs inside the reactor. The reactor was flushed with helium (50 mL min⁻\u0026sup1;), and the catalyst was then heated to 300 \u0026deg;C at a rate of 5 \u0026deg;C min⁻\u0026sup1; under helium flow. Upon reaching 300 \u0026deg;C, the catalyst was exposed to a reaction gas mixture containing 1 mol% CH₄, 4 mol% O₂, and 94 mol% He at a total flow rate of 50 mL min⁻\u0026sup1; for 8 hours, corresponding to the PXCT tomogram acquisition time. Under these conditions, carbon dioxide and water were the only detectable reaction products. Activity or Methane conversion degree was calculated as stated in Equation (1):\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1762330658.png\" width=\"576\" height=\"79\"\u003e\u003c/p\u003e\n\u003cp\u003eIn follow-up experiments, the same protocol was applied with additional thermal ageing steps. After the initial 300 \u0026deg;C exposure, the catalyst was heated to 450 \u0026deg;C and held under reaction conditions for 8 hours. It was then cooled to 300 \u0026deg;C, and the catalytic activity was re-evaluated. This procedure was repeated for 550 \u0026deg;C, 650 \u0026deg;C, and 750 \u0026deg;C treatments. Catalyst deactivation was calculated from the loss in conversion at 300 \u0026deg;C after each thermal step, as described in Equation (2):\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1762330683.png\" width=\"677\" height=\"64\"\u003e\u003c/p\u003e\n\u003cp\u003eFollowing each test cycle, a fraction of the spent catalyst was retrieved and analysed by STEM and XRD to track nanoparticle sintering, phase evolution, and structural degradation associated with deactivation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePowder X-ray diffraction (PXRD):\u0026nbsp;\u003c/em\u003e\u003c/strong\u003ePowder X-ray diffraction (PXRD) data were acquired using a Cu-K alpha radiation source with a scan step size of 0.02 2theta (Figure S3). Instrument broadening was accounted for.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eElectron Microscopy:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eScanning electron micrographs (SEM) were acquired using a Zeiss NVision-40. The scanning transmission electron micrographs (STEM) were acquired with an aberration-corrected Hitachi HD-2700CS microscope operated at 200 kV. High-angle annular dark-field (HAADF) images were acquired to facilitate compositional and morphological interpretation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOperando Ptychographic Tomography\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTomography Sample Preparation:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eTo prepare the PXCT examined sample pillar we mounted a single, millimetre-sized, empty glass bead on top of an aluminium tomography pin using a carbon adheasive.\u003csup\u003e63\u003c/sup\u003e The pin was then placed in a furnace preheated to 200 \u0026deg;C and held for 90 minutes to fully cure the adhesive. After curing, the bead was shaped into a cylindrical pillar (~30 \u0026micro;m diameter, ~50 \u0026micro;m height) using a micro-lathe.\u003csup\u003e26\u003c/sup\u003e The upper portion of this pillar was subsequently thinned to ~7 \u0026micro;m in diameter via focused ion beam (FIB) milling (Supplementary Fig. S4). The resulting glass pillar was then subjected to the catalyst preparation procedure outlined above.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePtychographic X-ray Computed Tomography (PXCT)\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eis the combination of \u0026nbsp;ptychography and X-ray computed tomography.\u003csup\u003e13\u0026ndash;15\u003c/sup\u003e Ptychography is a lensless coherent imaging technique where the sample is scanned across a coherent X-ray beam and a diffraction image is acquired at each scanning position. By ensuring that the neighbouring beam illuminations overlap with each other, the resulting redundancy encoded within the diffraction images enables the reconstruction of both the sample and the X-ray beam through iterative optimization algorithms.\u003csup\u003e15\u003c/sup\u003e By performing ptychography at multiple sample rotation angles, the resulting ptychographic projections enable tomographic reconstructions of both phase and amplitude contrast with nanometre resolution, ideal for local component identification in functional materials.\u003csup\u003e19,21,30,31\u003c/sup\u003e The phase tomogram when acquired away from sample-relevant X-Xray absorption edges can be converted to a value absolute electron density tomogram.\u003csup\u003e30\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003ePXCT\u003csup\u003e13,14\u003c/sup\u003e experiments were carried out 6.2 keV at the cSAXS beamline of the Swiss Light Source, Paul Scherrer Institut, Switzerland. The photon energy was selected using a double-crystal Si(111) monochromator. The horizontal aperture slits, located 22 m upstream of the sample was set to 20 \u0026mu;m in width, to create a horizontal virtual source point that coherently illuminated a Fresnel zone-plate, 200 \u0026mu;m in diameter, with an outermost zone width of 60 nm. The Fresnel zone-plate was designed with locally displaced zones to improve imaging quality.\u003csup\u003e64\u003c/sup\u003e Coherent diffraction patterns were acquired using an in-vacuum Eiger 1.5M area detector, with a 75 \u0026micro;m pixel size, placed 5.225 m downstream of the sample inside in an evacuated flight tube. For sample positioning and environment regulation we used the flexible tOMography Nano Imaging endstation (flOMNI)\u003csup\u003e29,65\u003c/sup\u003e with modifications for environmental control.