Bridging Particle-Scale Lithiation Mechanisms and Macroscopic Performance in High-Energy Density Si Anodes via Time-resolved Full 3D Visualisation

Bridging Particle-Scale Lithiation Mechanisms and Macroscopic Performance in High-Energy Density Si Anodes via Time-resolved Full 3D Visualisation | 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 Bridging Particle-Scale Lithiation Mechanisms and Macroscopic Performance in High-Energy Density Si Anodes via Time-resolved Full 3D Visualisation Roland Brunner, Michael Haeusler, Rahulkumar Sinoijya, Olga Stamati, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8273007/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Anodes with high silicon (Si) content, paired with nickel-manganese-cobalt (NMC) cathodes, enable interesting prospects for Li-ion batteries well beyond the state of the art. However, when Si alloys with lithium (Li), it undergoes significant volume changes, raising the critical question of how exactly the electrode and individual particles respond to the lithiation dynamics and thus impacting the battery performance. Here, we provide enhanced insights into the chemo-mechanical processes for cells with an 89 wt% Si anode paired with an NMC cathode. Electrode-scale deformation is linked with particle-scale mechanics by incorporating correlative multiscale 3D in situ investigations. Indeed, the combination of a sophisticated in situ cell setup, with high-resolution synchrotron X-ray computed nano-tomography, together with AI-driven segmentation and 4D strain mapping, allows us to detect pronounced spatial deformation and strain heterogeneities from the electrode to the single particle level. We observe diverse lithiation behaviours, anisotropic strain evolution and mechanically distinct transformation modes across hundreds of particles. Stress concentrators and fracture nucleation sites steer the transformation, generating localized strain fields decoupled from bulk electrode swelling. Indeed, many particles lithiate via complex internal network-like transformation routes. These 4D multiscale observations highlight key design levers for silicon-rich anodes, including defect screening, particle size optimization and electrode architecture engineering. Physical sciences/Energy science and technology/Energy storage/Batteries Physical sciences/Materials science/Materials for energy and catalysis/Batteries Physical sciences/Physics/Techniques and instrumentation/Imaging techniques Physical sciences/Chemistry/Energy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The electrification of transport is fundamental to the global effort to decarbonize energy systems and mitigate climate change. Lithium-ion batteries (LIBs) support this transition, not only powering electric vehicles, but also enabling grid-scale storage and facilitating the integration of intermittent renewable energy sources. Widespread adoption across sectors depends on overcoming key performance bottlenecks, particularly in energy density, charging speed and cycle life, while ensuring long-term economic and environmental sustainability 1 – 3 . The success of LIBs arises from their high energy density, long cycle life and high efficiency. In automotive applications, industry targets exceed 250 Wh kg − 1 energy density, >2C charge rates and > 1000 cycles 4 . These demands have driven the development of high-performance cathode materials, particularly those based on nickel, manganese and cobalt (NMC), which enable higher capacity and voltage windows 5 . However, the graphite anode, currently dominant in commercial LIBs, is limited by a theoretical capacity of ~ 372 mAh g⁻¹ 6 and suffers from limitations under high charging rates due to lithium plating 4 . As a result, the anode becomes the limiting component and pairing it with high-capacity NMC cathodes cannot fully unlock the desired performance for next-generation applications. To address this mismatch, alloy-type anodes have emerged as promising alternatives 7 , 8 . These materials react with lithium to form alloys, allowing much higher capacities than intercalation-based systems. Among them, silicon stands out due to its high theoretical specific capacity (~ 4200 mAh g⁻¹ for Li 22 Si 5 ), low working potential, natural abundance and compatibility with existing manufacturing infrastructure 1 , 8 – 11 . In combination with NMC cathodes, silicon anodes offer a path towards high-energy-density LIBs 7 , 12 , 13 . However, the key challenge remains the large volume changes silicon undergoes during (de)lithiation 11 , 14 , leading to capacity fading and decreased cycle life 11 , 13 , 15 – 18 . Despite extensive engineering strategies to mitigate these effects 8 , 9 , 19 – 22 , the widespread commercial implementation of ultra-high content silicon anodes remains challenging. Therefore, correlated investigations of the lithiation dynamics, stress evolution and degradation at both the electrode and particle-levels in cells pairing Si anodes with NMC cathodes is essential for progress. It is widely reported that lithiation of crystalline silicon proceeds via a two-phase core-shell mechanism 23 – 25 . A moving amorphization front converts crystalline Si (c-Si) into amorphous Li x Si, leading to radial expansion and internal stress accumulation. Much of this understanding stems from in situ transmission electron microscopy (TEM) studies on idealized systems that use statistically non-representative amounts of Si particles, neglect the electrode microstructure, including porosity and carbon binder domain (CBD), and are conducted under vacuum 26 , 27 . While TEM enables high spatial resolution, it is inherently two-dimensional, requires invasive sample preparation, is restricted to a small field of view and is limited in its ability to capture interparticle interactions, matrix effects, or collective behaviour within intact electrodes. As such, these observations provide limited insight into real-world battery configurations 8 , 9 , 19 , 20 , 26 , 27 . Recently, in situ three-dimensional imaging techniques have gained momentum in battery research, offering new opportunities to bridge the gap between model systems and realistic architectures 28 – 30 . In this context, synchrotron-based X-ray computed tomography (nano-SXCT) enables three-dimensional imaging at the nanoscale from two-dimensional projections collected over a 360° rotation. Prior studies utilizing nano-SXCT have revealed macroscale phenomena in battery cells such as electrode swelling, crack formation and delamination during cycling 31 – 37 . However, most in situ nano-SXCT experiments operate at voxel sizes above 0.2 µm 31,33–38 , insufficient to resolve sub-micron features of individual silicon particles, typically 500 nm – 5 µm in diameter, in embedded electrodes. Consequently, particle-scale phenomena, such as heterogeneous lithiation, stress localization and interparticle interactions, remain unresolved in three-dimensions, despite their central role in degradation cascades that affect entire electrodes. Moreover, many in situ imaging studies rely on half-cell configurations using lithium metal as a counter electrode, offering limited insight into high-energy full-cell setups incorporating NMC cathodes 35 – 39 . Yet, sub-micron, in situ 3D imaging of silicon particles embedded within an electrode microstructure, would allow direct tracking of critical early-stage microstructure degradation processes as well as local lithiation behaviour on different length scales that have so far remained hidden. A recent study combining operando optical microscopy and synchrotron X-ray computed tomography with digital volume correlation, revealed heterogeneous lithiation dynamics and strain evolution in graphite/µ-Si composite electrodes at the electrode scale, highlighting that Si cycling stability critically depends on intraparticle nanoscale porosity, whereas mechanical degradation is driven largely by expansion of the carbon-binder domain (CBD) 40 . Yet, full correlative in situ chemo-mechanical studies on Si|NMC cells that track behaviour from the electrode scale down to individual particles at sub-micron resolution unravelling lithiation pathways, stress concentrator and fracture nucleation in 3D over time, remain scarce. Herein, we apply in situ nano-SXCT to show the lithiation behaviour and mechanical response of an ultra-high 89 wt% Si content anode paired with a high-energy-density 811NMC cathode in three dimensions from electrode to particle level in a correlated manner. Our custom-designed electrochemical cell applies a controlled stack pressure to ensure electrical contact and mechanical relevance during cycling. This enables time-resolved 3D tracking of the electrode, Si particle´s adjacent microstructure as well as of the individual silicon particle dynamics with sufficient resolution and contrast beyond the state of the art. The possibility to capture 4D in situ data down to nanoscales in combination with semantic image segmentation and local digital volume correlation (DVC)-based analysis, allows the collection of high spatio-temporal resolved full-field displacement and strain maps. We analyse not only the lithiation behaviour of the electrode but rather enhance the perception of the chemo-mechanical process by studying diverse local lithiation behaviour, anisotropic strain evolution and mechanically distinct transformation modes from hundreds of particles distributed within the electrode to individual ones. Rather than a uniform core–shell transformation, many particles develop internal, complex network-like lithiated pathways. The in-depth correlative multiscale tomographic analysis suggests that Si lithiation is thus intrinsically heterogeneous, governed by global as well as local features such as the particle size distribution, particle location within the electrode and surrounding microstructure, state of charge but also by processing-induced damage, electrode architecture and cell configuration, respectively. These observations point to factors to consider in silicon-anode development as defect screening, particle-size optimization and architecture engineering. Beyond, the multiscale correlative in situ nano-SXCT-based framework generalizes to different materials and cycling conditions, combining nanoscale resolution with mechanical analysis to support the rational design of next-generation electrodes. Results and discussion In situ measurement setup and electrochemical cell behaviour. We build a cell setup, allowing in situ synchrotron X-ray computed nano-tomography acquisition to investigate electrochemically induced transformations of the electrode and Si particles during lithiation and delithiation with high resolution and contrast, see Fig. 1 . The cell geometry is scaled down to fit the requirements of nanoscale tomography and to ensure the detection of sub-micron object sizes, while maintaining design and material elements of high energy density commercial relevant LIBs, see Fig. 1a . The measurements are performed at the ID16B beamline 41 of the European Synchrotron Radiation Facility (ESRF), Grenoble, France. The anode consists of a slurry-cast layer containing 89 wt% micron-sized crystalline silicon particles connected by polyacrylic acid (PAA)-based binder, carbon black and carbon nanotubes, calendared to a final thickness of ~ 21 µm. Graphite is deliberately excluded from the anode to isolate the chemo-mechanical responses of silicon 1 , 7 , which is often obscured in composite systems. The prepared Si-based anode is precisely stacked with a polypropylene separator and paired with an NMC811 cathode, forming a full-cell configuration essential for studying microstructural evolution in high-energy-density LIBs unlike most in situ studies that use lithium metal as reference electrode 35 – 39 . To avoid fully exploiting the large Si capacity, the anode is operated under cathode-limited conditions (Methods). Figure 1b illustrates the structural and chemical composition of the pristine anode utilizing backscattered electron (BSE) field emission scanning electron microscopy (FESEM) imaging and energy-dispersive X-ray spectroscopy (EDS). The correlated images reveal the distribution of silicon particles embedded in the carbon-binder domain (CBD). The prepared anode|separator|cathode-stack, is integrated into the custom-designed in situ cell and mounted on the rotation stage at ID16B as shown in Fig. 1c . A key feature of the cell design is a spring-loaded upper contact which applies a constant compressive load of about 0.2–0.4 MPa, replicating real‑world conditions 42 . Furthermore, the spring is able to accommodate changes in the electrode stack thickness during cycling, maintaining uniform interfacial contact and stable electrochemical performance throughout lithiation and delithiation. While some previous in situ X-ray studies have used defined-pressure systems to replicate realistic mechanical environments, these approaches have typically been limited to larger-scale setups and have not been adapted for X-ray nano-tomography at microscale dimensions 36 , 38 , 39 . Other studies, by contrast, relied on hand-assembled or loosely packed capillary cells without controlled pressure 36 , 37 , 43 , 44 , often resulting in inconsistent compression and limited reproducibility. Details of cell assembly and electrochemical testing are provided in Methods and Supplementary Note 1–3 . Figure 1d shows a reconstructed nano-SXCT volume with a field of view of 102.4 x 102.4 x 102.4 µm³ and a voxel size of 50 nm. The dark top layer is the Cu current collector, the Si anode lies beneath and the bright layer corresponds to the separator. The dataset resolves particle-scale morphology suitable for quantitative analysis. 3D electrode and individual Si particle morphology evolution during Li insertion. Figure 2. Morphological evolution and phase-contrast-driven segmentation of non-lithiated silicon upon charging. (a) Representative nano-SXCT reconstructions of the anode from timesteps T0 (pristine) to T6 (cell: ~85% SOC). The Cu current collector lies above the orange dotted line, the porous separator is visible at the bottom of the anode. At the pristine state the Si particles and CBD + electrolyte are indicated by dark and light grey, respectively. Electrode expansion is traced by dashed red lines. ROI to study the evolution on particle level is indicated by a green dotted box. Representative particles are highlighted by red, green and blue. The scalebar refers to 5 µm. (b) ROI to track representative particles in red, green and blue, respectively, during charging using semantic segmentation. Scalebars refer to 3 µm. (c) Axial average anode thickness and relative non-lithiated (RNL) phase volume from Si particles distributed in the electrode from T0 to T6. (d) Cell voltage profile during a charge–discharge cycle with tomography time points from T0 to T9. Charging is done at constant current C/3 to 4.3 V, then constant-voltage hold at 4.3 V. At T6 the cell reaches ~ 85% SoC. T7 – T9 are recorded during/after partial discharge at constant current C/5 to 2.5 V. Nano-SXCT cross-section of the blue particle at T0 and T6 with dashed lines in orange (e) and yellow (f) highlighting a path at T0 through the CBD + E and Si interface (pristine state) as well as a path within the Si particle core, respectively. See also the path at T6. Particle contour of T0 is indicated and overlaid as reference for timestep T6. (g,h) Corresponding greyscale profiles vs. pixels (px) at T0 (black) and T6 (red) along the orange (g) and yellow (h) dashed line indicated in (e,f). Background colours highlight the region of lithiated and non-lithiated Si phases. Vertical dashed line illustrates the shift of the dark grey regions interface from T0 to T6 in (g). Figure 2a illustrates the reconstructed nano-SXCT volumes of the electrode across different states of lithiation, from the uncycled or pristine state at T0, to the lithiated condition at T6 associated with an 85% state of charge (SoC). The developed cell design, introduced in Fig. 1 , not only allows monitoring the evolving electrode morphology but also surpasses current studies 36 , 37 , 45 , by enabling the correlative tracking of individual silicon particles during lithiation in three dimensions, see Fig. 2b . The effective spatial resolution of approximately 300 nm, see further details in Supp. Figure 8 , enables sub-micron feature resolution at the particle scale while preserving statistically relevant electrode-level context. The copper current collector remains unchanged throughout the experiment and serves as a reliable internal reference for further analysis. Throughout lithiation the anode thickens in an approximately linear manner, as qualitatively observable in Fig. 2a and Supp. Video 1 and quantitatively confirmed in Fig. 2c . In detail, the mean electrode thickness increases from 20.7 ± 0.7 µm at T0 to 25.8 ± 1.8 µm at T3 (50% SoC) and reaches 30.0 ± 2.1 µm at T6, corresponding to a cumulative average thickness increase of about 44%. A more detailed analysis shows an incremental increase of about 5 to 7% between T1 and T2, T3 and T4, as well as T4 and T5. Yet, a significant steeper incline is witnessed between T2 and T3 suggesting a transition triggered by the electrochemical evolution of the cell. Indeed, this amplified change in thickness can be associated with the onset of the 4.3 V constant-voltage step, see Fig. 2d . Further information regarding the voltage and current profile during charging discharging are provided in Methods and Supplementary Note 3 . Despite the substantial overall expansion, no macroscopic cracking through the entire electrode thickness, as reported in previous studies 36 , 37 , is observed at any point during lithiation. For the semantic segmentation of the individual particles distributed within the electrode, the detectability of the targeted material features in the reconstructed volume is essential. The detectability relies on phase-contrast imaging, which is sensitive to variations in the real part of the refractive index (δ) 46 . In the pristine state, crystalline silicon exhibits a strong phase contrast relative to the surrounding CBD soaked with the utilized electrolyte (E), yielding rather distinguishable particle boundaries. For quantitative 3D analysis, a convolutional neural network (CNN)-like model is utilized to segment the individual particles throughout the lithiation process, see Fig. 2b . Further details regarding the image analysis is provided in the Methods section and Supplementary Note 4 . The timeseries, illustrated in Fig. 2b , shows increasing inter-particle spacing, particularly along the axial direction, consistent with the bulk electrode swelling up to 44%. Unexpectedly, the relative non-lithiated (RNL) phase volume, obtained