\u003csup\u003e23\u003c/sup\u003e For achieving fast scanning speeds a Fresnel zone plate scanner utilizing a combined motion of sample and illuminating FZP was used.\u003csup\u003e66\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe field of view of each projection, or ptychographic scan, was 11 x 7 \u0026mu;m\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e(width x height). The sample was scanned using a Fermat-spiral scanning pattern with an average step size of 0.7 \u0026micro;m. The exposure time per scanning point was 0.05\u0026thinsp;seconds. For each ptychographic scan or image reconstruction, a detector region of 900\u0026thinsp;\u0026times;\u0026thinsp;900 pixels was used, resulting in a reconstructed image pixel size of 15.48 nm. Reconstructions were performed using the PtychoShelves package\u003csup\u003e67\u003c/sup\u003e with 500 iterations of the difference map algorithm\u003csup\u003e13\u003c/sup\u003e followed by 600 iterations of maximum likelihood refinement.\u003csup\u003e68\u003c/sup\u003e All the tomograms mentioned in the main text were reconstructed using ~550 ptychographic projections, sufficient for a tomogram spatial resolution of 20 nm for a 7 \u0026micro;m (non-porous) sample according to the Crowther criterion.\u0026nbsp;Tomography projection acquisition followed a nested approach, specifically we acquired\u0026nbsp;30 equally spaced projections over 180\u0026ordm; at a time and then repeated the acquisition with an angular offset based on the golden ratio. The approach was chosen to accommodate possible sample stabilization delays.\u0026nbsp;Following ptychographic image reconstruction and alignment of the projections, tomograms for each environmental condition were reconstructed separately by first aligning the projections,\u003csup\u003e69\u003c/sup\u003e followed by tomogram reconstruction using a modified filtered back-projection algorithm (FBP).\u0026nbsp;\u003csup\u003e70\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate nanoparticle formation, mobility and catalyst deactivation we examined the prepared sample pillar across 9 environmental conditions. In sequence, we examined the pillar (1-2) at 25˚C and 300˚C under a constant flow of air, (3-7) at 300˚C, 450˚C, 550˚C, 650˚C and 750˚C under of a constant flow of a methane gas mixture\u0026nbsp;(1 mol.% CH\u003csub\u003e4\u003c/sub\u003e / 4 mol.% O\u003csub\u003e2\u003c/sub\u003e / 94 mol.% Ar), and (8-9) at\u0026nbsp;750˚C and 830˚C under a constant flow of air. See Supplementary Figure 1 for a graphical representation of the tested conditions and associated catalyst performance. Using the environmental control system\u003csup\u003e23\u003c/sup\u003e integrated mass flow controllers we ensured that the gas flow across measurements was kept constant. The flow rate was set to 1 L min\u003csup\u003e-1\u003c/sup\u003e. While tomogram acquisition commenced after a 30 minute wait period after each change in environmental condition, we excluded the 6 initially acquired sub-sets of projections from the tomogram reconstruction of a given environmental condition. This exclusion introduced a sample stabilization or thermodynamic equilibration time of ~2.0 hours per condition and tomogram acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTomogram Dose Estimation:\u003c/em\u003e\u003c/strong\u003e The imparted X-ray dose during a single tomogram acquisition was estimated to be on the order of ~\u0026nbsp;10\u003csup\u003e8\u003c/sup\u003e Gy. The estimated dose is based on the average area flux density of each ptychographic scan and the mass density of the specimen.\u003csup\u003e71\u003c/sup\u003e For this calculation the sample was assumed to consist entirely of silica.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTomogram Spatial Resolution Evaluation:\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eTomogram analysis was performed solely on the phase component of the acquired PXCT datasets, due to its superior spatial-resolution and signal-to-noise ratio at the selected X-ray energy.\u003csup\u003e60,72\u003c/sup\u003e Spatial resolution estimates for each of the reconstructed tomograms were obtained using Fourier shell correlation (FSC).\u003csup\u003e73\u003c/sup\u003e The acquired projections per conditions were alternatively separated into two sets and individually reconstructed. To estimate the \u003cem\u003etomogram average\u003c/em\u003e spatial resolution, we then calculated the correlation function between these two tomograms in the Fourier domain. The achieved resolution is estimated based on the first intersection of the correlation function with the half-bit threshold criteria (Figure S5). The tomogram spatial resolution averaged across all environmental conditions according to FSC is 35 nm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eVoxel-level Electron Density Uncertainty:\u003c/em\u003e\u003c/strong\u003e To estimate the error of the retrieved electron density, we calculated the standard deviation (\u0026sigma;) of a region of air/argon surrounding the imaged pillar. Assuming the region to possess a uniform known density. The average electron density uncertainty was calculated to be ~0.008 n\u003csub\u003ee\u003c/sub\u003e \u0026Aring;\u003csup\u003e-\u003c/sup\u003e\u0026sup3;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTomogram Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTomogram analysis and 3D rendering were performed using in-house developed Matlab routines or using Avizo. Prior to analysis, the tomograms were registered via a subpixel image registration approach using a mutual information metric and resampled onto a common gird. Tomography analysis was limited to a common sample volume present in all acquired tomograms.