from the particle segmentation decreases. First, rather gradually up to timestep T2 and then more abruptly between T2 and T3, mirroring the trend of both the electrode-thickness evolution and the cell-voltage profile, see Fig. 2c and d , respectively. Cross-sectional slices of a representative Si particle at timesteps T0 and T6 are shown in Fig. 2e and f . The presented images highlight significant grey value changes from timestep T0 to T6, suggesting the formation of a lithiation induced network within the Si particle´s core but also the modification at its interface to the CBD and electrolyte (CBD + E). To study the latter the evaluated particle contour from T0 is overlaid as a reference on the T6 slice. The centre of mass of the particle is fixed allowing a direct comparison. The overlay reveals a locally dependent retreat of the Si particle’s outer interface at T6. Indeed, the definition of the particles interface during the lithiation is challenging. The corresponding greyscale line profile plot in Fig. 2g supports the observed interface shift. At T0, along the indicated orange dashed line, the c-Si|CBD + E interface, labelled with interface T0, is accentuated by a significant decrease of the grey value. Certainly, at T6, the decrease is shifted towards the particle core by about 8 px. This observed grey value behaviour in the profile for T0 and T6 marks the transition from non-lithiated to lithiated Si. Figure 2h illustrates greyscale profiles drawn entirely within the particle´s core, see yellow dashed line in Fig. 2f . For timestep T0 a flat profile over the entire considered range is depicted. This indicates a relatively homogeneous material phase with uniform phase contrast. By contrast for the same range at T6, the greyscale value significantly increases at a certain distance within the particle core and drops again after about 16 pixels. Lithiation alters the refractive index of Si 47 , making lithiated regions highly distinguishable within the Si-core. The collected tomographic data, based on the observed distinct grey value changes, enhances the perception regarding the lithiation of the Si particle core. Therefore, the deep learning-based segmentation rather targets the non-lithiated fraction of the silicon core, see Fig. 2c . Thus, the apparent particle shrinking in the segmented data, does not reflect a physical contraction. For instance, the blue-labelled particle from Fig. 2b , indicates a decrease in volume from 119 µm³ to 80 µm³ at T0 and T6, respectively, i.e. yields that 33 %of the Si core is lithiated at T6. Note, that this percentage does not include the lithiated zone at the particles outer interface. Further, small, heavily lithiated particles may lose contrast entirely and fall below the detection threshold, causing them to drop out of the segmented dataset. Capturing the global deformation of the electrode. (a) Local digital volume correlation (local-DVC) grid on a representative anode sub-volume (40 x 40 x 40 µm³) at T0. A node spacing (ns) of 35 voxels and a half window size (hws) of 35 voxels, give overlapping 70³-voxel correlation windows (red cube). (b) DVC principle: a regular grid of correlation windows is tracked between a reference volume (Tn) and a deformed volume (Tn + 1), yielding local displacement vectors at window centres (illustrated by a green arrow). From the displacement field, local strain tensors are computed. The schematic of a deforming Si particle illustrates this approach. (c) A nano-SXCT vertical cross-section (T0) indicating the divided current-collector side (orange) and separator side (blue). Right: Corresponding axial strain maps at T2, T4, T6 and T8 referenced to T0. Effective axial strain, is mapped from compressive (blue, − 100%) to tensile (red, + 150%). The scale bar corresponds to 10 µm. (d) Evolution of volumetric strain is shown for the current collector (orange) and separator (blue) side, as well as for the whole electrode (red), revealing spatial heterogeneity. (e) Extracted histograms indicate the local volumetric strain distributions in the upper and lower electrode regions at T2, T4, T6 and T8. Maxima are highlighted by arrows. A progressive broadening and skewing of the strain distributions, indicates increasing heterogeneity and asymmetry. (f) Temporal evolution of the axial strain components (XX, YY, ZZ) over the entire anode. Light grey and dark grey backgrounds indicate timepoints corresponding to lithiation and delithiation, respectively. Orange and blue lines represent the strain in the upper and lower regions, respectively. We quantify the chemo-mechanical response by applying a local digital volume correlation (local-DVC) based analysis 48 to the time-resolved synchrotron tomograms, extracting full-field displacements and strains. Specifically, this approach features a mechanical perspective of the underlying morphological changes, bridging the gap between visual observations, mechanical response and electrochemical behaviour. We register all timesteps to the pristine state of the electrode at timestep T0 using cubic correlation windows placed on a regular 3D grid. A 50% overlap between adjacent windows is used to resolve displacement gradients at the particle scale while maintaining robust convergence of the iterative correlation. Displacement vectors at window centres provide the local strain tensor. See the schematic in Fig. 3 a and b for the grid and principle. Details with respect to the DVC model are presented in Methods and Supplementary Note 5 . Figure 3 c shows the evolution of axial strain maps for the vertical cross-sections from the electrode. The underlying dynamics is exemplary illustrated by timestep T2, T4, T6. It indicates that the deformation is dominated by expansion along the thickness in axial direction. The effective visualized axial strain ranges from compressive to tensile, illustrated in blue and red, respectively. First localized tensile zones appear at T2, establishing a separator-to-collector gradient in the very first lithiation step. These zones intensify and connect as lithiation proceeds significantly as indicated in timestep T4 and are peaking at T6 on the separator side. A partial relaxation during delithiation is observed at T8. More detailed strain analysis of the electrode is performed by mapping the temporal evolution of the extracted mean volumetric strain across the full anode as well as lower and upper electrode parts, associated with the separator and current collector side, respectively, see Fig. 3 d. The mean volumetric strain of the full electrode increases by about 6% upon initial lithiation at T1 and then progressively builds-up throughout the constant current and constant voltage charging, reaching roughly 44% at T6. The measured electrode expansion, see also the analysis in Fig. 2a , is consistent with previous reports 17 , 40 , 49 . All these values remain well below the often-cited theoretical volumetric expansion of ~ 300% for fully lithiated pure Si 11,17,50 . In full-cell configurations, actual expansion is significantly constrained by factors such as limited lithiation depth, anode to cathode balance, mechanical confinement, porosity and the influence of surrounding matrix materials. This discrepancy highlights the limitations of earlier studies, which often employed idealized systems that neglect electrode-scale mechanical particle interactions. Therefore, a critical perspective is required when interpreting both theoretical expansion values and data derived from simplified experimental setups. During lithium extraction from T6 to T8, the electrode exhibits partial strain recovery, but a residual volumetric strain of ~ 32% persists, see dark shaded area in Fig. 3 d. The presence of an irreversible strain component suggests underlying permanent microstructural changes, such as solid electrolyte interphase (SEI) growth or plastic deformation 51 . Indeed, a deeper understanding regarding the asymmetry of the strain distribution in the electrode is gained by analysing the upper region adjacent to the current collector and lower region near the separator of the electrode, separately. As shown in Fig. 3 d, strain differences are small at early stages of lithiation, see timestep T2, but diverge with state of charge. By T6 the separator-side region averages about 50% volumetric strain, while the current-collector side averages about 34%. Further, we quantify the emergence of strain heterogeneity by plotting the histograms of volumetric strain for the two regions at T2, T4, T6, and T8, see Fig. 3 e. At timestep T2 both distributions are narrow and centred likewise, consistent with a uniform expansion. However, as lithiation progresses, the distributions broaden significantly, reflecting increased spatial heterogeneity. By T6 the separator-side distribution at the bottom of the electrode shows strain values exceeding 100% in some areas, while the current-collector side at the top includes areas with compressive strains down to − 50%. In Fig. 3 f the temporal evolution of the mean axial strain components XX, YY and ZZ over the entire anode is further studied to understand the dominant mechanical loading direction. The results strengthen the finding that the deformation is predominantly uniaxial, with expansion primarily along the electrode thickness in z- direction. The in-plane strain components ε xx and ε yy remain below 3% throughout, while the axial expansion ε zz accounts for nearly all volumetric change. This observation aligns with the macroscopic electrode swelling shown in Fig. 2a and reflects the inherent mechanical anisotropy of the cell, governed by stack pressure and boundary conditions. It also is in accordance with the particle movement illustrated in Fig. 2b . The independent particle tracking based on segmentation, see details in Supp. Figure 9 , supports further the presented strain analysis. While lateral particle displacements in the xy-plane are minimal, axial displacements vary markedly with position within the electrode. Particles near the current collector shift by ~ 2 µm, while those near the separator move up to ~ 11 µm, corresponding to local swelling of nearly 60%. The observed axial strain gradient, reflects boundary and transport conditions. Mechanical constraints are imposed by the rigid current collector, which restricts expansion at the top and favours deformation toward the less confined separator side, whereas lithium ions access the electrode from the separator side via electrolyte-filled pores. The revealed strain asymmetry observed in the electrode suggests a preferential lithiation, SEI formation and strain accumulation near the separator interface 52 . Three-dimensional strain evolution in the particle vicinity during Li insertion and extraction. (c) Orthogonal views of volumetric strain at T6 relative to T0, overlaid on the T0 microstructure. Slices are extracted along the planes indicated in the 3D renderings (blue, XZ; yellow, XY; red, YZ). Contours mark equal-strain levels. Four equally spaced slices are depicted along each orientation to visualize in-plane variations. The strain colormap spans compressive − 50% (blue) to tensile + 50% (red). Small and large Si particles, indicated by sp-Si and lp-Si are shown in light grey, CBD/Pores in dark grey. Scale bars, 5 µm. (d) Temporal evolution of volumetric strain for four additional particle-centred volumes of interest. The local mechanics is further analysed in three dimensions around individual particles distributed in the electrode upon charging and discharging, to uncover the chemo-mechanical process on particle level. As depicted in Supp. Figure 10 , the lithiated anode exhibits modest local thickness variations across the field of view, indicating non-uniform lithiation kinetics and local stress concentration sites within the electrode. To trace the evolution of the particle vicinity in three-dimensions, we isolate 15 x 15 x 15 µm³ sub-volumes centred on an exemplary silicon particle located in the electrode under investigation, see Fig. 4 a. All timesteps are spatially aligned based on the centre of mass of this central particle at each respective timestep. The approach fixes a particle-centric reference frame that removes global rigid body motion and electrode-scale expansion from the local analysis. Subsequently, volumetric strain fields are computed between successive timesteps from T0◊T2, T2◊T4, T4◊T6 and T6◊T8, see Fig. 4 b. In this frame, the central particle exhibits near-zero apparent strain by design, while surrounding windows capture the relative deformation of the neighbouring microstructure, described by other particles, CBD and pore network. The evaluated successive three-dimensional strain maps show progressive inhomogeneous accumulation of tensile strain in the neighbourhood of the centred Si particle during lithiation, reaching a maximum at timestep T6. Displacement vectors indicate expansion toward locally compliant pores in the vicinity of the particle. After partial delithiation at T8, strain magnitudes decrease relative to T6 and return to levels between those observed at T4 and T5, which exhibit a similar SOC. This trend is consistent with alloy driven expansion of Si and partial reversibility upon Li extraction which generates mechanical stress in confined architectures 11 , 14 , 53 , 54 . Additionally, solid electrolyte interphase growth may also contribute to the observed deformation 55 – 58 . Next the impact of the surrounding microstructure on the particle-resolved strain distribution in different planes, is assessed in more detail. Hence, orthogonal slices through the three-dimensional microstructure at timestep T6 relative to T0 are presented in Fig. 4 c. The volumetric strain distribution projected on the microstructure reveals for different planes that regions containing many smaller sized particles (sp-Si), embedded in CBD, exhibit elevated strain, whereas narrow gaps confined between closely packed large particles (lp-Si) show comparatively low strain. Further, high local porosity near particles accommodates expansion by pore collapse and thereby helps to relieve strain. Hence, an inhomogeneous strain field in the vicinity of the particle conditioned by the microstructure results, also suggesting significant impact on the lithiation at the particle´s interface, see Fig. 2e and f . Post-mortem FESEM cross-sections on electrode level, see Supp. Figure 11 , support these observations, revealing microstructural precursors for strain localization such as binder-rich zones, porosity variations and a highly inhomogeneous Si particle size distribution. Regions dominated by large Si particles show only minor irreversible thickness increase, whereas areas rich in sub-micron particles exhibit greater residual thickening, consistent with enhanced SEI formation driven by their higher surface area 59 , 60 . Thus, the resulting depicted three-dimensional inhomogeneous strain in the particle vicinity affects the chemical reaction and further deepens the understanding of the underlying chemo-mechanical process. This observation is in line to prior findings 61 – 63 which have identified SEI constituents such as fluorine-rich layers and carbonate-based species, as well as residual Li x Si phases that resist full delithiation, as contributing factors to irreversible expansion. Pronounced strain heterogeneity within the electrode, becomes even more evident when analysing multiple particle-centred volumes of interest (VOI), see Fig. 4 d. The analysis provides important information concerning the initial chemo-mechanical process, which is indeed highly relevant for observations made at longer cycling 17 , 18 . It reveals that location-dependent strain heterogeneity emerges already at the first cycle of the cell within the anode microstructure. Between T1 and T2 the mean volumetric strain increases similarly across VOIs, but the strain evolution diverges strongly as lithiation progresses, consistent with the trends in Fig. 2 and Fig. 3 . At T6, some VOIs exhibit modest average volumetric strain of about 25%, whereas others reach 60% (e.g., subvolume 4 and 3, respectively), with local peaks larger than 150% at inter-particle contacts and within constricted pore regions. See also Supp. Figure 12 for further detail. In addition, local heterogeneities can be also triggered by possible transient gas evolution, as shown in tomographic series, see Supp. Figure 13 . Here exemplary a void as a local perturbation appearing between timestep T1 and T2 and disappearing again between T4 to T5, is illustrated. The temporary emergence suggests gas generation, likely from electrolyte decomposition or reactions of absorbed water 64 – 66 . As indicated by the volumetric strain analysis, such gas bubbles can both concentrate and relieve stress locally, disrupt particle networks and drive mechanical inhomogeneities. Divergent particle-level responses revealed by residual analysis Figure 5: Divergent particle-level responses to lithium insertion and extraction. (a-b) Time series for residual maps for a representative (a) core–shell-like and (b) non-core–shell-like (de)lithiation response. States T1, T2, T3, T4, T5, T6 and partially delithiated T8 illustrate the growth of residual features during lithiation and their partial regression upon lithium extraction within the Si particle. Higher residual intensity, in red and blue for core-shell (cs)- and non-cs-like, respectively, indicates regions with higher grey value changes upon (de)lithiation. For improved visibility of the cs-like residual structure, the particle contour is overlaid on the cs-like particle at T6. (c) Orthogonal tomographic slices in different planes exemplary at T3 and T6 of the cs-like particle shown in (a), with residual overlay (red contour). (d) Orthogonal slices at T3 and T6 for the non-cs particle shown in (b) with residual overlay (blue contour). Complex internal network emerges within an initially intact particle and intensify by T6 upon lithiation. Some features diminish after delithiation, consistent with a network-mediated transformation rather than a single advancing front. (e) Post-mortem FESEM of the cell with elemental EDS maps in the delithiated state (after T8) corroborates in situ observations. The anode cross-section exhibits pronounced thickness variations. Magnified regions (red and blue box) show network-like interiors in some particles with weak F and C signals, alongside particles displaying mechanical cracks. The key challenge is to study spatially the mechanical response of individual silicon particles during lithium insertion and extraction. Macroscopic deformation patterns arise from particle-scale dynamics and, in turn, bias those dynamics through changing contact networks and local confinement. To further resolve the underlying