\u003csup\u003e23\u003c/sup\u003e Further, to exclude possible FIB sample preparation artefacts from the tomogram analysis we excluded the outermost micrometre of the imaged sample cylinder from analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePore Analysis:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e Isolated pores and pore networks were identified through threshold-based segmentation of the electron density tomograms.\u0026nbsp;An upper electron density threshold of 0.28 e⁻ \u0026Aring;⁻\u0026sup3; was applied.\u0026nbsp;The threshold, selected in view of the electron density of the silica support\u0026nbsp;(0.56 n\u003csub\u003ee\u003c/sub\u003e \u0026Aring;\u003csup\u003e-\u003c/sup\u003e\u0026sup3; Table S1), classifies all voxel which are at minimum filled with 50 vol.% with air or argon as pores. Silica is the lightest material in the sample. The isolated volumes were then subjected to a morphological closing operation to refine the segmentation and following to 3D thickness map calculations to retrieve a pore size distribution for each tomogram/ environmental condition. Shown in Supplementary Figure 8 are a subset of the obtained, volume-weighted, pore diameter distributions. Pores with diameters below 50 nm were excluded from the thickness map analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEffect of the Wet Impregnation Process on the Silica Support Structure:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eTo evaluate whether the Pd impregnation process altered the silica support structure, and to establish a baseline for histogram interpretation and Pd feature identification, a tomogram of the pure silica support material was acquired prior to catalyst loading. Figure S13 presents a comparison of electron density histograms extracted from tomograms of the silica support before and after wet impregnation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eExtraction and Analysis of Environment Induced Sample Changes:\u003c/em\u003e\u003c/strong\u003e Following the spatial registration and resampling of the tomograms onto a common grid, we segmented the sample into two principal components: the silica support and voxels at one point occupied by Pd across the measurement series. To isolate the silica support from the pore space, we applied a lower threshold of 0.28 n\u003csub\u003ee\u003c/sub\u003e \u0026Aring;\u003csup\u003e-\u003c/sup\u003e\u0026sup3; and an upper threshold of 0.8 n\u003csub\u003ee\u003c/sub\u003e \u0026Aring;⁻\u0026sup3;. Values were informed by the electron density histogram of the bare support, Figure S13. Voxels with densities exceeding 0.8 n\u003csub\u003ee\u003c/sub\u003e \u0026Aring;⁻\u0026sup3; were classified as Pd-containing, corresponding to a minimum voxel occupancy of 15 vol% PdO, Figure S9. This separation allows us then to monitor evolution both support and the growth and mobility of already existing or newly forming nanoparticles.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(1) \u003cem\u003eSilica Support Changes and Metal-Support Interactions.\u0026nbsp;\u003c/em\u003eHaving isolated the support in all tomograms we first confirmed that the silica support did not undergo spatial deformation on the observable level (Table S1 and Figure S8 \u0026ndash; Pore Size Distribution) over the course of the measurement series. This justifies the use of a constant support mask for the succeeding Pd nanoparticle analysis steps. \u0026nbsp;While no spatial deformation of the support was detected, minor electron density changes of radial and environmental dependency were detectable, Figure S6 \u0026amp; 7.\u003csup\u003e21\u003c/sup\u003e We currently believe these changes to stem from the removal of oxygen vacancies from the silica support.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e(2) Pd Nanoparticle Formation, Growth, and Migration\u003c/em\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003eTo track the evolution of Pd particles across the measurement series, we first generated a \u003cem\u003e\u0026ldquo;Pd location mask\u0026rdquo;\u003c/em\u003e by summing all segmented tomograms. This produced a binary map identifying all voxels that contained Pd at any point during the experiment. The resulting mask was then applied to all tomograms to enable voxel-wise analysis across conditions. To provide a first qualitative impression of particle growth and mobility, we subtracted tomograms acquired under adjacent environmental conditions (e.g., subtracting the 450 \u0026deg;C tomogram from the 550 \u0026deg;C tomogram). The resulting differential maps, visualized using a divergent colormap scaled across the full dataset, highlight regions of Pd accumulation and depletion (Figure 2, Movie S1). For quantitative analysis (Figure 3, Movie S3), we evaluated the electron density of each Pd-containing voxel individually across the series. This voxel-level analysis allowed us to determine growth and dissolution rates, as well as the fraction of stationary versus transient Pd-occupied voxels. Being a voxel-level analysis and as a dominant fraction of the initially present and newly forming Pd particles are smaller than the spatial resolution, growth rates here refer to net Pd density fluctuations within individual voxels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(3) \u003cem\u003eTransport length.\u003c/em\u003e To estimate the volume or distance over which Pd can migrate within the support under the tested conditions, we employed a volume-subsampling approach. A central volume of approximately 40 \u0026micro;m\u0026sup3; was used for this analysis. The previously defined Pd-location mask was applied to this volume to exclude contributions from the silica support. For each environmental condition in the measurement series, we calculated the integrated electron density within this volume. By incrementally subsampling this region into smaller nested volumes and performing the same integration, we identified changes in the rate of electron density gain or loss as a function of volume size. The key assumption is that, for a fixed condition, the rate of Pd accumulation or depletion should remain constant across nested volumes -unless Pd species begin migrating into or out of that volume. A deviation in growth rate exceeding \u0026plusmn;5% between adjacent sub-volumes was used as a cut-off to define the maximum effective transport distance under each condition.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGeneral:\u003c/strong\u003e PXCT experiments were performed at the coherent small-angle x-ray scattering (cSAXS) beamline of the Swiss Light Source (SLS). The construction of the utilized instrumentation was supported by the Swiss National Science Foundation (SNF) (R\u0026prime;EQUIP, 145056, OMNY) and the Competence Centre for Materials Science and Technology (CCMX) of the ETH-Board. We thank X. Donath and L. Heller for technical support. Electron microscopy work was performed at the Scientific Centre for Optical and Electron Microscopy (ScopeM) at ETH Zurich and the Electron Microscopy Facility at PSI. We want to thank F. Krumeich from ETH Zurich for his STEM measurements of the powder catalyst samples. We further would like to thank E. A. Mueller Gubler and J. Reuteler for assistance with the FIB sample preparation. Finally, we thank the anonymous reviewers of an earlier version of this manuscript for suggestions that helped improve the data analysis and framing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eA.B., T.A. and J.I. are funded by the Swiss National Science Foundation (SNF), Project Numbers 200021_178943, 200021_196898 and PZ00P2_179886.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eA.B., M.H. and J.I. conceived the study. M.H. designed and led the construction of the environmental control system. T.A., M.G.S., M.H. and J.I. performed PXCT experiments. T.A. and J.I. reconstructed tomograms. A.B. and J.I. analysed data. A.B. prepared samples, performed performance tests. A.B. and F.K. performed electron microscopy experiments. A.B. and J.I. wrote the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations:\u0026nbsp;\u003c/strong\u003eThe authors declare no financial, ethical or other competing interests relating to the contents of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u0026nbsp;\u003c/strong\u003eData needed to evaluate the presented conclusions are provided in the manuscript and/or the Supplementary Materials. The raw data and reconstructed projections can be accessed at the following address, doi.xyz (\u003cem\u003eto be populated during final manuscript revisions\u003c/em\u003e), or obtained from the corresponding authors upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode Availability:\u003c/strong\u003e The code and scripts developed and used for this study can be accessed at the following address https://www.psi.ch/en/sls/csaxs/software, or obtained from the corresponding authors upon reasonable request.\u003cstrong\u003e\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSchl\u0026ouml;gl, R. Heterogeneous Catalysis. \u003cem\u003eAngewandte Chemie - International Edition\u003c/em\u003e \u003cstrong\u003e54\u003c/strong\u003e, 3465\u0026ndash;3520 (2015).\u003c/li\u003e\n\u003cli\u003eLox, E. S. J. Automotive Exhaust Treatment. in \u003cem\u003eHandbook of Heterogeneous Catalysis\u003c/em\u003e 2274\u0026ndash;2345 (Wiley-VCH Verlag GmbH \u0026amp; Co. KGaA, Weinheim, Germany, 2008). doi:10.1002/9783527610044.hetcat0120.\u003c/li\u003e\n\u003cli\u003eAitbekova, A. \u003cem\u003eet al.\u003c/em\u003e Templated encapsulation of platinum-based catalysts promotes high-temperature stability to 1,100 \u0026deg;C. \u003cem\u003eNature Materials\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 1290\u0026ndash;1297 (2022).\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;n, A. J., Mitchell, S., Mondelli, C., Jaydev, S. \u0026amp; P\u0026eacute;rez-Ram\u0026iacute;rez, J. Unifying views on catalyst deactivation. \u003cem\u003eNature Catalysis\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 854\u0026ndash;866 (2022).\u003c/li\u003e\n\u003cli\u003eHansen, T. W., DeLaRiva, A. T., Challa, S. R. \u0026amp; Datye, A. K. Sintering of Catalytic Nanoparticles: Particle Migration or Ostwald Ripening? \u003cem\u003eAccounts of Chemical Research\u003c/em\u003e \u003cstrong\u003e46\u003c/strong\u003e, 1720\u0026ndash;1730 (2013).\u003c/li\u003e\n\u003cli\u003eOh, J., Boucly, A., van Bokhoven, J. A., Artiglia, L. \u0026amp; Cargnello, M. Palladium Catalysts for Methane Oxidation: Old Materials, New Challenges. \u003cem\u003eAccounts of Chemical Research\u003c/em\u003e (2023) doi:10.1021/acs.accounts.3c00454.\u003c/li\u003e\n\u003cli\u003eDatye, A. K. \u0026amp; Votsmeier, M. Opportunities and challenges in the development of advanced materials for emission control catalysts. \u003cem\u003eNature Materials\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 1049\u0026ndash;1059 (2021).