structural transformations, we compute DVC residual fields between two representative states extracted from the underlying electrode. The DVC-measured deformation is applied to the initial volume, geometrically matching it to the later configuration, e.g. the T0-deformed-to-T6 timestep. By subtracting the deformed volume of the initial state from the later dataset, we isolate residuals within the particle that reflect local material changes beyond mere positional shifts, and allow to draw conclusion about the underlying particle lithiation behaviour, see Methods for further details. Figure 5a and b contrast two distinct particle responses in 3D from timestep T1 to T6 and at T8, upon (de)lithiation. The exemplar core–shell(cs)-like particle in Fig. 5a show faint, surface-limited residuals at T3 that evolve into a more continuous shell by timestep T6, while the core remains largely unchanged, consistent with a surface-limited lithiation front and minimal internal restructuring at the accessible spatial resolution. The Si particle core appears morphologically stable, with no visible cracks or internal microstructural transformations, see in particular timestep T6 where the particle is visualized together with the emerging residuals. Here, surface localized residuals and subtle grey-value shifts indicate limited lithiation-induced changes at the particle´s periphery. In contrast, the non-cs particle in Fig. 5b already exhibits residual pathways that traverse the particle in all three directions at timestep T3. By T6 these pathways broaden, new branches appear and features brighten, indicating increasing local transformation and a complex distributed, 3D network-type lithiation. After partial delithiation at T8 several pathways fade or retract, indicating partial reversibility. The onset and amplification of these changes are consistent with the macroscopic electrode response described above as well as follow the voltage characteristic, see in particular Fig. 3 and Fig. 2d . Orthogonal tomographic slices extracted at timesteps T3 and T6 along the planes indicated in Fig. 5a,b (T3) further resolve these structural characteristics and their evolution for the cs- and non-cs particles in more detail, see Fig. 5c,d and Supp. Video 2 and 3 . Supplementary Fig. 14 shows an additional example of such emerging network structures upon partial lithium extraction within the particle. The study includes cases where the network contrast nearly disappears. Together, these observations indicate that cs-like particles remain predominantly surface-limited over T0–T8, whereas non-cs particles undergo internal, network-mediated transformation. These branched lithiated domains within the particles observed here in 3D in the first electrochemical cycle, ultimately extend prior 2D post-mortem observations made by Häusler et al. 18 regarding the underlying initialization of local microstructural and strain modifications, which in turn impact the electrochemical performance of the Si-based cell after long cycling. Supplementary Fig. 15 also indicate particles already fractured before initial charging. Correlative analysis between particle and electrode-level reveals that such pre-cracked particles are predominantly located near the electrode surface. Indeed, processing-induced damage during steps such as calendaring might explain the performed observation. The presented post-mortem FESEM imaging of the delithiated electrode after one cycle in Fig. 5e corroborates the in situ-based nano-SXCT analysis. A couple of particles display faint, network-like domains. EDS analysis of these regions within the Si particle reveal neither fluorine presence nor silicon loss, arguing against SEC infiltration or the onset of dendrite formation 17 , 18 . Furthermore, it excludes fracture as the origin, since it affiliates to a different behaviour than observed for the crack, see Fig. 5e . Supp. Figure 16 , further indicates that these networks expand with cycling. The presented approach allows correlative 3D investigations over different length scales, from cell to single particle-level. Results indicate that the classical and common core-shell mechanism represents only one of several lithiation possibilities and strongly depend on the chemo-mechanical response. The latter is modulated by local particle-specific factors such as defect state, local microstructural environment and lithiation kinetics. Within the scanned volume, illustrated in Supp. Figure 17 , about 10% of the particles follow a cs-like response in the first lithiation insertion. Most common behaviour involves rather the lithiation along complex networks within the particle. The in-depth correlative multiscale tomographic analysis suggests that Si lithiation is thus intrinsically heterogeneous, governed by global as well as local features like the particle size distribution, particle location within the electrode and surrounding microstructure, state of charge but also by processing-induced damage, electrode architecture and cell configuration, respectively. Conclusion This work provides enhanced insights on the chemo-mechanical process linking electrode-scale deformation to particle-scale mechanics for cells with high silicon (Si) content and paired with nickel-manganese-cobalt (NMC) cathodes, by combining correlative multiscale 3D in situ characterization. The combination of a pressure-controlled in situ cell design with high-resolution synchrotron X-ray nano-tomography, AI-driven segmentation and 4D strain mapping enables the detection of pronounced spatial deformation and strain heterogeneities from the electrode scale down to individual Si particles. The observed strain heterogeneity on different length scales has direct implications for industrial electrode design. Micron-sized silicon particles, including those sourced from industrial cutting waste, offer a scalable and cost-effective alternative to engineered nanostructures 22 or sophisticated coated architectures 21 , but their successful deployment hinges on mitigating mechanically driven degradation. Our findings highlight several design levers for optimizing not only micron-sized Si but also nano-porous and other advanced Si architectures. First, at the particle level, most particles do not follow a simple core–shell pathway. Instead, internal complex network-like transformation routes emerge within the particle and partly regress on delithiation. Minimizing fabrication-induced defects is paramount since defects act as stress concentrators and fracture nucleation sites. Implementing quality control protocols to detect and screen out cracked particles prior to integration could significantly improve cycling stability. Surface engineering to guide SEI formation and regulate lithium flux 67 could influence how and where lithiation begins, potentially steering the transformation pathway away from high-strain configurations. Second, the particle adjacent microstructure in context to pores, particle size and distribution influence both the extent and reversibility of lithiation-induced strain since larger particles show a different lithiation behaviour than smaller ones. A tighter size distribution could promote a more uniform mechanical response across the electrode, thereby reducing local stress heterogeneities. Third, our results highlight that mechanical failure is often dictated not by total expansion but by localized strain accumulation at both particle and electrode scales. The presented correlative multiscale framework provides a basis for engineering electrode architectures that moderate lithiation gradients and redistribute stress more evenly. Likewise, adjusting charging protocols, such as employing adaptive current profiles 68 , 69 , may reduce the severity of transient strain during fast charging and extend electrode lifetime. Ultimately, these results indicate that failure risk is controlled by strain localization and microstructural context, rather than bulk expansion alone. A correlative multiscale 3D view of the underlying chemo-mechanical processes is therefore essential for rational design. Practical levers include reducing fabrication-induced defects, tightening particle-size distributions, and designing architectures that moderate local strain gradients. By integrating advanced quantitative multiscale imaging, AI-based morphological analysis and mechanically realistic operating conditions, this study provides not only deeper understanding but also a diagnostic and design framework for durable, high-capacity Si anodes. The approach is broadly applicable beyond liquid-electrolyte Li-ion systems, including solid-state batteries employing Si-based anodes. Materials and Methods Material preparation The silicon-based anode was composed of 89 wt% micron-sized silicon particles (median size: 3–7 µm; CLM 00001 / Wacker Chemie AG), 9 wt% polyacrylic acid (PAA)-based binder (AQUACHARGE (water solution) / SUMITOMO SEIKA), 1.8 wt% carbon black (Super C65 / IMERYS) and 0.2 wt% single-walled carbon nanotubes (Tuball BATT H2O / OCSIAL). The electrode slurry was cast onto a copper foil and subsequently calendared, yielding electrodes with an areal loading of 3 mg cm − 2 and a theoretical areal capacity of approximately 11 mAh cm − 2 . However, to avoid fully utilizing the anode’s capacity, its effective capacity was limited to ~ 3.5 mAh cm⁻² by pairing it with a cathode of matching capacity. As the cathode, a nickel–manganese–cobalt-oxide (NMC811, 3.5 mAh/cm2), consisting of 96.5 wt% NMC811, 1.5 wt% PVDF-based binder and 1 wt% carbon black, was employed. Circular electrodes with a diameter of 1.100 ± 0.001 mm were precisely cut utilising a 3D Micromac microPREP PRO femtosecond laser with a laser power of 35 mW to ensure reproducible geometry (see Supplementary Note 1 for further details). Cell assembly The prepared electrode discs (1.100 ± 0.001 mm) were precisely assembled into a custom-designed in situ electrochemical cell, based on the setup described here 36 . A non-woven polypropylene separator (1.5 mm diameter), soaked in 0.5 µL electrolyte composed of 1 M lithium hexafluorophosphate (LiPF₆) in fluoroethylene carbonate (FEC) and diethyl carbonate (DEC) (2:8 v/v) with 2 wt% vinylene carbonate (VC), was placed between the electrodes. The cell housing was constructed from perfluoroalkoxy alkane (PFA) tubing (inner diameter 1.6 mm, outer diameter 3.2 mm), which is compatible with synchrotron imaging chosen for its low X-ray attenuation, chemical resistance and mechanical robustness. Threaded stainless steel mounts were screwed into both ends of the tubing to create a sealed enclosure. A central feature of the cell design is the ability to apply a precisely adjustable and fixed mechanical pressure to the electrode stack via a spring-loaded contact inserted through the upper steel mount. For the 1.1 mm diameter cell used in this study, the applied pressure could be tuned across a wide range - from 0.01 to 1.5 MPa. During experiments, the spring was fixed to apply a constant pressure of 0.2–0.4 MPa. This adjustability is essential for optimizing and standardizing contact between cell components while minimizing mechanical deformation of the active material. A stable and defined pressure ensures consistent electrochemical performance, reproducibility between cells and preserves the integrity of microstructural evolution during in situ imaging. To maintain an inert environment and prevent air ingress, all interfaces between the steel mounts, polymer housing and spring contact were sealed with lacquer. The entire cell assembly was performed inside an argon-filled glovebox. The complete cell setup was further mounted on a polyetheretherketone (PEEK) cylindrical-shaped support to ensure mechanical stability and chemical compatibility during cycling and imaging on the sample rotation stage at ID16B. Finally, the electrodes are electrically connected to a potentiostat 70 . For the lower mount, see Fig. 1c , a banana plug was utilized. At the upper terminal, a copper wire was wrapped tightly around the spring contact and was further secured with parafilm. Soldering was avoided to prevent any heat-induced damage. The flexibility of the yet secure electrical setup enables sample rotation about the z-axis for uninterrupted in situ monitoring without compromising electrochemical or mechanical cell integrity. Additional assembly details are provided in Supplementary Note 2 . Despite employing several measures to ensure high-quality electrode fabrication and assembly, such as femtosecond laser cutting to ensure flat, uniform edges and a parallel layer stack, the high mass and electron density of Cu introduce X-ray scattering artefacts in the phase images, resulting in localized image degradation and blurring near the current collector in the resulting 3D volumes. Consequently, these blurred regions are excluded from strain analysis. Electrochemical charging and discharging protocol Electrochemical cycling was performed in situ using an OrigaFlex OGF500 potentiostat during synchrotron X-ray computed nano-tomography (nano-SXCT) acquisition using a custom script-controlled protocol. The cell was first charged using a two-step constant current–constant voltage (CC–CV) strategy. In the constant current (CC) phase, the cell was charged at a rate of C/3 until either a voltage of 4.3 V was reached or a maximum time of 30 minutes elapsed. If the voltage limit was reached before timeout, the protocol transitioned into the constant voltage phase. Otherwise, a tomographic scan was triggered. In the subsequent constant voltage (CV) phase, the voltage was held at 4.3 V. Again, if either the current dropped below a predefined threshold (C/10) or 30 minutes had passed, a scan was initiated and the loop continued. The charging sequence continued until either a defined number of scans (n = 6) had been reached or the current had sufficiently stabilized. Following the final charging scan, the cell was discharged under constant current conditions at a rate of C/6 until the lower voltage cut-off of 2.5 V was reached. To determine noise induced from the SXCT scan, two final scans without additional discharge at timestep T8 and T9 were acquired without intervening electrochemical activity, see Supp. Figure 18 . To minimize artefacts arising from mechanical or thermal relaxation during tomography, the cell was temporarily switched to open-circuit voltage (OCV) one minute prior to each scan. Once acquisition was complete, electrochemical cycling resumed automatically. Further experimental details and a detailed flowchart of the control logic, including all decision pathways and fail-safes, are provided in the Supplementary Note 3 . Cell SoC values reported in the main text refer to full-cell SoC. By design this corresponds to ~ 1/3 anode capacity utilisation ( Methods: Material preparation ), owing to cathode-limited cycling. In situ X-ray nano-tomography measurement In situ X-ray nano-tomography was performed at the beamline ID16B 41 of the European Synchrotron Radiation Facility (ESRF) in Grenoble, France, using holo-tomography 71 . The imaging was conducted with a monochromatic, conical X-ray beam at an energy of 29.6 keV and a flux of ~ 10¹² photons per second. Phase-contrast information was acquired by collecting radiographs at four different propagation distances, enabling accurate phase retrieval. Each tomographic dataset comprised 2505 projections acquired over a 360° sample rotation around the axial direction (z-direction), with an exposure time of 20 ms per projection. In addition, 20 flat-field and 21 dark-field images were recorded per scan. Data were collected using a PCO Edge 4.2 CMOS camera (2048 x 2048 pixels) coupled with a 30 µm thick LSO scintillator. The total acquisition time per holo-tomography scan was approximately 10 minutes. The voxel size for in situ scans was 50 x 50 x 50 nm³. Data reconstruction and processing The 3D reconstruction was performed with the open-source software PyNX 72 through a two-step approach. Firstly, an iterative phase retrieval step was applied using as an initial guess a Paganin-like approach with a complex refraction index ratio δ/β = 170. Subsequently, a filtered back-projection reconstruction was performed using the ESRF software Nabu 73 . Ring artefact reduction was applied post-reconstruction using an in-house developed correction algorithm. The final reconstructed volumes measured 102.4 x 102.4 x 102.4 µm³ with a voxel size of 50 x 50 x 50 nm³ and were saved in 16-bit unsigned integer format. To enhance image contrast and improve visualization, histogram equalization was applied in a final post-processing step. Machine-learning image segmentation To segment different material phases in the reconstructed tomography volumes, a deep learning-based approach was applied using an attention residual U-Net architecture 74 implemented with the Python Keras library. Two separate models were trained to account for structural changes over time: Model 1 for early timesteps (T0–T2) and Model 2 for later stages (T3–T8). Initial labels were generated using Ilastik 75 and 12 annotated slice images per model (before augmentation) were selected for training. Image sizes were 256 x 512 px, with Model 1 using 4 slices per timestep and Model 2 using 2 slices per timestep. Data augmentation was performed to expand the dataset threefold. Both models were trained for 150 epochs on an NVIDIA RTX A5000 GPU. Additional details are provided in Supplementary Information . The final 3D visualization of the segmented data was accomplished using Dragonfly 3D World, Version 2024.1 76 . Calculation of spatial resolution Spatial resolution was estimated by analysing greyscale intensity transitions at particle interfaces. This involved manually selecting particle edges and extracting orthogonal line profiles across them. At these interfaces, the greyscale intensity exhibits characteristic changes due to phase contrast. The resolution was quantified as the full width at half maximum (FWHM) of the derivative of the greyscale profile, which was approximated by a quadratic function, following a similar approach as described in Häusler et al. 70 . A representative line profile is provided in Supp. Figure 8 . Strain analysis Quantitative 3D strain analysis was performed using the open-source Software for Practical Analysis of Materials (SPAM) 48 , which implements a digital volume correlation (DVC) based framework to measure 3D displacement and strain fields from a pair of X-ray tomography images. The analysis workflow began with two global registration steps: an initial “eye registration” for coarse manual alignment, followed by an automatic “non-rigid registration” step that estimates a single linear and homogeneous deformation function (Φ) mapping the reference image volume 1 into