\u003c/li\u003e\n\u003cli\u003eXu, Q., Kharas, K. C., Croley, B. J. \u0026amp; Datye, A. K. The Sintering of Supported Pd Automotive Catalysts. \u003cem\u003eChemCatChem\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 1004\u0026ndash;1014 (2011).\u003c/li\u003e\n\u003cli\u003eTait, S. L., Ngo, L. T., Yu, Q., Fain, S. C., Jr. \u0026amp; Campbell, C. T. Growth and sintering of Pd clusters on \u0026alpha;-Al2O3(0001). \u003cem\u003eJ. Chem. Phys.\u003c/em\u003e \u003cstrong\u003e122\u003c/strong\u003e, 064712 (2005).\u003c/li\u003e\n\u003cli\u003eKawaguchi, T. \u003cem\u003eet al.\u003c/em\u003e Gas-Induced Segregation in Pt-Rh Alloy Nanoparticles Observed by \u003cem\u003eIn Situ\u003c/em\u003e Bragg Coherent Diffraction Imaging. \u003cem\u003ePhys. Rev. Lett.\u003c/em\u003e \u003cstrong\u003e123\u003c/strong\u003e, 246001 (2019).\u003c/li\u003e\n\u003cli\u003eSmith, J. \u003cem\u003eet al.\u003c/em\u003e Sintering Mechanism of Pt/Al2O3 in Complex Emission Gases Elucidated via In Situ Environmental STEM. \u003cem\u003eACS Materials Lett.\u003c/em\u003e 3301\u0026ndash;3311 (2024) doi:10.1021/acsmaterialslett.4c00422.\u003c/li\u003e\n\u003cli\u003eFrey, H., Beck, A., Huang, X., van Bokhoven, J. A. \u0026amp; Willinger, M. G. Dynamic interplay between metal nanoparticles and oxide support under redox conditions. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e376\u003c/strong\u003e, 982\u0026ndash;987 (2022).\u003c/li\u003e\n\u003cli\u003eThibault, P. \u003cem\u003eet al.\u003c/em\u003e High-Resolution Scanning X-ray Diffraction Microscopy. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e321\u003c/strong\u003e, 379\u0026ndash;382 (2008).\u003c/li\u003e\n\u003cli\u003eDierolf, M. \u003cem\u003eet al.\u003c/em\u003e Ptychographic X-ray computed tomography at the nanoscale. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e467\u003c/strong\u003e, 436\u0026ndash;439 (2010).\u003c/li\u003e\n\u003cli\u003eMiao, J., Ishikawa, T., Robinson, I. K. \u0026amp; Murnane, M. M. Beyond crystallography: Diffractive imaging using coherent X-ray light sources. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e348\u003c/strong\u003e, 530\u0026ndash;535 (2015).\u003c/li\u003e\n\u003cli\u003eSheppard, T. L. \u003cem\u003eet al.\u003c/em\u003e In Situ Multimodal 3D Chemical Imaging of a Hierarchically Structured Core@Shell Catalyst. \u003cem\u003eJournal of the American Chemical Society\u003c/em\u003e \u003cstrong\u003e139\u003c/strong\u003e, 7855\u0026ndash;7863 (2017).\u003c/li\u003e\n\u003cli\u003eIhli, J. \u003cem\u003eet al.\u003c/em\u003e Hierarchical Structure of NiMo Hydrodesulfurization Catalysts Determined by Ptychographic X-Ray Computed Tomography. \u003cem\u003eAngewandte Chemie - International Edition\u003c/em\u003e \u003cstrong\u003e59\u003c/strong\u003e, 17266\u0026ndash;17271 (2020).\u003c/li\u003e\n\u003cli\u003eFam, Y. \u003cem\u003eet al.\u003c/em\u003e Correlative Multiscale 3D Imaging of a Hierarchical Nanoporous Gold Catalyst by Electron, Ion and X‐ray Nanotomography. \u003cem\u003eChemCatChem\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 2858\u0026ndash;2867 (2018).\u003c/li\u003e\n\u003cli\u003eIhli, J. \u003cem\u003eet al.\u003c/em\u003e A three-dimensional view of structural changes caused by deactivation of fluid catalytic cracking catalysts. \u003cem\u003eNature Communications\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, (2017).\u003c/li\u003e\n\u003cli\u003eHirose, M. \u003cem\u003eet al.\u003c/em\u003e Oxygen-diffusion-driven oxidation behavior and tracking areas visualized by X-ray spectro-ptychography with unsupervised learning. \u003cem\u003eCommunications Chemistry\u003c/em\u003e \u003cstrong\u003e2\u003c/strong\u003e, 1\u0026ndash;7 (2019).\u003c/li\u003e\n\u003cli\u003eGao, Z. \u003cem\u003eet al.\u003c/em\u003e Sparse ab initio x-ray transmission spectrotomography for nanoscopic compositional analysis of functional materials. \u003cem\u003eScience Advances\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 1\u0026ndash;12 (2021).\u003c/li\u003e\n\u003cli\u003eWeber, S. \u003cem\u003eet al.\u003c/em\u003e Evolution of Hierarchically Porous Nickel Alumina Catalysts Studied by X-Ray Ptychography. \u003cem\u003eAdvanced Science\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 1\u0026ndash;12 (2022).\u003c/li\u003e\n\u003cli\u003eHoller, M. \u003cem\u003eet al.\u003c/em\u003e Environmental control for X-ray nanotomography. \u003cem\u003eJournal of Synchrotron Radiation\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 1223\u0026ndash;1231 (2022).\u003c/li\u003e\n\u003cli\u003eBAM Federal Institute for Materials Research and Testing SS, Germany, E. reference material E. F. 2000 [cited]Available from: http://www.bam.de/de/rm-certificates_media/rm_cert_porous_materials/erm_fd120_121_122rep.pdf. \u003cem\u003eNo Title\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eReddy, G. K., Ling, C., Peck, T. C. \u0026amp; Jia, H. Understanding the chemical state of palladium during the direct NO decomposition-influence of pretreatment environment and reaction temperature. \u003cem\u003eRSC Advances\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 19645\u0026ndash;19655 (2017).\u003c/li\u003e\n\u003cli\u003eHoller, M. \u003cem\u003eet al.\u003c/em\u003e A lathe system for micrometre-sized cylindrical sample preparation at room and cryogenic temperatures. \u003cem\u003eJournal of Synchrotron Radiation\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 472\u0026ndash;476 (2020).