image 2 accounting for affine transformations: translations, rotations, normal and shear strain. The correlation procedure is based on a gradient-based iterative algorithm that minimizes the difference between the two images, progressively correcting the latter by a trial deformation function. Convergence is evaluated when a stable solution is reached, based on δΦ of the deformation function increment between two successive iterations. Local strain measurements were computed using SPAM’s Local Digital Image Correlation (LDIC) module. This approach subdivides the image volume into a regular 3D grid of points and performs independent non-rigid correlations within local sub-volumes (correlation windows) centred on each point. Material deformations were tracked solving the above iterative algorithm for each sub-volume across successive timepoints. A pyramidal refinement approach was employed to improve correlation resolution, progressively reducing the node spacing (ns) from 100 to 70 and finally to 35 pixels. The half-window size (hws) was set equal to the node spacing at each refinement step, ensuring 50% overlap between adjacent correlation windows. A final window size of 3.5x3.5x3.5 µm³ (70³ voxels) was selected as optimal, balancing spatial resolution and convergence robustness. Displacement noise in the measured Φ-fields was filtered by replacing non-converged nodes with values interpolated from their neighbouring eight nodes before further processing. This filtering process helps to decrease the errors within the convergence loop. To quantify cumulative deformation over multiple timesteps, sequential deformation fields (e.g., T0→T1, T1→T2, T2→T3) were combined to construct cumulative mappings (such as T0→T3) based on a multiplicative composition of the incremental local deformation functions. Total strain tensor components were then derived from the spatial gradients of these accumulative displacement fields using SPAM’s strain field calculation routine, which operates on the regularly gridded displacement data. See also Supplementary Note 5. The strain mapping approach was applied at two spatial scales to capture both localized deformation around individual particles and global strain gradients across the electrode: Local strain analysis (particle-centred frame): To investigate local strain behaviour in the immediate vicinity of individual particles, cubic sub-volumes of 15x15x15 µm³ or 15x15x10 µm³ were extracted, each centred on a selected silicon particle. For each timestep, the particle’s centre of mass was calculated and the sub-volume was cropped accordingly to establish a fixed local reference frame. This approach effectively removes global electrode displacements, isolating the relative deformation within each particle’s neighbourhood. Electrode-scale strain mapping (electrode-centred frame): For electrode-scale analysis, the full imaged volume of 102.4x102.4x102.4 µm³ was subdivided into larger 40x40x40 µm³ regions (see Supp. Figure 19 ), enabling spatially resolved strain mapping across the entire electrode thickness. Residual mapping of local structural deviations based on DVC analysis To visualize local structural deviations, residual maps were generated based on the accumulative multiplicative deformation fields (Φ). For each subsequent timepoint (T1 through T8), Φ-fields were computed relative to the reference state T0. These Φ-fields were then used to deform the reference image, generating predicted synthetically deformed volumes for each timepoint (e.g., T0-deformed-to-T6). Residual images were obtained by subtracting the deformed reference image (T0-deformed-to-T6) from the corresponding original image at that timepoint (T6). Subtraction was performed in ImageJ (Fiji) 77 , followed by a Gaussian blur (σ = 2) to suppress high-frequency noise and an (abs)-function to normalise the residual values. Finally, based on the double-scan error intensities, a level of 5000 residual values was considered as measurement noise and removed from the fields, isolating high residual features indicating non-linear structural transformation, as shown in Supp. Figure 18 . FESEM analysis Cross-sectional preparation of the anodes was performed using a Hitachi IM4000 + ion milling system, which employs low-energy argon ions to create clean cross sections without introducing mechanical stress to the sample. Field-emission scanning electron microscopy (FESEM) was conducted on a ZEISS GeminiSEM 450 at an acceleration voltage of 5 kV and a probe current of 3 nA. Energy-dispersive X-ray spectroscopy (EDS) was performed using an Oxford Ultim Extreme detector (1024 x 768 pixels) at an acceleration voltage of 3 kV and a current of 3 nA, see also Supplementary Note 6 . Declarations Conflicts of interest: The authors declare no conflicts of interest. Author contributions: Conceptualization: M.H. and R.B.; Experimental concept: M.H.; Material fabrication: C.S. and S.K.; Sample preparation: M.H.; In situ measurement: M.H., R.J.S., O.S., J.V. and R.B.; DVC analysis: M.H., R.J.S. and O.S.; Visualization: M.H. and R.J.S.; Supervision: R.B.; Writing: M.H. and R.B.; All authors contributed to discussions of the research. Acknowledgments The authors gratefully acknowledge the financial support under the scope of the COMET program within the K2 Center “Integrated Computational Material, Process and Product Engineering (IC-MPPE)” (Project ASSESS P1.10) and the funding by the Austrian Research Promotion Agency (FFG) from the Mobility of the Future programme, Proj. No. 891479 “OpMoSi”. ESRF is acknowledged for beam time allocation and access (proposal MA-4927 78 & MA-6174 79 ) at ID16B beamline. Furthermore, Charlotte Cui is acknowledged for her support during laser preparation. Data availability: All data supporting the findings of this study are available within the article and its Supplementary Information. The underlying nano-SXCT datasets generated and analysed during the current study are publicly available via the ESRF data repository under the DOIs doi.org/10.15151/ESRF-ES-1190113340 and doi.org/10.15151/ESRF-ES-1579881493 . 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Preprint at https://doi.org/10.15151/ESRF-ES-1190113340 Häusler M, Sinojya R, Stamati O, Brunner R (2024) In-situ nano-tomography of Si-based anodes to reveal the particle displacemnet upon different charging conditions [Dataset]. doi.org/doi.org/10.15151/ESRF-ES-1579881493 . European Synchrotron Radiation Facility. Preprint at https:// Additional Declarations There is NO Competing Interest. Supplementary Files Supp.Video1.mp4 Time evolution electrode Supp.Video2.mp4 Cross section of core-shell- like particle Supp.Video3.mp4 Cross section of non-core-shell- like particle Supp.InfoNatureFinal.docx Spplementary Information Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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1","display":"","copyAsset":false,"role":"figure","size":632587,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNano-SXCT setup and custom in situ cell\u003c/strong\u003e. (a) Schematic of the layered Li-ion cell utilized for in situ nano-SXCT experiment at ESRF ID16B. The cell consists of a ~20 µm thick, silicon-based anode and an NMC cathode with 1.1 mm diameter, coated onto a copper and aluminium current collector, respectively. In between the electrodes, an electrolyte-soaked separator with a 1.5 mm diameter is placed. (b) Backscattered electron (BSE) FESEM cross-section of the pristine anode, showing the copper current collector at the top. The right-hand panels display the EDS maps of silicon (Si), oxygen (O) and carbon (C), from a magnified region, highlighting silicon particles and the carbon binder domain (CBD). The anode is graphite-free. (c) In situ cell assembly: The cell is inserted into a PFA tube (inner/outer Ø 1.6/3.2 mm). The tube is then closed on both ends with stainless-steel screw mounts. A spring contact is adjusted to apply a predefined external pressure as well as to ensure stable electrical contact. The assembly is mounted onto a PEEK support at the rotation stage. Electrical connection from the potentiostat to the cell is established via a banana plug at the lower mount and by wrapping a 0.8 mm copper wire around the top of the spring contact, respectively. During tomography, the X-ray beam passes perpendicular to the rotation axis in xy-direction. (d) Reconstructed nano-SXCT volume (field of view 102.4 x 102.4 x 102.4 µm³; voxel size 50 nm). The dark top layer is the copper foil, beneath is the Si anode and the bright layer corresponds to the separator. The measurement resolves particle scale morphology suitable for quantitative analysis.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8273007/v1/22b7ad8940849f906749ec60.png"},{"id":98385306,"identity":"31ed442d-63d4-4432-829b-4d8a2a4b845b","added_by":"auto","created_at":"2025-12-17 08:28:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":7156971,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMorphological evolution and phase-contrast-driven segmentation of non-lithiated silicon upon charging. \u003c/strong\u003e(a) Representative nano-SXCT reconstructions of the anode from timesteps T0 (pristine) to T6 (cell: ~85% SOC). The Cu current collector lies above the orange dotted line, the porous separator is visible at the bottom of the anode. At the pristine state the Si particles and CBD+electrolyte are indicated by dark and light grey, respectively. Electrode expansion is traced by dashed red lines. ROI to study the evolution on particle level is indicated by a green dotted box. Representative particles are highlighted by red, green and blue. The scalebar refers to 5 µm. (b) ROI to track representative particles in red, green and blue, respectively, during charging using semantic segmentation. Scalebars refer to 3 µm. (c) Axial average anode thickness and relative non-lithiated (RNL) phase volume from Si particles distributed in the electrode from T0 to T6. (d) \u0026nbsp;Cell voltage profile during a charge–discharge cycle with tomography time points from T0 to T9. Charging is done at constant current C/3 to 4.3 V, then constant-voltage hold at 4.3 V. At T6 the cell reaches ~85% SoC. T7 – T9 are recorded during/after partial discharge at constant current C/5 to 2.5 V. Nano-SXCT cross-section of the blue particle at T0 and T6 with dashed lines in orange (e) and yellow (f) highlighting a path at T0 through the CBD+E and Si interface (pristine state) as well as a path within the Si particle core, respectively. See also the path at T6. Particle contour of T0 is indicated and overlaid as reference for timestep T6. (g,h) Corresponding greyscale profiles vs. pixels (px) at T0 (black) and T6 (red) along the orange (g) and yellow (h) dashed line indicated in (e,f). Background colours highlight the region of lithiated and non-lithiated Si phases. Vertical dashed line illustrates the shift of the dark grey regions interface from T0 to T6 in (g).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8273007/v1/97bdfe945f29dedd98a72bd0.png"},{"id":98440452,"identity":"83394bfd-8e7a-4e2d-9fac-78e34ca3a44a","added_by":"auto","created_at":"2025-12-17 17:03:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":4836989,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eElectrode-scale evolution of volumetric and axial strain.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a) Local digital volume correlation (local-DVC) grid on a representative anode sub-volume (40 x 40 x 40 µm³) at T0. A node spacing (ns) of 35 voxels and a half window size (hws) of 35 voxels, give overlapping 70³-voxel correlation windows (red cube). (b) DVC principle: a regular grid of correlation windows is tracked between a reference volume (Tn) and a deformed volume (Tn+1), yielding local displacement vectors at window centres (illustrated by a green arrow). From the displacement field, local strain tensors are computed. The schematic of a deforming Si particle illustrates this approach. (c) A nano-SXCT vertical cross-section (T0) indicating the divided current-collector side (orange) and separator side (blue). Right: Corresponding axial strain maps at T2, T4, T6 and T8 referenced to T0. \u0026nbsp;Effective axial strain, is mapped from compressive (blue, –100%) to tensile (red, +150%). The scale bar corresponds to 10 µm. (d) Evolution of volumetric strain is shown for the current collector (orange) and separator (blue) side, as well as for the whole electrode (red), revealing spatial heterogeneity. (e) Extracted histograms indicate the local volumetric strain distributions in the upper and lower electrode regions at T2, T4, T6 and T8. Maxima are highlighted by arrows. A progressive broadening and skewing of the strain distributions, indicates increasing heterogeneity and asymmetry. (f) Temporal evolution of the axial strain components (XX, YY, ZZ) over the entire anode. Light grey and dark grey backgrounds indicate timepoints corresponding to lithiation and delithiation, respectively. Orange and blue lines represent the strain in the upper and lower regions, respectively.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8273007/v1/2994c0c38e57e04f4d22146d.png"},{"id":98440471,"identity":"e6d67815-fbe9-4039-a118-3718f0dad600","added_by":"auto","created_at":"2025-12-17 17:03:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":15773929,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVolumetric strain analysis on particle level.\u003c/strong\u003e (a) Nano-SXCT reconstructions of 15 x 15 x 15 µm³ sub-volumes at T0, T2, T4 and T6. The T0 volume is rendered semi-transparent to highlight the central particle to which all timesteps are registered. (b) Incremental three-dimensional volumetric-strain maps, each referenced to a preceding step, e.g. T0àT2, whereas T0àT2 illustrates exemplarily a transparent 3D representation to highlight the central particle. The corresponding morphology is overlaid to facilitate interpretation of local strain changes during (de)lithiation. The strain colormap spans compressive −50% (blue) to tensile +50% (red). Further, displacement vectors to indicate local expansion directions are shown for T4àT6 and T6àT8.\u003cbr\u003e\n(c) Orthogonal views of volumetric strain at T6 relative to T0, overlaid on the T0 microstructure. Slices are extracted along the planes indicated in the 3D renderings (blue, XZ; yellow, XY; red, YZ). Contours mark equal-strain levels. Four equally spaced slices are depicted along each orientation to visualize in-plane variations. The strain colormap spans compressive −50% (blue) to tensile +50% (red). Small and large Si particles, indicated by sp-Si and lp-Si are shown in light grey, CBD/Pores in dark grey. Scale bars, 5 µm. (d) Temporal evolution of volumetric strain for four additional particle-centred volumes of interest.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8273007/v1/4b24a3aee51ee5081d0b7bc6.png"},{"id":98440292,"identity":"5d109a4c-eb26-4968-a013-fb6b5c081d0b","added_by":"auto","created_at":"2025-12-17 17:03:40","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":16633280,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDivergent particle-level responses to lithium insertion and extraction. \u003c/strong\u003e(a-b) Time series for residual maps for a representative (a) core–shell-like and (b) non-core–shell-like (de)lithiation response. States T1, T2, T3, T4, T5, T6 and partially delithiated T8 illustrate the growth of residual features during lithiation and their partial regression upon lithium extraction within the Si particle. Higher residual intensity, in red and blue for core-shell (cs)- and non-cs-like, respectively, indicates regions with higher grey value changes upon (de)lithiation. For improved visibility of the cs-like residual structure, the particle contour is overlaid on the cs-like particle at T6. (c) Orthogonal tomographic slices in different planes exemplary at T3 and T6 of the cs-like particle shown in (a), with residual overlay (red contour). (d) Orthogonal slices at T3 and T6 for the non-cs particle shown in (b) with residual overlay (blue contour). Complex internal network emerges within an initially intact particle and intensify by T6 upon lithiation. Some features diminish after delithiation, consistent with a network-mediated transformation rather than a single advancing front. (e) Post-mortem FESEM of the cell with elemental EDS maps in the delithiated state (after T8) corroborates in situ observations. The anode cross-section exhibits pronounced thickness variations. Magnified regions (red and blue box) show network-like interiors in some particles with weak F and C signals, alongside particles displaying mechanical cracks.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-8273007/v1/074bb01861f4a74706b979c8.png"},{"id":100857847,"identity":"b6632a67-b813-4c58-bd8f-49ef562d8ed2","added_by":"auto","created_at":"2026-01-22 07:23:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":40529153,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8273007/v1/e9f441fd-4b57-41bc-af49-f7854ded7401.pdf"},{"id":98385307,"identity":"9c42b8f7-7c82-4d79-a6a8-b7332bdae7a3","added_by":"auto","created_at":"2025-12-17 08:28:50","extension":"mp4","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3639091,"visible":true,"origin":"","legend":"Time evolution electrode","description":"","filename":"Supp.Video1.mp4","url":"https://assets-eu.researchsquare.com/files/rs-8273007/v1/52b0526c0be87357f80329bd.mp4"},{"id":98385221,"identity":"4cfc314c-8226-4141-8b21-cf2fb3917fc7","added_by":"auto","created_at":"2025-12-17 08:28:48","extension":"mp4","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":6660333,"visible":true,"origin":"","legend":"\u003cp\u003eCross section of core-shell- like particle\u003c/p\u003e","description":"","filename":"Supp.Video2.mp4","url":"https://assets-eu.researchsquare.com/files/rs-8273007/v1/f2213b428eb49724f3950294.mp4"},{"id":98439917,"identity":"b2f62c0c-b060-4567-a7ee-78a76ec72a2c","added_by":"auto","created_at":"2025-12-17 17:03:04","extension":"mp4","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":5484646,"visible":true,"origin":"","legend":"\u003cp\u003eCross section of non-core-shell- like particle\u003c/p\u003e","description":"","filename":"Supp.Video3.mp4","url":"https://assets-eu.researchsquare.com/files/rs-8273007/v1/0df14d5962e48cdf7aa70389.mp4"},{"id":98385229,"identity":"0cc1ac3f-6d94-400c-98e5-9452bf901bbf","added_by":"auto","created_at":"2025-12-17 08:28:48","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":14469242,"visible":true,"origin":"","legend":"Spplementary Information","description":"","filename":"Supp.InfoNatureFinal.docx","url":"https://assets-eu.researchsquare.com/files/rs-8273007/v1/1e171b9fd7eaebb4fb7d2684.