\u003c/li\u003e\n\u003cli\u003eCelestre, R. \u003cem\u003eet al.\u003c/em\u003e Nanosurveyor 2: A Compact Instrument for Nano-Tomography at the Advanced Light Source. \u003cem\u003eJournal of Physics: Conference Series\u003c/em\u003e \u003cstrong\u003e849\u003c/strong\u003e, 012047 (2017).\u003c/li\u003e\n\u003cli\u003eMichelson, A. \u003cem\u003eet al.\u003c/em\u003e Three-dimensional visualization of nanoparticle lattices and multimaterial frameworks. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e376\u003c/strong\u003e, 203\u0026ndash;207 (2022).\u003c/li\u003e\n\u003cli\u003eHoller, M. \u003cem\u003eet al.\u003c/em\u003e X-ray ptychographic computed tomography at 16 nm isotropic 3D resolution. \u003cem\u003eScientific Reports\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, 3857 (2015).\u003c/li\u003e\n\u003cli\u003eDiaz, A. \u003cem\u003eet al.\u003c/em\u003e Quantitative x-ray phase nanotomography. \u003cem\u003ePhysical Review B\u003c/em\u003e \u003cstrong\u003e85\u003c/strong\u003e, 020104 (2012).\u003c/li\u003e\n\u003cli\u003eIhli, J. \u003cem\u003eet al.\u003c/em\u003e Ptychographic X-ray tomography reveals additive zoning in nanocomposite single crystals. \u003cem\u003eChemical Science\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 355\u0026ndash;363 (2020).\u003c/li\u003e\n\u003cli\u003eMunde, M. S., Gao, D. Z. \u0026amp; Shluger, A. L. Diffusion and aggregation of oxygen vacancies in amorphous silica. \u003cem\u003eJ. Phys.: Condens. Matter\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 245701 (2017).\u003c/li\u003e\n\u003cli\u003eSacks, M. D. \u0026amp; Tseng, T.-Y. Preparation of SiO2 Glass from Model Powder Compacts: I, Formation and Characterization of Powders, Suspensions, and Green Compacts. \u003cem\u003eJournal of the American Ceramic Society\u003c/em\u003e \u003cstrong\u003e67\u003c/strong\u003e, 526\u0026ndash;532 (1984).\u003c/li\u003e\n\u003cli\u003eYu, X. \u003cem\u003eet al.\u003c/em\u003e Anchoring PdOx clusters on defective alumina for improved catalytic methane oxidation. \u003cem\u003eNat Commun\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 6494 (2024).\u003c/li\u003e\n\u003cli\u003eOstwald, W. Studien \u0026uuml;ber die Bildung und Umwandlung fester K\u0026ouml;rper. \u003cem\u003eZeitschrift f\u0026uuml;r Physikalische Chemie\u003c/em\u003e \u003cstrong\u003e22U\u003c/strong\u003e, 289\u0026ndash;330 (1897).\u003c/li\u003e\n\u003cli\u003eGoodman, E. D. \u003cem\u003eet al.\u003c/em\u003e Size-controlled nanocrystals reveal spatial dependence and severity of nanoparticle coalescence and Ostwald ripening in sintering phenomena. \u003cem\u003eNanoscale\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 930\u0026ndash;938 (2021).\u003c/li\u003e\n\u003cli\u003eLi, L. \u003cem\u003eet al.\u003c/em\u003e Modeling the Migration of Platinum Nanoparticles on Surfaces Using a Kinetic Monte Carlo Approach. \u003cem\u003eJ. Phys. Chem. C\u003c/em\u003e \u003cstrong\u003e121\u003c/strong\u003e, 4261\u0026ndash;4269 (2017).\u003c/li\u003e\n\u003cli\u003ePlessow, P. N. \u0026amp; Abild-Pedersen, F. Sintering of Pt Nanoparticles via Volatile PtO 2 : Simulation and Comparison with Experiments. \u003cem\u003eACS Catalysis\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 7098\u0026ndash;7108 (2016).\u003c/li\u003e\n\u003cli\u003eOh, J. \u003cem\u003eet al.\u003c/em\u003e Colloidally Engineered Pd and Pt Catalysts Distinguish Surface- and Vapor-Mediated Deactivation Mechanisms. \u003cem\u003eACS Catalysis\u003c/em\u003e 1812\u0026ndash;1822 (2023) doi:10.1021/acscatal.2c04683.\u003c/li\u003e\n\u003cli\u003eBecker, M., Frey, H., Batool, S. R., Van Bokhoven, J. A. \u0026amp; Beck, A. Al-anchored platinum catalysts on reducible supports: High-temperature stability against redispersion during methane oxidation. \u003cem\u003eApplied Catalysis B: Environment and Energy\u003c/em\u003e \u003cstrong\u003e373\u003c/strong\u003e, 125323 (2025).\u003c/li\u003e\n\u003cli\u003eGoodman, E. D. \u003cem\u003eet al.\u003c/em\u003e Catalyst deactivation via decomposition into single atoms and the role of metal loading. \u003cem\u003eNature Catalysis\u003c/em\u003e \u003cstrong\u003e2\u003c/strong\u003e, 748\u0026ndash;755 (2019).\u003c/li\u003e\n\u003cli\u003eLee, J. \u003cem\u003eet al.\u003c/em\u003e Aggregation of CeO 2 particles with aligned grains drives sintering of Pt single atoms in Pt/CeO 2 catalysts. \u003cem\u003eJournal of Materials Chemistry A\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 7029\u0026ndash;7035 (2022).\u003c/li\u003e\n\u003cli\u003eKoč\u0026iacute;, P., \u0026Scaron;těp\u0026aacute;nek, F., Kub\u0026iacute;ček, M. \u0026amp; Marek, M. Modelling of micro/nano-scale concentration and temperature gradients in porous supported catalysts. \u003cem\u003eChemical Engineering Science\u003c/em\u003e \u003cstrong\u003e62\u003c/strong\u003e, 5380\u0026ndash;5385 (2007).\u003c/li\u003e\n\u003cli\u003eBarrow, N. \u003cem\u003eet al.\u003c/em\u003e Doubling the life of Cu/ZnO methanol synthesis catalysts via use of Si as a structural promoter to inhibit sintering. \u003cem\u003eScience Advances\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 1\u0026ndash;12 (2024).\u003c/li\u003e\n\u003cli\u003eMoulijn, J. A., Van Diepen, A. E. \u0026amp; Kapteijn, F. Catalyst deactivation: is it predictable? What to do? \u003cem\u003eApplied Catalysis A: General\u003c/em\u003e \u003cstrong\u003e212\u003c/strong\u003e, 3\u0026ndash;16 (2001).