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Bridging Particle-Scale Lithiation Mechanisms and Macroscopic Performance in High-Energy Density Si Anodes via Time-resolved Full 3D Visualisation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe electrification of transport is fundamental to the global effort to decarbonize energy systems and mitigate climate change. Lithium-ion batteries (LIBs) support this transition, not only powering electric vehicles, but also enabling grid-scale storage and facilitating the integration of intermittent renewable energy sources. Widespread adoption across sectors depends on overcoming key performance bottlenecks, particularly in energy density, charging speed and cycle life, while ensuring long-term economic and environmental sustainability \u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe success of LIBs arises from their high energy density, long cycle life and high efficiency. In automotive applications, industry targets exceed 250 Wh kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e energy density, \u0026gt;2C charge rates and \u0026gt;\u0026thinsp;1000 cycles \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. These demands have driven the development of high-performance cathode materials, particularly those based on nickel, manganese and cobalt (NMC), which enable higher capacity and voltage windows \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. However, the graphite anode, currently dominant in commercial LIBs, is limited by a theoretical capacity of ~\u0026thinsp;372 mAh g⁻\u0026sup1; \u003csup\u003e6\u003c/sup\u003e and suffers from limitations under high charging rates due to lithium plating \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. As a result, the anode becomes the limiting component and pairing it with high-capacity NMC cathodes cannot fully unlock the desired performance for next-generation applications.\u003c/p\u003e \u003cp\u003eTo address this mismatch, alloy-type anodes have emerged as promising alternatives \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. These materials react with lithium to form alloys, allowing much higher capacities than intercalation-based systems. Among them, silicon stands out due to its high theoretical specific capacity (~\u0026thinsp;4200 mAh g⁻\u0026sup1; for Li\u003csub\u003e22\u003c/sub\u003eSi\u003csub\u003e5\u003c/sub\u003e), low working potential, natural abundance and compatibility with existing manufacturing infrastructure \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In combination with NMC cathodes, silicon anodes offer a path towards high-energy-density LIBs \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. However, the key challenge remains the large volume changes silicon undergoes during (de)lithiation \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, leading to capacity fading and decreased cycle life \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Despite extensive engineering strategies to mitigate these effects \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, the widespread commercial implementation of ultra-high content silicon anodes remains challenging. Therefore, correlated investigations of the lithiation dynamics, stress evolution and degradation at both the electrode and particle-levels in cells pairing Si anodes with NMC cathodes is essential for progress.\u003c/p\u003e \u003cp\u003eIt is widely reported that lithiation of crystalline silicon proceeds via a two-phase core-shell mechanism \u003csup\u003e\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. A moving amorphization front converts crystalline Si (c-Si) into amorphous Li\u003csub\u003ex\u003c/sub\u003eSi, leading to radial expansion and internal stress accumulation. Much of this understanding stems from in situ transmission electron microscopy (TEM) studies on idealized systems that use statistically non-representative amounts of Si particles, neglect the electrode microstructure, including porosity and carbon binder domain (CBD), and are conducted under vacuum \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. While TEM enables high spatial resolution, it is inherently two-dimensional, requires invasive sample preparation, is restricted to a small field of view and is limited in its ability to capture interparticle interactions, matrix effects, or collective behaviour within intact electrodes. As such, these observations provide limited insight into real-world battery configurations \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRecently, in situ three-dimensional imaging techniques have gained momentum in battery research, offering new opportunities to bridge the gap between model systems and realistic architectures \u003csup\u003e\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. In this context, synchrotron-based X-ray computed tomography (nano-SXCT) enables three-dimensional imaging at the nanoscale from two-dimensional projections collected over a 360\u0026deg; rotation. Prior studies utilizing nano-SXCT have revealed macroscale phenomena in battery cells such as electrode swelling, crack formation and delamination during cycling \u003csup\u003e\u003cspan additionalcitationids=\"CR32 CR33 CR34 CR35 CR36\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. However, most in situ nano-SXCT experiments operate at voxel sizes above 0.2 \u0026micro;m \u003csup\u003e31,33\u0026ndash;38\u003c/sup\u003e, insufficient to resolve sub-micron features of individual silicon particles, typically 500 nm \u0026ndash; 5 \u0026micro;m in diameter, in embedded electrodes. Consequently, particle-scale phenomena, such as heterogeneous lithiation, stress localization and interparticle interactions, remain unresolved in three-dimensions, despite their central role in degradation cascades that affect entire electrodes. Moreover, many in situ imaging studies rely on half-cell configurations using lithium metal as a counter electrode, offering limited insight into high-energy full-cell setups incorporating NMC cathodes \u003csup\u003e\u003cspan additionalcitationids=\"CR36 CR37 CR38\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Yet, sub-micron, in situ 3D imaging of silicon particles embedded within an electrode microstructure, would allow direct tracking of critical early-stage microstructure degradation processes as well as local lithiation behaviour on different length scales that have so far remained hidden. A recent study combining operando optical microscopy and synchrotron X-ray computed tomography with digital volume correlation, revealed heterogeneous lithiation dynamics and strain evolution in graphite/\u0026micro;-Si composite electrodes at the electrode scale, highlighting that Si cycling stability critically depends on intraparticle nanoscale porosity, whereas mechanical degradation is driven largely by expansion of the carbon-binder domain (CBD) \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Yet, full correlative in situ chemo-mechanical studies on Si|NMC cells that track behaviour from the electrode scale down to individual particles at sub-micron resolution unravelling lithiation pathways, stress concentrator and fracture nucleation in 3D over time, remain scarce.\u003c/p\u003e \u003cp\u003eHerein, we apply in situ nano-SXCT to show the lithiation behaviour and mechanical response of an ultra-high 89 wt% Si content anode paired with a high-energy-density 811NMC cathode in three dimensions from electrode to particle level in a correlated manner. Our custom-designed electrochemical cell applies a controlled stack pressure to ensure electrical contact and mechanical relevance during cycling. This enables time-resolved 3D tracking of the electrode, Si particle\u0026acute;s adjacent microstructure as well as of the individual silicon particle dynamics with sufficient resolution and contrast beyond the state of the art. The possibility to capture 4D in situ data down to nanoscales in combination with semantic image segmentation and local digital volume correlation (DVC)-based analysis, allows the collection of high spatio-temporal resolved full-field displacement and strain maps. We analyse not only the lithiation behaviour of the electrode but rather enhance the perception of the chemo-mechanical process by studying diverse local lithiation behaviour, anisotropic strain evolution and mechanically distinct transformation modes from hundreds of particles distributed within the electrode to individual ones. Rather than a uniform core\u0026ndash;shell transformation, many particles develop internal, complex network-like lithiated pathways. The in-depth correlative multiscale tomographic analysis suggests that Si lithiation is thus intrinsically heterogeneous, governed by global as well as local features such as the particle size distribution, particle location within the electrode and surrounding microstructure, state of charge but also by processing-induced damage, electrode architecture and cell configuration, respectively. These observations point to factors to consider in silicon-anode development as defect screening, particle-size optimization and architecture engineering. Beyond, the multiscale correlative in situ nano-SXCT-based framework generalizes to different materials and cycling conditions, combining nanoscale resolution with mechanical analysis to support the rational design of next-generation electrodes.\u003c/p\u003e"},{"header":"Results and discussion","content":"\u003cp\u003e \u003cb\u003eIn situ measurement setup and electrochemical cell behaviour.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe build a cell setup, allowing in situ synchrotron X-ray computed nano-tomography acquisition to investigate electrochemically induced transformations of the electrode and Si particles during lithiation and delithiation with high resolution and contrast, see \u003cb\u003eFig.\u0026nbsp;1\u003c/b\u003e. The cell geometry is scaled down to fit the requirements of nanoscale tomography and to ensure the detection of sub-micron object sizes, while maintaining design and material elements of high energy density commercial relevant LIBs, see \u003cb\u003eFig.\u0026nbsp;1a\u003c/b\u003e. The measurements are performed at the ID16B beamline \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e of the European Synchrotron Radiation Facility (ESRF), Grenoble, France.\u003c/p\u003e \u003cp\u003eThe anode consists of a slurry-cast layer containing 89 wt% micron-sized crystalline silicon particles connected by polyacrylic acid (PAA)-based binder, carbon black and carbon nanotubes, calendared to a final thickness of ~\u0026thinsp;21 \u0026micro;m. Graphite is deliberately excluded from the anode to isolate the chemo-mechanical responses of silicon \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, which is often obscured in composite systems. The prepared Si-based anode is precisely stacked with a polypropylene separator and paired with an NMC811 cathode, forming a full-cell configuration essential for studying microstructural evolution in high-energy-density LIBs unlike most in situ studies that use lithium metal as reference electrode \u003csup\u003e\u003cspan additionalcitationids=\"CR36 CR37 CR38\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. To avoid fully exploiting the large Si capacity, the anode is operated under cathode-limited conditions (Methods).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 1b\u003c/b\u003e illustrates the structural and chemical composition of the pristine anode utilizing backscattered electron (BSE) field emission scanning electron microscopy (FESEM) imaging and energy-dispersive X-ray spectroscopy (EDS). The correlated images reveal the distribution of silicon particles embedded in the carbon-binder domain (CBD).\u003c/p\u003e \u003cp\u003eThe prepared anode|separator|cathode-stack, is integrated into the custom-designed in situ cell and mounted on the rotation stage at ID16B as shown in \u003cb\u003eFig.\u0026nbsp;1c\u003c/b\u003e. A key feature of the cell design is a spring-loaded upper contact which applies a constant compressive load of about 0.2\u0026ndash;0.4 MPa, replicating real‑world conditions \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Furthermore, the spring is able to accommodate changes in the electrode stack thickness during cycling, maintaining uniform interfacial contact and stable electrochemical performance throughout lithiation and delithiation. While some previous in situ X-ray studies have used defined-pressure systems to replicate realistic mechanical environments, these approaches have typically been limited to larger-scale setups and have not been adapted for X-ray nano-tomography at microscale dimensions \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Other studies, by contrast, relied on hand-assembled or loosely packed capillary cells without controlled pressure \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, often resulting in inconsistent compression and limited reproducibility. Details of cell assembly and electrochemical testing are provided in \u003cb\u003eMethods\u003c/b\u003e and \u003cb\u003eSupplementary Note 1\u0026ndash;3\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 1d\u003c/b\u003e shows a reconstructed nano-SXCT volume with a field of view of 102.4 x 102.4 x 102.4 \u0026micro;m\u0026sup3; and a voxel size of 50 nm. The dark top layer is the Cu current collector, the Si anode lies beneath and the bright layer corresponds to the separator. The dataset resolves particle-scale morphology suitable for quantitative analysis.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3D electrode and individual Si particle morphology evolution during Li insertion.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 2. Morphological evolution and phase-contrast-driven segmentation of non-lithiated silicon upon charging.\u003c/b\u003e (a) Representative nano-SXCT reconstructions of the anode from timesteps T0 (pristine) to T6 (cell: ~85% SOC). The Cu current collector lies above the orange dotted line, the porous separator is visible at the bottom of the anode. At the pristine state the Si particles and CBD\u0026thinsp;+\u0026thinsp;electrolyte are indicated by dark and light grey, respectively. Electrode expansion is traced by dashed red lines. ROI to study the evolution on particle level is indicated by a green dotted box. Representative particles are highlighted by red, green and blue. The scalebar refers to 5 \u0026micro;m. (b) ROI to track representative particles in red, green and blue, respectively, during charging using semantic segmentation. Scalebars refer to 3 \u0026micro;m. (c) Axial average anode thickness and relative non-lithiated (RNL) phase volume from Si particles distributed in the electrode from T0 to T6. (d) Cell voltage profile during a charge\u0026ndash;discharge cycle with tomography time points from T0 to T9. Charging is done at constant current C/3 to 4.3 V, then constant-voltage hold at 4.3 V. At T6 the cell reaches\u0026thinsp;~\u0026thinsp;85% SoC. T7 \u0026ndash; T9 are recorded during/after partial discharge at constant current C/5 to 2.5 V. Nano-SXCT cross-section of the blue particle at T0 and T6 with dashed lines in orange (e) and yellow (f) highlighting a path at T0 through the CBD\u0026thinsp;+\u0026thinsp;E and Si interface (pristine state) as well as a path within the Si particle core, respectively. See also the path at T6. Particle contour of T0 is indicated and overlaid as reference for timestep T6. (g,h) Corresponding greyscale profiles vs. pixels (px) at T0 (black) and T6 (red) along the orange (g) and yellow (h) dashed line indicated in (e,f). Background colours highlight the region of lithiated and non-lithiated Si phases. Vertical dashed line illustrates the shift of the dark grey regions interface from T0 to T6 in (g).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 2a\u003c/b\u003e illustrates the reconstructed nano-SXCT volumes of the electrode across different states of lithiation, from the uncycled or pristine state at T0, to the lithiated condition at T6 associated with an 85% state of charge (SoC). The developed cell design, introduced in \u003cb\u003eFig.\u0026nbsp;1\u003c/b\u003e, not only allows monitoring the evolving electrode morphology but also surpasses current studies \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, by enabling the correlative tracking of individual silicon particles during lithiation in three dimensions, see \u003cb\u003eFig.\u0026nbsp;2b\u003c/b\u003e. The effective spatial resolution of approximately 300 nm, see further details in \u003cb\u003eSupp. Figure\u0026nbsp;8\u003c/b\u003e, enables sub-micron feature resolution at the particle scale while preserving statistically relevant electrode-level context. The copper current collector remains unchanged throughout the experiment and serves as a reliable internal reference for further analysis.\u003c/p\u003e \u003cp\u003eThroughout lithiation the anode thickens in an approximately linear manner, as qualitatively observable in \u003cb\u003eFig.\u0026nbsp;2a\u003c/b\u003e and \u003cb\u003eSupp. Video 1\u003c/b\u003e and quantitatively confirmed in \u003cb\u003eFig.\u0026nbsp;2c\u003c/b\u003e. In detail, the mean electrode thickness increases from 20.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 \u0026micro;m at T0 to 25.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8 \u0026micro;m at T3 (50% SoC) and reaches 30.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1 \u0026micro;m at T6, corresponding to a cumulative average thickness increase of about 44%. A more detailed analysis shows an incremental increase of about 5 to 7% between T1 and T2, T3 and T4, as well as T4 and T5. Yet, a significant steeper incline is witnessed between T2 and T3 suggesting a transition triggered by the electrochemical evolution of the cell. Indeed, this amplified change in thickness can be associated with the onset of the 4.3 V constant-voltage step, see \u003cb\u003eFig.\u0026nbsp;2d\u003c/b\u003e. Further information regarding the voltage and current profile during charging discharging are provided in \u003cb\u003eMethods\u003c/b\u003e and \u003cb\u003eSupplementary Note 3\u003c/b\u003e. Despite the substantial overall expansion, no macroscopic cracking through the entire electrode thickness, as reported in previous studies \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, is observed at any point during lithiation.\u003c/p\u003e \u003cp\u003eFor the semantic segmentation of the individual particles distributed within the electrode, the detectability of the targeted material features in the reconstructed volume is essential. The detectability relies on phase-contrast imaging, which is sensitive to variations in the real part of the refractive index (δ) \u003csup\u003e46\u003c/sup\u003e. In the pristine state, crystalline silicon exhibits a strong phase contrast relative to the surrounding CBD soaked with the utilized electrolyte (E), yielding rather distinguishable particle boundaries. For quantitative 3D analysis, a convolutional neural network (CNN)-like model is utilized to segment the individual particles throughout the lithiation process, see \u003cb\u003eFig.\u0026nbsp;2b\u003c/b\u003e. Further details regarding the image analysis is provided in the \u003cb\u003eMethods section\u003c/b\u003e and \u003cb\u003eSupplementary Note 4\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eThe timeseries, illustrated in \u003cb\u003eFig.\u0026nbsp;2b\u003c/b\u003e, shows increasing inter-particle spacing, particularly along the axial direction, consistent with the bulk electrode swelling up to 44%. Unexpectedly, the relative non-lithiated (RNL) phase volume, obtained from the particle segmentation decreases. First, rather gradually up to timestep T2 and then more abruptly between T2 and T3, mirroring the trend of both the electrode-thickness evolution and the cell-voltage profile, see \u003cb\u003eFig.\u0026nbsp;2c\u003c/b\u003e and \u003cb\u003ed\u003c/b\u003e, respectively.\u003c/p\u003e \u003cp\u003eCross-sectional slices of a representative Si particle at timesteps T0 and T6 are shown in \u003cb\u003eFig.\u0026nbsp;2e\u003c/b\u003e and \u003cb\u003ef\u003c/b\u003e. The presented images highlight significant grey value changes from timestep T0 to T6, suggesting the formation of a lithiation induced network within the Si particle\u0026acute;s core but also the modification at its interface to the CBD and electrolyte (CBD\u0026thinsp;+\u0026thinsp;E). To study the latter the evaluated particle contour from T0 is overlaid as a reference on the T6 slice. The centre of mass of the particle is fixed allowing a direct comparison. The overlay reveals a locally dependent retreat of the Si particle\u0026rsquo;s outer interface at T6. Indeed, the definition of the particles interface during the lithiation is challenging. The corresponding greyscale line profile plot in \u003cb\u003eFig.\u0026nbsp;2g\u003c/b\u003e supports the observed interface shift. At T0, along the indicated orange dashed line, the c-Si|CBD\u0026thinsp;+\u0026thinsp;E interface, labelled with interface T0, is accentuated by a significant decrease of the grey value. Certainly, at T6, the decrease is shifted towards the particle core by about 8 px. This observed grey value behaviour in the profile for T0 and T6 marks the transition from non-lithiated to lithiated Si.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 2h\u003c/b\u003e illustrates greyscale profiles drawn entirely within the particle\u0026acute;s core, see yellow dashed line in \u003cb\u003eFig.\u0026nbsp;2f\u003c/b\u003e. For timestep T0 a flat profile over the entire considered range is depicted. This indicates a relatively homogeneous material phase with uniform phase contrast. By contrast for the same range at T6, the greyscale value significantly increases at a certain distance within the particle core and drops again after about 16 pixels. Lithiation alters the refractive index of Si \u003csup\u003e47\u003c/sup\u003e, making lithiated regions highly distinguishable within the Si-core. The collected tomographic data, based on the observed distinct grey value changes, enhances the perception regarding the lithiation of the Si particle core. Therefore, the deep learning-based segmentation rather targets the non-lithiated fraction of the silicon core, see \u003cb\u003eFig.\u0026nbsp;2c\u003c/b\u003e. Thus, the apparent particle shrinking in the segmented data, does not reflect a physical contraction. For instance, the blue-labelled particle from \u003cb\u003eFig.\u0026nbsp;2b\u003c/b\u003e, indicates a decrease in volume from 119 \u0026micro;m\u0026sup3; to 80 \u0026micro;m\u0026sup3; at T0 and T6, respectively, i.e. yields that 33 %of the Si core is lithiated at T6. Note, that this percentage does not include the lithiated zone at the particles outer interface. Further, small, heavily lithiated particles may lose contrast entirely and fall below the detection threshold, causing them to drop out of the segmented dataset.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCapturing the global deformation of the electrode.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e(a) Local digital volume correlation (local-DVC) grid on a representative anode sub-volume (40 x 40 x 40 \u0026micro;m\u0026sup3;) at T0. A node spacing (ns) of 35 voxels and a half window size (hws) of 35 voxels, give overlapping 70\u0026sup3;-voxel correlation windows (red cube). (b) DVC principle: a regular grid of correlation windows is tracked between a reference volume (Tn) and a deformed volume (Tn\u0026thinsp;+\u0026thinsp;1), yielding local displacement vectors at window centres (illustrated by a green arrow). From the displacement field, local strain tensors are computed. The schematic of a deforming Si particle illustrates this approach. (c) A nano-SXCT vertical cross-section (T0) indicating the divided current-collector side (orange) and separator side (blue). Right: Corresponding axial strain maps at T2, T4, T6 and T8 referenced to T0. Effective axial strain, is mapped from compressive (blue, \u0026minus;\u0026thinsp;100%) to tensile (red, +\u0026thinsp;150%). The scale bar corresponds to 10 \u0026micro;m. (d) Evolution of volumetric strain is shown for the current collector (orange) and separator (blue) side, as well as for the whole electrode (red), revealing spatial heterogeneity. (e) Extracted histograms indicate the local volumetric strain distributions in the upper and lower electrode regions at T2, T4, T6 and T8. Maxima are highlighted by arrows. A progressive broadening and skewing of the strain distributions, indicates increasing heterogeneity and asymmetry. (f) Temporal evolution of the axial strain components (XX, YY, ZZ) over the entire anode. Light grey and dark grey backgrounds indicate timepoints corresponding to lithiation and delithiation, respectively. Orange and blue lines represent the strain in the upper and lower regions, respectively.\u003c/p\u003e \u003cp\u003eWe quantify the chemo-mechanical response by applying a local digital volume correlation (local-DVC) based analysis\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e to the time-resolved synchrotron tomograms, extracting full-field displacements and strains. Specifically, this approach features a mechanical perspective of the underlying morphological changes, bridging the gap between visual observations, mechanical response and electrochemical behaviour. We register all timesteps to the pristine state of the electrode at timestep T0 using cubic correlation windows placed on a regular 3D grid. A 50% overlap between adjacent windows is used to resolve displacement gradients at the particle scale while maintaining robust convergence of the iterative correlation. Displacement vectors at window centres provide the local strain tensor. See the schematic in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003ea and \u003cb\u003eb\u003c/b\u003e for the grid and principle. Details with respect to the DVC model are presented in \u003cb\u003eMethods\u003c/b\u003e and \u003cb\u003eSupplementary Note 5\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003ec shows the evolution of axial strain maps for the vertical cross-sections from the electrode. The underlying dynamics is exemplary illustrated by timestep T2, T4, T6. It indicates that the deformation is dominated by expansion along the thickness in axial direction. The effective visualized axial strain ranges from compressive to tensile, illustrated in blue and red, respectively. First localized tensile zones appear at T2, establishing a separator-to-collector gradient in the very first lithiation step. These zones intensify and connect as lithiation proceeds significantly as indicated in timestep T4 and are peaking at T6 on the separator side. A partial relaxation during delithiation is observed at T8.\u003c/p\u003e \u003cp\u003eMore detailed strain analysis of the electrode is performed by mapping the temporal evolution of the extracted mean volumetric strain across the full anode as well as lower and upper electrode parts, associated with the separator and current collector side, respectively, see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003ed. The mean volumetric strain of the full electrode increases by about 6% upon initial lithiation at T1 and then progressively builds-up throughout the constant current and constant voltage charging, reaching roughly 44% at T6. The measured electrode expansion, see also the analysis in \u003cb\u003eFig.\u0026nbsp;2a\u003c/b\u003e, is consistent with previous reports \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. All these values remain well below the often-cited theoretical volumetric expansion of ~\u0026thinsp;300% for fully lithiated pure Si \u003csup\u003e11,17,50\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn full-cell configurations, actual expansion is significantly constrained by factors such as limited lithiation depth, anode to cathode balance, mechanical confinement, porosity and the influence of surrounding matrix materials. This discrepancy highlights the limitations of earlier studies, which often employed idealized systems that neglect electrode-scale mechanical particle interactions. Therefore, a critical perspective is required when interpreting both theoretical expansion values and data derived from simplified experimental setups.\u003c/p\u003e \u003cp\u003eDuring lithium extraction from T6 to T8, the electrode exhibits partial strain recovery, but a residual volumetric strain of ~\u0026thinsp;32% persists, see dark shaded area in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003ed. The presence of an irreversible strain component suggests underlying permanent microstructural changes, such as solid electrolyte interphase (SEI) growth or plastic deformation \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIndeed, a deeper understanding regarding the asymmetry of the strain distribution in the electrode is gained by analysing the upper region adjacent to the current collector and lower region near the separator of the electrode, separately. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003ed, strain differences are small at early stages of lithiation, see timestep T2, but diverge with state of charge. By T6 the separator-side region averages about 50% volumetric strain, while the current-collector side averages about 34%.\u003c/p\u003e \u003cp\u003eFurther, we quantify the emergence of strain heterogeneity by plotting the histograms of volumetric strain for the two regions at T2, T4, T6, and T8, see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003ee. At timestep T2 both distributions are narrow and centred likewise, consistent with a uniform expansion. However, as lithiation progresses, the distributions broaden significantly, reflecting increased spatial heterogeneity. By T6 the separator-side distribution at the bottom of the electrode shows strain values exceeding 100% in some areas, while the current-collector side at the top includes areas with compressive strains down to \u0026minus;\u0026thinsp;50%.\u003c/p\u003e \u003cp\u003eIn Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003ef the temporal evolution of the mean axial strain components XX, YY and ZZ over the entire anode is further studied to understand the dominant mechanical loading direction. The results strengthen the finding that the deformation is predominantly uniaxial, with expansion primarily along the electrode thickness in z- direction. The in-plane strain components ε\u003csub\u003exx\u003c/sub\u003e and ε\u003csub\u003eyy\u003c/sub\u003e remain below 3% throughout, while the axial expansion ε\u003csub\u003ezz\u003c/sub\u003e accounts for nearly all volumetric change. This observation aligns with the macroscopic electrode swelling shown in \u003cb\u003eFig.\u0026nbsp;2a\u003c/b\u003e and reflects the inherent mechanical anisotropy of the cell, governed by stack pressure and boundary conditions. It also is in accordance with the particle movement illustrated in \u003cb\u003eFig.\u0026nbsp;2b\u003c/b\u003e. The independent particle tracking based on segmentation, see details in \u003cb\u003eSupp. Figure\u0026nbsp;9\u003c/b\u003e, supports further the presented strain analysis. While lateral particle displacements in the xy-plane are minimal, axial displacements vary markedly with position within the electrode. Particles near the current collector shift by ~\u0026thinsp;2 \u0026micro;m, while those near the separator move up to ~\u0026thinsp;11 \u0026micro;m, corresponding to local swelling of nearly 60%.\u003c/p\u003e \u003cp\u003eThe observed axial strain gradient, reflects boundary and transport conditions. Mechanical constraints are imposed by the rigid current collector, which restricts expansion at the top and favours deformation toward the less confined separator side, whereas lithium ions access the electrode from the separator side via electrolyte-filled pores. The revealed strain asymmetry observed in the electrode suggests a preferential lithiation, SEI formation and strain accumulation near the separator interface \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThree-dimensional strain evolution in the particle vicinity during Li insertion and extraction.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e(c) Orthogonal views of volumetric strain at T6 relative to T0, overlaid on the T0 microstructure. Slices are extracted along the planes indicated in the 3D renderings (blue, XZ; yellow, XY; red, YZ). Contours mark equal-strain levels. Four equally spaced slices are depicted along each orientation to visualize in-plane variations. The strain colormap spans compressive \u0026minus;\u0026thinsp;50% (blue) to tensile\u0026thinsp;+\u0026thinsp;50% (red). Small and large Si particles, indicated by sp-Si and lp-Si are shown in light grey, CBD/Pores in dark grey. Scale bars, 5 \u0026micro;m. (d) Temporal evolution of volumetric strain for four additional particle-centred volumes of interest.\u003c/p\u003e \u003cp\u003eThe local mechanics is further analysed in three dimensions around individual particles distributed in the electrode upon charging and discharging, to uncover the chemo-mechanical process on particle level. As depicted in \u003cb\u003eSupp. Figure\u0026nbsp;10\u003c/b\u003e, the lithiated anode exhibits modest local thickness variations across the field of view, indicating non-uniform lithiation kinetics and local stress concentration sites within the electrode. To trace the evolution of the particle vicinity in three-dimensions, we isolate 15 x 15 x 15 \u0026micro;m\u0026sup3; sub-volumes centred on an exemplary silicon particle located in the electrode under investigation, see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e4\u003c/span\u003ea. All timesteps are spatially aligned based on the centre of mass of this central particle at each respective timestep. The approach fixes a particle-centric reference frame that removes global rigid body motion and electrode-scale expansion from the local analysis. Subsequently, volumetric strain fields are computed between successive timesteps from T0\u0026loz;T2, T2\u0026loz;T4, T4\u0026loz;T6 and T6\u0026loz;T8, see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e4\u003c/span\u003eb. In this frame, the central particle exhibits near-zero apparent strain by design, while surrounding windows capture the relative deformation of the neighbouring microstructure, described by other particles, CBD and pore network. The evaluated successive three-dimensional strain maps show progressive inhomogeneous accumulation of tensile strain in the neighbourhood of the centred Si particle during lithiation, reaching a maximum at timestep T6. Displacement vectors indicate expansion toward locally compliant pores in the vicinity of the particle. After partial delithiation at T8, strain magnitudes decrease relative to T6 and return to levels between those observed at T4 and T5, which exhibit a similar SOC. This trend is consistent with alloy driven expansion of Si and partial reversibility upon Li extraction which generates mechanical stress in confined architectures \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Additionally, solid electrolyte interphase growth may also contribute to the observed deformation \u003csup\u003e\u003cspan additionalcitationids=\"CR56 CR57\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eNext the impact of the surrounding microstructure on the particle-resolved strain distribution in different planes, is assessed in more detail. Hence, orthogonal slices through the three-dimensional microstructure at timestep T6 relative to T0 are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e4\u003c/span\u003ec. The volumetric strain distribution projected on the microstructure reveals for different planes that regions containing many smaller sized particles (sp-Si), embedded in CBD, exhibit elevated strain, whereas narrow gaps confined between closely packed large particles (lp-Si) show comparatively low strain. Further, high local porosity near particles accommodates expansion by pore collapse and thereby helps to relieve strain. Hence, an inhomogeneous strain field in the vicinity of the particle conditioned by the microstructure results, also suggesting significant impact on the lithiation at the particle\u0026acute;s interface, see \u003cb\u003eFig.\u0026nbsp;2e and f\u003c/b\u003e. Post-mortem FESEM cross-sections on electrode level, see \u003cb\u003eSupp. Figure\u0026nbsp;11\u003c/b\u003e, support these observations, revealing microstructural precursors for strain localization such as binder-rich zones, porosity variations and a highly inhomogeneous Si particle size distribution. Regions dominated by large Si particles show only minor irreversible thickness increase, whereas areas rich in sub-micron particles exhibit greater residual thickening, consistent with enhanced SEI formation driven by their higher surface area \u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e,\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Thus, the resulting depicted three-dimensional inhomogeneous strain in the particle vicinity affects the chemical reaction and further deepens the understanding of the underlying chemo-mechanical process. This observation is in line to prior findings \u003csup\u003e\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e which have identified SEI constituents such as fluorine-rich layers and carbonate-based species, as well as residual Li\u003csub\u003ex\u003c/sub\u003eSi phases that resist full delithiation, as contributing factors to irreversible expansion.