\u003c/li\u003e\n\u003cli\u003eGoodman, E. D., Schwalbe, J. A. \u0026amp; Cargnello, M. Mechanistic Understanding and the Rational Design of Sinter-Resistant Heterogeneous Catalysts. \u003cem\u003eACS Catalysis\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 7156\u0026ndash;7173 (2017).\u003c/li\u003e\n\u003cli\u003eHolm, A. \u003cem\u003eet al.\u003c/em\u003e Nanoscale Spatial Distribution of Supported Nanoparticles Controls Activity and Stability in Powder Catalysts for CO Oxidation and Photocatalytic H 2 Evolution. \u003cem\u003eJournal of the American Chemical Society\u003c/em\u003e \u003cstrong\u003e142\u003c/strong\u003e, 14481\u0026ndash;14494 (2020).\u003c/li\u003e\n\u003cli\u003evan Deelen, T. W., Hern\u0026aacute;ndez Mej\u0026iacute;a, C. \u0026amp; de Jong, K. P. Control of metal-support interactions in heterogeneous catalysts to enhance activity and selectivity. \u003cem\u003eNature Catalysis\u003c/em\u003e \u003cstrong\u003e2\u003c/strong\u003e, 955\u0026ndash;970 (2019).\u003c/li\u003e\n\u003cli\u003eYang, Q. \u003cem\u003eet al.\u003c/em\u003e Single Carbon Vacancy Traps Atomic Platinum for Hydrogen Evolution Catalysis. \u003cem\u003eJournal of the American Chemical Society\u003c/em\u003e \u003cstrong\u003e144\u003c/strong\u003e, 2171\u0026ndash;2178 (2022).\u003c/li\u003e\n\u003cli\u003eBeck, A. \u003cem\u003eet al.\u003c/em\u003e The dynamics of overlayer formation on catalyst nanoparticles and strong metal-support interaction. \u003cem\u003eNature Communications\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 3220 (2020).\u003c/li\u003e\n\u003cli\u003eTauster, S. J., Fung, S. C., Baker, R. T. K. \u0026amp; Horsley, J. A. Strong-Interactions in Supported-Metal Catalysts. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e211\u003c/strong\u003e, 1121\u0026ndash;1125 (1981).\u003c/li\u003e\n\u003cli\u003eSalomonsson, P., Johansson, S. \u0026amp; Kasemo, B. Methane oxidation over PdOx : on the mechanism for the hysteresis in activity and oxygen content. \u003cem\u003eCatal Lett\u003c/em\u003e \u003cstrong\u003e33\u003c/strong\u003e, 1\u0026ndash;13 (1995).\u003c/li\u003e\n\u003cli\u003eBecher, J. \u003cem\u003eet al.\u003c/em\u003e Sample Environment for Operando Hard X-ray Tomography\u0026mdash;An Enabling Technology for Multimodal Characterization in Heterogeneous Catalysis. \u003cem\u003eCatalysts\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 459 (2021).\u003c/li\u003e\n\u003cli\u003eSidorenko, P. \u0026amp; Cohen, O. Single-shot ptychography. \u003cem\u003eOptica\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 9 (2016).\u003c/li\u003e\n\u003cli\u003eStreun, A. \u003cem\u003eet al.\u003c/em\u003e SLS-2 \u0026ndash; the upgrade of the Swiss Light Source. \u003cem\u003eJournal of Synchrotron Radiation\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 631\u0026ndash;641 (2018).\u003c/li\u003e\n\u003cli\u003eRaimondi, P. ESRF-EBS: The Extremely Brilliant Source Project. \u003cem\u003eSynchrotron Radiation News\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 8\u0026ndash;15 (2016).\u003c/li\u003e\n\u003cli\u003eGarc\u0026iacute;a-Moreno, F. \u003cem\u003eet al.\u003c/em\u003e Tomoscopy: Time-Resolved Tomography for Dynamic Processes in Materials. \u003cem\u003eAdvanced Materials\u003c/em\u003e \u003cstrong\u003e33\u003c/strong\u003e, (2021).\u003c/li\u003e\n\u003cli\u003eZhang, J., Lee, W. K. \u0026amp; Ge, M. Sub-10 second fly-scan nano-tomography using machine learning. \u003cem\u003eCommunications Materials\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 1\u0026ndash;9 (2022).\u003c/li\u003e\n\u003cli\u003eLo, Y. H. \u003cem\u003eet al.\u003c/em\u003e X-ray linear dichroic ptychography. \u003cem\u003eProceedings of the National Academy of Sciences of the United States of America\u003c/em\u003e \u003cstrong\u003e118\u003c/strong\u003e, 1\u0026ndash;8 (2021).\u003c/li\u003e\n\u003cli\u003eGao, Z. \u003cem\u003eet al.\u003c/em\u003e Nanoscale crystal grain characterization: Via linear polarization X-ray ptychography. \u003cem\u003eChemical Communications\u003c/em\u003e \u003cstrong\u003e56\u003c/strong\u003e, 13373\u0026ndash;13376 (2020).\u003c/li\u003e\n\u003cli\u003eGao, Z. \u003cem\u003eet al.\u003c/em\u003e Dynamic sparse x-ray nanotomography reveals ionomer hydration mechanism in polymer electrolyte fuel-cell catalyst. \u003cem\u003eScience Advances\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, eadp3346 (2024).\u003c/li\u003e\n\u003cli\u003eBeck, A. \u003cem\u003eet al.\u003c/em\u003e Following the structure of copper-zinc-alumina across the pressure gap in carbon dioxide hydrogenation. \u003cem\u003eNature Catalysis\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, 488\u0026ndash;497 (2021).\u003c/li\u003e\n\u003cli\u003eHoller, M. \u003cem\u003eet al.\u003c/em\u003e OMNY PIN - A versatile sample holder for tomographic measurements at room and cryogenic temperatures. \u003cem\u003eReview of Scientific Instruments\u003c/em\u003e \u003cstrong\u003e88\u003c/strong\u003e, (2017).\u003c/li\u003e\n\u003cli\u003eOdstrčil, M., Lebugle, M., Guizar-Sicairos, M., David, C. \u0026amp; Holler, M. Towards optimized illumination for high-resolution ptychography. \u003cem\u003eOpt. Express, OE\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 14981\u0026ndash;14997 (2019).\u003c/li\u003e\n\u003cli\u003eHoller, M. \u0026amp; Raabe, J. Error motion compensating tracking interferometer for the position measurement of objects with rotational degree of freedom. \u003cem\u003eOptical Engineering\u003c/em\u003e \u003cstrong\u003e54\u003c/strong\u003e, 054101 (2015).