\u003c/p\u003e \u003cp\u003ePronounced strain heterogeneity within the electrode, becomes even more evident when analysing multiple particle-centred volumes of interest (VOI), see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e4\u003c/span\u003ed. The analysis provides important information concerning the initial chemo-mechanical process, which is indeed highly relevant for observations made at longer cycling \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. It reveals that location-dependent strain heterogeneity emerges already at the first cycle of the cell within the anode microstructure. Between T1 and T2 the mean volumetric strain increases similarly across VOIs, but the strain evolution diverges strongly as lithiation progresses, consistent with the trends in \u003cb\u003eFig.\u0026nbsp;2\u003c/b\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e. At T6, some VOIs exhibit modest average volumetric strain of about 25%, whereas others reach 60% (e.g., subvolume 4 and 3, respectively), with local peaks larger than 150% at inter-particle contacts and within constricted pore regions. See also \u003cb\u003eSupp. Figure\u0026nbsp;12\u003c/b\u003e for further detail.\u003c/p\u003e \u003cp\u003eIn addition, local heterogeneities can be also triggered by possible transient gas evolution, as shown in tomographic series, see \u003cb\u003eSupp. Figure\u0026nbsp;13\u003c/b\u003e. Here exemplary a void as a local perturbation appearing between timestep T1 and T2 and disappearing again between T4 to T5, is illustrated. The temporary emergence suggests gas generation, likely from electrolyte decomposition or reactions of absorbed water \u003csup\u003e\u003cspan additionalcitationids=\"CR65\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. As indicated by the volumetric strain analysis, such gas bubbles can both concentrate and relieve stress locally, disrupt particle networks and drive mechanical inhomogeneities.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDivergent particle-level responses revealed by residual analysis\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 5: Divergent particle-level responses to lithium insertion and extraction.\u003c/b\u003e (a-b) Time series for residual maps for a representative (a) core\u0026ndash;shell-like and (b) non-core\u0026ndash;shell-like (de)lithiation response. States T1, T2, T3, T4, T5, T6 and partially delithiated T8 illustrate the growth of residual features during lithiation and their partial regression upon lithium extraction within the Si particle. Higher residual intensity, in red and blue for core-shell (cs)- and non-cs-like, respectively, indicates regions with higher grey value changes upon (de)lithiation. For improved visibility of the cs-like residual structure, the particle contour is overlaid on the cs-like particle at T6. (c) Orthogonal tomographic slices in different planes exemplary at T3 and T6 of the cs-like particle shown in (a), with residual overlay (red contour). (d) Orthogonal slices at T3 and T6 for the non-cs particle shown in (b) with residual overlay (blue contour). Complex internal network emerges within an initially intact particle and intensify by T6 upon lithiation. Some features diminish after delithiation, consistent with a network-mediated transformation rather than a single advancing front. (e) Post-mortem FESEM of the cell with elemental EDS maps in the delithiated state (after T8) corroborates in situ observations. The anode cross-section exhibits pronounced thickness variations. Magnified regions (red and blue box) show network-like interiors in some particles with weak F and C signals, alongside particles displaying mechanical cracks.\u003c/p\u003e \u003cp\u003eThe key challenge is to study spatially the mechanical response of individual silicon particles during lithium insertion and extraction. Macroscopic deformation patterns arise from particle-scale dynamics and, in turn, bias those dynamics through changing contact networks and local confinement. To further resolve the underlying structural transformations, we compute DVC residual fields between two representative states extracted from the underlying electrode. The DVC-measured deformation is applied to the initial volume, geometrically matching it to the later configuration, e.g. the T0-deformed-to-T6 timestep. By subtracting the deformed volume of the initial state from the later dataset, we isolate residuals within the particle that reflect local material changes beyond mere positional shifts, and allow to draw conclusion about the underlying particle lithiation behaviour, see \u003cb\u003eMethods\u003c/b\u003e for further details.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 5a\u003c/b\u003e and \u003cb\u003eb\u003c/b\u003e contrast two distinct particle responses in 3D from timestep T1 to T6 and at T8, upon (de)lithiation. The exemplar core\u0026ndash;shell(cs)-like particle in \u003cb\u003eFig.\u0026nbsp;5a\u003c/b\u003e show faint, surface-limited residuals at T3 that evolve into a more continuous shell by timestep T6, while the core remains largely unchanged, consistent with a surface-limited lithiation front and minimal internal restructuring at the accessible spatial resolution. The Si particle core appears morphologically stable, with no visible cracks or internal microstructural transformations, see in particular timestep T6 where the particle is visualized together with the emerging residuals. Here, surface localized residuals and subtle grey-value shifts indicate limited lithiation-induced changes at the particle\u0026acute;s periphery.\u003c/p\u003e \u003cp\u003eIn contrast, the non-cs particle in \u003cb\u003eFig.\u0026nbsp;5b\u003c/b\u003e already exhibits residual pathways that traverse the particle in all three directions at timestep T3. By T6 these pathways broaden, new branches appear and features brighten, indicating increasing local transformation and a complex distributed, 3D network-type lithiation. After partial delithiation at T8 several pathways fade or retract, indicating partial reversibility. The onset and amplification of these changes are consistent with the macroscopic electrode response described above as well as follow the voltage characteristic, see in particular Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cb\u003eFig.\u0026nbsp;2d\u003c/b\u003e. Orthogonal tomographic slices extracted at timesteps T3 and T6 along the planes indicated in \u003cb\u003eFig.\u0026nbsp;5a,b\u003c/b\u003e (T3) further resolve these structural characteristics and their evolution for the cs- and non-cs particles in more detail, see \u003cb\u003eFig.\u0026nbsp;5c,d\u003c/b\u003e and \u003cb\u003eSupp. Video 2\u003c/b\u003e and \u003cb\u003e3\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSupplementary Fig.\u0026nbsp;14\u003c/b\u003e shows an additional example of such emerging network structures upon partial lithium extraction within the particle. The study includes cases where the network contrast nearly disappears. Together, these observations indicate that cs-like particles remain predominantly surface-limited over T0\u0026ndash;T8, whereas non-cs particles undergo internal, network-mediated transformation. These branched lithiated domains within the particles observed here in 3D in the first electrochemical cycle, ultimately extend prior 2D post-mortem observations made by H\u0026auml;usler et al.\u003csup\u003e18\u003c/sup\u003e regarding the underlying initialization of local microstructural and strain modifications, which in turn impact the electrochemical performance of the Si-based cell after long cycling.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSupplementary Fig.\u0026nbsp;15\u003c/b\u003e also indicate particles already fractured before initial charging. Correlative analysis between particle and electrode-level reveals that such pre-cracked particles are predominantly located near the electrode surface. Indeed, processing-induced damage during steps such as calendaring might explain the performed observation.\u003c/p\u003e \u003cp\u003eThe presented post-mortem FESEM imaging of the delithiated electrode after one cycle in \u003cb\u003eFig.\u0026nbsp;5e\u003c/b\u003e corroborates the in situ-based nano-SXCT analysis. A couple of particles display faint, network-like domains. EDS analysis of these regions within the Si particle reveal neither fluorine presence nor silicon loss, arguing against SEC infiltration or the onset of dendrite formation \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Furthermore, it excludes fracture as the origin, since it affiliates to a different behaviour than observed for the crack, see \u003cb\u003eFig.\u0026nbsp;5e\u003c/b\u003e. \u003cb\u003eSupp. Figure\u0026nbsp;16\u003c/b\u003e, further indicates that these networks expand with cycling.\u003c/p\u003e \u003cp\u003eThe presented approach allows correlative 3D investigations over different length scales, from cell to single particle-level. Results indicate that the classical and common core-shell mechanism represents only one of several lithiation possibilities and strongly depend on the chemo-mechanical response. The latter is modulated by local particle-specific factors such as defect state, local microstructural environment and lithiation kinetics. Within the scanned volume, illustrated in \u003cb\u003eSupp. Figure\u0026nbsp;17\u003c/b\u003e, about 10% of the particles follow a cs-like response in the first lithiation insertion. Most common behaviour involves rather the lithiation along complex networks within the particle. The in-depth correlative multiscale tomographic analysis suggests that Si lithiation is thus intrinsically heterogeneous, governed by global as well as local features like the particle size distribution, particle location within the electrode and surrounding microstructure, state of charge but also by processing-induced damage, electrode architecture and cell configuration, respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis work provides enhanced insights on the chemo-mechanical process linking electrode-scale deformation to particle-scale mechanics for cells with high silicon (Si) content and paired with nickel-manganese-cobalt (NMC) cathodes, by combining correlative multiscale 3D in situ characterization. The combination of a pressure-controlled in situ cell design with high-resolution synchrotron X-ray nano-tomography, AI-driven segmentation and 4D strain mapping enables the detection of pronounced spatial deformation and strain heterogeneities from the electrode scale down to individual Si particles.\u003c/p\u003e \u003cp\u003eThe observed strain heterogeneity on different length scales has direct implications for industrial electrode design. Micron-sized silicon particles, including those sourced from industrial cutting waste, offer a scalable and cost-effective alternative to engineered nanostructures \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e or sophisticated coated architectures \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, but their successful deployment hinges on mitigating mechanically driven degradation. Our findings highlight several design levers for optimizing not only micron-sized Si but also nano-porous and other advanced Si architectures.\u003c/p\u003e \u003cp\u003eFirst, at the particle level, most particles do not follow a simple core\u0026ndash;shell pathway. Instead, internal complex network-like transformation routes emerge within the particle and partly regress on delithiation. Minimizing fabrication-induced defects is paramount since defects act as stress concentrators and fracture nucleation sites. Implementing quality control protocols to detect and screen out cracked particles prior to integration could significantly improve cycling stability. Surface engineering to guide SEI formation and regulate lithium flux \u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e could influence how and where lithiation begins, potentially steering the transformation pathway away from high-strain configurations.\u003c/p\u003e \u003cp\u003eSecond, the particle adjacent microstructure in context to pores, particle size and distribution influence both the extent and reversibility of lithiation-induced strain since larger particles show a different lithiation behaviour than smaller ones. A tighter size distribution could promote a more uniform mechanical response across the electrode, thereby reducing local stress heterogeneities.\u003c/p\u003e \u003cp\u003eThird, our results highlight that mechanical failure is often dictated not by total expansion but by localized strain accumulation at both particle and electrode scales. The presented correlative multiscale framework provides a basis for engineering electrode architectures that moderate lithiation gradients and redistribute stress more evenly. Likewise, adjusting charging protocols, such as employing adaptive current profiles \u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e,\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e, may reduce the severity of transient strain during fast charging and extend electrode lifetime.\u003c/p\u003e \u003cp\u003eUltimately, these results indicate that failure risk is controlled by strain localization and microstructural context, rather than bulk expansion alone. A correlative multiscale 3D view of the underlying chemo-mechanical processes is therefore essential for rational design. Practical levers include reducing fabrication-induced defects, tightening particle-size distributions, and designing architectures that moderate local strain gradients. By integrating advanced quantitative multiscale imaging, AI-based morphological analysis and mechanically realistic operating conditions, this study provides not only deeper understanding but also a diagnostic and design framework for durable, high-capacity Si anodes. The approach is broadly applicable beyond liquid-electrolyte Li-ion systems, including solid-state batteries employing Si-based anodes.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eMaterial preparation\u003c/h2\u003e \u003cp\u003eThe silicon-based anode was composed of 89 wt% micron-sized silicon particles (median size: 3\u0026ndash;7 \u0026micro;m; CLM 00001 / Wacker Chemie AG), 9 wt% polyacrylic acid (PAA)-based binder (AQUACHARGE (water solution) / SUMITOMO SEIKA), 1.8 wt% carbon black (Super C65 / IMERYS) and 0.2 wt% single-walled carbon nanotubes (Tuball BATT H2O / OCSIAL). The electrode slurry was cast onto a copper foil and subsequently calendared, yielding electrodes with an areal loading of 3 mg cm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e and a theoretical areal capacity of approximately 11 mAh cm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e. However, to avoid fully utilizing the anode\u0026rsquo;s capacity, its effective capacity was limited to ~\u0026thinsp;3.5 mAh cm⁻\u0026sup2; by pairing it with a cathode of matching capacity. As the cathode, a nickel\u0026ndash;manganese\u0026ndash;cobalt-oxide (NMC811, 3.5 mAh/cm2), consisting of 96.5 wt% NMC811, 1.5 wt% PVDF-based binder and 1 wt% carbon black, was employed. Circular electrodes with a diameter of 1.100\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001 mm were precisely cut utilising a 3D Micromac microPREP PRO femtosecond laser with a laser power of 35 mW to ensure reproducible geometry (see \u003cb\u003eSupplementary Note 1\u003c/b\u003e for further details).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCell assembly\u003c/h3\u003e\n\u003cp\u003eThe prepared electrode discs (1.100\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001 mm) were precisely assembled into a custom-designed in situ electrochemical cell, based on the setup described here \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. A non-woven polypropylene separator (1.5 mm diameter), soaked in 0.5 \u0026micro;L electrolyte composed of 1 M lithium hexafluorophosphate (LiPF₆) in fluoroethylene carbonate (FEC) and diethyl carbonate (DEC) (2:8 v/v) with 2 wt% vinylene carbonate (VC), was placed between the electrodes. The cell housing was constructed from perfluoroalkoxy alkane (PFA) tubing (inner diameter 1.6 mm, outer diameter 3.2 mm), which is compatible with synchrotron imaging chosen for its low X-ray attenuation, chemical resistance and mechanical robustness.\u003c/p\u003e \u003cp\u003eThreaded stainless steel mounts were screwed into both ends of the tubing to create a sealed enclosure. A central feature of the cell design is the ability to apply a precisely adjustable and fixed mechanical pressure to the electrode stack via a spring-loaded contact inserted through the upper steel mount. For the 1.1 mm diameter cell used in this study, the applied pressure could be tuned across a wide range - from 0.01 to 1.5 MPa. During experiments, the spring was fixed to apply a constant pressure of 0.2\u0026ndash;0.4 MPa. This adjustability is essential for optimizing and standardizing contact between cell components while minimizing mechanical deformation of the active material. A stable and defined pressure ensures consistent electrochemical performance, reproducibility between cells and preserves the integrity of microstructural evolution during in situ imaging. To maintain an inert environment and prevent air ingress, all interfaces between the steel mounts, polymer housing and spring contact were sealed with lacquer. The entire cell assembly was performed inside an argon-filled glovebox.\u003c/p\u003e \u003cp\u003eThe complete cell setup was further mounted on a polyetheretherketone (PEEK) cylindrical-shaped support to ensure mechanical stability and chemical compatibility during cycling and imaging on the sample rotation stage at ID16B. Finally, the electrodes are electrically connected to a potentiostat \u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. For the lower mount, see \u003cb\u003eFig.\u0026nbsp;1c\u003c/b\u003e, a banana plug was utilized. At the upper terminal, a copper wire was wrapped tightly around the spring contact and was further secured with parafilm. Soldering was avoided to prevent any heat-induced damage. The flexibility of the yet secure electrical setup enables sample rotation about the z-axis for uninterrupted in situ monitoring without compromising electrochemical or mechanical cell integrity. Additional assembly details are provided in \u003cb\u003eSupplementary Note 2\u003c/b\u003e. Despite employing several measures to ensure high-quality electrode fabrication and assembly, such as femtosecond laser cutting to ensure flat, uniform edges and a parallel layer stack, the high mass and electron density of Cu introduce X-ray scattering artefacts in the phase images, resulting in localized image degradation and blurring near the current collector in the resulting 3D volumes. Consequently, these blurred regions are excluded from strain analysis.