\u003c/li\u003e\n\u003cli\u003eOdstrcil, M., Lebugle, M., Lachat, T., Raabe, J. \u0026amp; Holler, M. Fast positioning for X-ray scanning microscopy by a combined motion of sample and beam-defining optics. \u003cem\u003eJ Synchrotron Rad\u003c/em\u003e \u003cstrong\u003e26\u003c/strong\u003e, 504\u0026ndash;509 (2019).\u003c/li\u003e\n\u003cli\u003eWakonig, K. \u003cem\u003eet al.\u003c/em\u003e PtychoShelves, a versatile high-level framework for high-performance analysis of ptychographic data. \u003cem\u003eJournal of Applied Crystallography\u003c/em\u003e \u003cstrong\u003e53\u003c/strong\u003e, 574\u0026ndash;586 (2020).\u003c/li\u003e\n\u003cli\u003eThibault, P. \u0026amp; Guizar-Sicairos, M. Maximum-likelihood refinement for coherent diffractive imaging. \u003cem\u003eNew Journal of Physics\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, (2012).\u003c/li\u003e\n\u003cli\u003eOdstrčil, M., Holler, M., Raabe, J. \u0026amp; Guizar-Sicairos, M. Alignment methods for nanotomography with deep subpixel accuracy. \u003cem\u003eOptics Express\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 36637 (2019).\u003c/li\u003e\n\u003cli\u003eGuizar-Sicairos, M. \u003cem\u003eet al.\u003c/em\u003e Phase tomography from x-ray coherent diffractive imaging projections. \u003cem\u003eOptics Express\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 21345 (2011).\u003c/li\u003e\n\u003cli\u003eHowells, M. R. \u003cem\u003eet al.\u003c/em\u003e An assessment of the resolution limitation due to radiation-damage in X-ray diffraction microscopy. \u003cem\u003eJournal of Electron Spectroscopy and Related Phenomena\u003c/em\u003e \u003cstrong\u003e170\u003c/strong\u003e, 4\u0026ndash;12 (2009).\u003c/li\u003e\n\u003cli\u003eIhli, J. \u003cem\u003eet al.\u003c/em\u003e Resonant Ptychographic Tomography Facilitates Three-Dimensional Quantitative Colocalization of Catalyst Components and Chemical Elements. \u003cem\u003eJournal of Physical Chemistry C\u003c/em\u003e \u003cstrong\u003e122\u003c/strong\u003e, 22920\u0026ndash;22929 (2018).\u003c/li\u003e\n\u003cli\u003eVan Heel, M. \u0026amp; Schatz, M. Fourier shell correlation threshold criteria. \u003cem\u003eJournal of Structural Biology\u003c/em\u003e \u003cstrong\u003e151\u003c/strong\u003e, 250\u0026ndash;262 (2005).\u003c/li\u003e\n\u003cli\u003eHoller, M. \u003cem\u003eet al.\u003c/em\u003e An instrument for 3D x-ray nano-imaging. \u003cem\u003eReview of Scientific Instruments\u003c/em\u003e \u003cstrong\u003e83\u003c/strong\u003e, (2012).\u003c/li\u003e\n\u003cli\u003eGooch, J. W. Silica, amorphous [MAK Value Documentation, 1991]. in \u003cem\u003eThe MAK-Collection for Occupational Health and Safety\u003c/em\u003e 158\u0026ndash;179 (Wiley-VCH Verlag GmbH \u0026amp; Co. KGaA, Weinheim, Germany, 2012). doi:10.1002/3527600418.mb763186e0002.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Ptychography, Tomography, Heterogeneous Catalysis, Supported Catalyst, Methane Oxidation","lastPublishedDoi":"10.21203/rs.3.rs-7914877/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7914877/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNanoparticles supported on the surface of porous carrier materials are the dominant form of heterogeneous catalysts today. Yet, they suffer from a common deactivation mechanism: the loss of active surface area under industrial use conditions. Deactivation often stems from the sintering of nanoparticles, a mass transport process whose mechanism and operating length scale are a topic of controversy. Investigating this process is challenging, requiring not only a behavioural characterisation of thousands of individual particles within the spatial confines of a hierarchically structured support but also a characterisation of their ensemble behaviour and local support interactions. Here, we introduce in-situ ptychographic X-ray computed nanotomography as a tool to facilitate this characterisation, allowing a local examination of catalysts in their use-geometry under operational-relevant conditions. Applied to methane oxidation over a palladium-on-silica supported catalyst, we reveal two concurrently operating deactivation drivers, short-range ripening and long-range particle migration, each with different temperature and atmosphere dependencies. The latter enables particles to traverse hundreds of nanometres through the support. These observations expand the current understanding of sintering behaviour in supported catalysts and demonstrate PXCT\u0026rsquo;s capability to resolve restructuring processes within complex porous materials.\u003c/p\u003e","manuscriptTitle":"In-Situ Ptychographic Nanotomography Captures Activation, Mobility, and Deactivation of Supported Catalysts","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-05 08:37:42","doi":"10.21203/rs.3.rs-7914877/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f1e1e121-d287-4832-a0ae-920a0379b2ce","owner":[],"postedDate":"November 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":57368821,"name":"Physical sciences/Chemistry/Catalysis"},{"id":57368822,"name":"Physical sciences/Materials science/Techniques and instrumentation"},{"id":57368823,"name":"Physical sciences/Chemistry/Catalysis/Heterogeneous catalysis"}],"tags":[],"updatedAt":"2026-05-08T16:33:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-05 08:37:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7914877","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7914877","identity":"rs-7914877","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}