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eElectrochemical charging and discharging protocol\u003c/h2\u003e \u003cp\u003eElectrochemical cycling was performed in situ using an OrigaFlex OGF500 potentiostat during synchrotron X-ray computed nano-tomography (nano-SXCT) acquisition using a custom script-controlled protocol. The cell was first charged using a two-step constant current\u0026ndash;constant voltage (CC\u0026ndash;CV) strategy. In the constant current (CC) phase, the cell was charged at a rate of C/3 until either a voltage of 4.3 V was reached or a maximum time of 30 minutes elapsed. If the voltage limit was reached before timeout, the protocol transitioned into the constant voltage phase. Otherwise, a tomographic scan was triggered. In the subsequent constant voltage (CV) phase, the voltage was held at 4.3 V. Again, if either the current dropped below a predefined threshold (C/10) or 30 minutes had passed, a scan was initiated and the loop continued. The charging sequence continued until either a defined number of scans (n\u0026thinsp;=\u0026thinsp;6) had been reached or the current had sufficiently stabilized.\u003c/p\u003e \u003cp\u003eFollowing the final charging scan, the cell was discharged under constant current conditions at a rate of C/6 until the lower voltage cut-off of 2.5 V was reached. To determine noise induced from the SXCT scan, two final scans without additional discharge at timestep T8 and T9 were acquired without intervening electrochemical activity, see \u003cb\u003eSupp. Figure\u0026nbsp;18\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eTo minimize artefacts arising from mechanical or thermal relaxation during tomography, the cell was temporarily switched to open-circuit voltage (OCV) one minute prior to each scan. Once acquisition was complete, electrochemical cycling resumed automatically. Further experimental details and a detailed flowchart of the control logic, including all decision pathways and fail-safes, are provided in the \u003cb\u003eSupplementary Note 3\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eCell SoC values reported in the main text refer to full-cell SoC. By design this corresponds to ~\u0026thinsp;1/3 anode capacity utilisation (\u003cb\u003eMethods: Material preparation\u003c/b\u003e), owing to cathode-limited cycling.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIn situ X-ray nano-tomography measurement\u003c/h3\u003e\n\u003cp\u003eIn situ X-ray nano-tomography was performed at the beamline ID16B \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e of the European Synchrotron Radiation Facility (ESRF) in Grenoble, France, using holo-tomography \u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. The imaging was conducted with a monochromatic, conical X-ray beam at an energy of 29.6 keV and a flux of ~\u0026thinsp;10\u0026sup1;\u0026sup2; photons per second. Phase-contrast information was acquired by collecting radiographs at four different propagation distances, enabling accurate phase retrieval. Each tomographic dataset comprised 2505 projections acquired over a 360\u0026deg; sample rotation around the axial direction (z-direction), with an exposure time of 20 ms per projection. In addition, 20 flat-field and 21 dark-field images were recorded per scan. Data were collected using a PCO Edge 4.2 CMOS camera (2048 x 2048 pixels) coupled with a 30 \u0026micro;m thick LSO scintillator. The total acquisition time per holo-tomography scan was approximately 10 minutes. The voxel size for in situ scans was 50 x 50 x 50 nm\u0026sup3;.\u003c/p\u003e\n\u003ch3\u003eData reconstruction and processing\u003c/h3\u003e\n\u003cp\u003eThe 3D reconstruction was performed with the open-source software PyNX \u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e through a two-step approach. Firstly, an iterative phase retrieval step was applied using as an initial guess a Paganin-like approach with a complex refraction index ratio δ/β\u0026thinsp;=\u0026thinsp;170. Subsequently, a filtered back-projection reconstruction was performed using the ESRF software Nabu\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. Ring artefact reduction was applied post-reconstruction using an in-house developed correction algorithm. The final reconstructed volumes measured 102.4 x 102.4 x 102.4 \u0026micro;m\u0026sup3; with a voxel size of 50 x 50 x 50 nm\u0026sup3; and were saved in 16-bit unsigned integer format. To enhance image contrast and improve visualization, histogram equalization was applied in a final post-processing step.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMachine-learning image segmentation\u003c/h2\u003e \u003cp\u003eTo segment different material phases in the reconstructed tomography volumes, a deep learning-based approach was applied using an attention residual U-Net architecture \u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e implemented with the Python Keras library. Two separate models were trained to account for structural changes over time: Model 1 for early timesteps (T0\u0026ndash;T2) and Model 2 for later stages (T3\u0026ndash;T8). Initial labels were generated using Ilastik \u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e and 12 annotated slice images per model (before augmentation) were selected for training. Image sizes were 256 x 512 px, with Model 1 using 4 slices per timestep and Model 2 using 2 slices per timestep. Data augmentation was performed to expand the dataset threefold. Both models were trained for 150 epochs on an NVIDIA RTX A5000 GPU. Additional details are provided in \u003cb\u003eSupplementary Information\u003c/b\u003e. The final 3D visualization of the segmented data was accomplished using Dragonfly 3D World, Version 2024.1\u003csup\u003e76\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCalculation of spatial resolution\u003c/h2\u003e \u003cp\u003eSpatial resolution was estimated by analysing greyscale intensity transitions at particle interfaces. This involved manually selecting particle edges and extracting orthogonal line profiles across them. At these interfaces, the greyscale intensity exhibits characteristic changes due to phase contrast. The resolution was quantified as the full width at half maximum (FWHM) of the derivative of the greyscale profile, which was approximated by a quadratic function, following a similar approach as described in H\u0026auml;usler et al. \u003csup\u003e70\u003c/sup\u003e. A representative line profile is provided in \u003cb\u003eSupp. Figure\u0026nbsp;8\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStrain analysis\u003c/h2\u003e \u003cp\u003eQuantitative 3D strain analysis was performed using the open-source Software for Practical Analysis of Materials (SPAM) \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, which implements a digital volume correlation (DVC) based framework to measure 3D displacement and strain fields from a pair of X-ray tomography images. The analysis workflow began with two global registration steps: an initial \u0026ldquo;eye registration\u0026rdquo; for coarse manual alignment, followed by an automatic \u0026ldquo;non-rigid registration\u0026rdquo; step that estimates a single linear and homogeneous deformation function (Φ) mapping the reference image volume 1 into image 2 accounting for affine transformations: translations, rotations, normal and shear strain. The correlation procedure is based on a gradient-based iterative algorithm that minimizes the difference between the two images, progressively correcting the latter by a trial deformation function. Convergence is evaluated when a stable solution is reached, based on δΦ of the deformation function increment between two successive iterations. Local strain measurements were computed using SPAM\u0026rsquo;s Local Digital Image Correlation (LDIC) module. This approach subdivides the image volume into a regular 3D grid of points and performs independent non-rigid correlations within local sub-volumes (correlation windows) centred on each point. Material deformations were tracked solving the above iterative algorithm for each sub-volume across successive timepoints. A pyramidal refinement approach was employed to improve correlation resolution, progressively reducing the node spacing (ns) from 100 to 70 and finally to 35 pixels. The half-window size (hws) was set equal to the node spacing at each refinement step, ensuring 50% overlap between adjacent correlation windows. A final window size of 3.5x3.5x3.5 \u0026micro;m\u0026sup3; (70\u0026sup3; voxels) was selected as optimal, balancing spatial resolution and convergence robustness. Displacement noise in the measured Φ-fields was filtered by replacing non-converged nodes with values interpolated from their neighbouring eight nodes before further processing. This filtering process helps to decrease the errors within the convergence loop. To quantify cumulative deformation over multiple timesteps, sequential deformation fields (e.g., T0\u0026rarr;T1, T1\u0026rarr;T2, T2\u0026rarr;T3) were combined to construct cumulative mappings (such as T0\u0026rarr;T3) based on a multiplicative composition of the incremental local deformation functions. Total strain tensor components were then derived from the spatial gradients of these accumulative displacement fields using SPAM\u0026rsquo;s strain field calculation routine, which operates on the regularly gridded displacement data. See also \u003cb\u003eSupplementary Note 5.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe strain mapping approach was applied at two spatial scales to capture both localized deformation around individual particles and global strain gradients across the electrode:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eLocal strain analysis (particle-centred frame): To investigate local strain behaviour in the immediate vicinity of individual particles, cubic sub-volumes of 15x15x15 \u0026micro;m\u0026sup3; or 15x15x10 \u0026micro;m\u0026sup3; were extracted, each centred on a selected silicon particle. For each timestep, the particle\u0026rsquo;s centre of mass was calculated and the sub-volume was cropped accordingly to establish a fixed local reference frame. This approach effectively removes global electrode displacements, isolating the relative deformation within each particle\u0026rsquo;s neighbourhood.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eElectrode-scale strain mapping (electrode-centred frame): For electrode-scale analysis, the full imaged volume of 102.4x102.4x102.4 \u0026micro;m\u0026sup3; was subdivided into larger 40x40x40 \u0026micro;m\u0026sup3; regions (see \u003cb\u003eSupp. Figure\u0026nbsp;19\u003c/b\u003e), enabling spatially resolved strain mapping across the entire electrode thickness.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eResidual mapping of local structural deviations based on DVC analysis\u003c/h2\u003e \u003cp\u003eTo visualize local structural deviations, residual maps were generated based on the accumulative multiplicative deformation fields (Φ). For each subsequent timepoint (T1 through T8), Φ-fields were computed relative to the reference state T0. These Φ-fields were then used to deform the reference image, generating predicted synthetically deformed volumes for each timepoint (e.g., T0-deformed-to-T6). Residual images were obtained by subtracting the deformed reference image (T0-deformed-to-T6) from the corresponding original image at that timepoint (T6). Subtraction was performed in ImageJ (Fiji)\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e, followed by a Gaussian blur (σ\u0026thinsp;=\u0026thinsp;2) to suppress high-frequency noise and an (abs)-function to normalise the residual values. Finally, based on the double-scan error intensities, a level of 5000 residual values was considered as measurement noise and removed from the fields, isolating high residual features indicating non-linear structural transformation, as shown in \u003cb\u003eSupp. Figure\u0026nbsp;18\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFESEM analysis\u003c/h2\u003e \u003cp\u003eCross-sectional preparation of the anodes was performed using a Hitachi IM4000\u0026thinsp;+\u0026thinsp;ion milling system, which employs low-energy argon ions to create clean cross sections without introducing mechanical stress to the sample. Field-emission scanning electron microscopy (FESEM) was conducted on a ZEISS GeminiSEM 450 at an acceleration voltage of 5 kV and a probe current of 3 nA. Energy-dispersive X-ray spectroscopy (EDS) was performed using an Oxford Ultim Extreme detector (1024 x 768 pixels) at an acceleration voltage of 3 kV and a current of 3 nA, see also \u003cb\u003eSupplementary Note 6\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflicts of interest:\u003c/h2\u003e \u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\u003ch2\u003eAuthor contributions:\u003c/h2\u003e \u003cp\u003eConceptualization: M.H. and R.B.; Experimental concept: M.H.; Material fabrication: C.S. and S.K.; Sample preparation: M.H.; In situ measurement: M.H., R.J.S., O.S., J.V. and R.B.; DVC analysis: M.H., R.J.S. and O.S.; Visualization: M.H. and R.J.S.; Supervision: R.B.; Writing: M.H. and R.B.; All authors contributed to discussions of the research.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThe authors gratefully acknowledge the financial support under the scope of the COMET program within the K2 Center \u0026ldquo;Integrated Computational Material, Process and Product Engineering (IC-MPPE)\u0026rdquo; (Project ASSESS P1.10) and the funding by the Austrian Research Promotion Agency (FFG) from the Mobility of the Future programme, Proj. No. 891479 \u0026ldquo;OpMoSi\u0026rdquo;. ESRF is acknowledged for beam time allocation and access (proposal MA-4927\u003csup\u003e78\u003c/sup\u003e \u0026amp; MA-6174\u003csup\u003e79\u003c/sup\u003e) at ID16B beamline. Furthermore, Charlotte Cui is acknowledged for her support during laser preparation.\u003c/p\u003e\u003ch2\u003eData availability:\u003c/h2\u003e \u003cp\u003eAll data supporting the findings of this study are available within the article and its Supplementary Information. The underlying nano-SXCT datasets generated and analysed during the current study are publicly available via the ESRF data repository under the DOIs \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.15151/ESRF-ES-1190113340\u003c/span\u003e\u003cspan address=\"10.15151/ESRF-ES-1190113340\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.15151/ESRF-ES-1579881493\u003c/span\u003e\u003cspan address=\"10.15151/ESRF-ES-1579881493\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Additional processed data are available from the corresponding author upon reasonable request.\u003c/p\u003e\u003ch2\u003eCode availability:\u003c/h2\u003e \u003cp\u003eData pre-processing steps and the semantic segmentation model architecture are described in detail in the Methods. The custom code used for data pre-processing, training and analysis is available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWu X, Ji G, Wang J, Zhou G, Liang Z (2023) Toward Sustainable All Solid-State Li\u0026ndash;Metal Batteries: Perspectives on Battery Technology and Recycling Processes. Adv Mater 35:2301540\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNjema GG, Ouma RBO, Kibet JK (2024) A Review on the Recent Advances in Battery Development and Energy Storage Technologies. \u003cem\u003eJournal of Renewable Energy\u003c/em\u003e 2329261 (2024)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuilty CD et al (2023) Electron and Ion Transport in Lithium and Lithium-Ion Battery Negative and Positive Composite Electrodes. 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Preprint at https://\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8273007/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8273007/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAnodes with high silicon (Si) content, paired with nickel-manganese-cobalt (NMC) cathodes, enable interesting prospects for Li-ion batteries well beyond the state of the art. However, when Si alloys with lithium (Li), it undergoes significant volume changes, raising the critical question of how exactly the electrode and individual particles respond to the lithiation dynamics and thus impacting the battery performance. Here, we provide enhanced insights into the chemo-mechanical processes for cells with an 89 wt% Si anode paired with an NMC cathode. Electrode-scale deformation is linked with particle-scale mechanics by incorporating correlative multiscale 3D in situ investigations. Indeed, the combination of a sophisticated in situ cell setup, with high-resolution synchrotron X-ray computed nano-tomography, together with AI-driven segmentation and 4D strain mapping, allows us to detect pronounced spatial deformation and strain heterogeneities from the electrode to the single particle level. We observe diverse lithiation behaviours, anisotropic strain evolution and mechanically distinct transformation modes across hundreds of particles. Stress concentrators and fracture nucleation sites steer the transformation, generating localized strain fields decoupled from bulk electrode swelling. Indeed, many particles lithiate via complex internal network-like transformation routes. These 4D multiscale observations highlight key design levers for silicon-rich anodes, including defect screening, particle size optimization and electrode architecture engineering.\u003c/p\u003e","manuscriptTitle":"Bridging Particle-Scale Lithiation Mechanisms and Macroscopic Performance in High-Energy Density Si Anodes via Time-resolved Full 3D Visualisation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-17 08:28:43","doi":"10.21203/rs.3.rs-8273007/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dac6f251-d68c-4c0f-adc8-72f28dc4a0a6","owner":[],"postedDate":"December 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59749182,"name":"Physical sciences/Energy science and technology/Energy storage/Batteries"},{"id":59749183,"name":"Physical sciences/Materials science/Materials for energy and catalysis/Batteries"},{"id":59749184,"name":"Physical sciences/Physics/Techniques and instrumentation/Imaging techniques"},{"id":59749185,"name":"Physical sciences/Chemistry/Energy"}],"tags":[],"updatedAt":"2026-01-21T15:12:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-17 08:28:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8273007","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8273007","identity":"rs-8273007","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}