I13-2-Diamond Manchester Imaging
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Diamond Proposal Number(s):
[35875]
Open Access
Abstract: Aqueous zinc metal batteries (AZMBs) face significant challenges in achieving reversibility and cycling stability, primarily due to hydrogen evolution reactions (HER) and zinc dendrite growth. In this study, by employing carefully designed cells that approximate the structural characteristics of practical batteries, we revisit this widely held view through in-operando X-ray radiography to examine zinc dendrite formation and HER under near-practical operating conditions. While conventional understanding emphasizes the severity of these processes, our findings suggest that zinc dendrites and HER are noticeably less pronounced in dense, real-operation configurations compared to modified cells, possibly due to a more uniform electric field and the suppression of triple-phase boundaries. This study indicates that other components, such as degradation at the cathode current collector interface and configuration mismatches within the full cell, may also represent important barriers to the practical application of AZMBs, particularly during the early stages of electrodeposition.
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Dec 2025
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B16-Test Beamline
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Diamond Proposal Number(s):
[31723]
Open Access
Abstract: Out-of-plane fiber wrinkles in carbon-fiber-reinforced polymer laminates trigger premature failure, yet remain difficult to detect and assess. This study introduces a powerful new diagnostic capability: the pairing of X-ray computed tomography (XCT) and Wide Angle X-ray Scattering (WAXS) during in situ compression of specimens containing small (0.2 mm) and large (0.5 mm) wrinkles. This approach enables, for the first time, detailed field-resolved mapping of axial () and radial () lattice microstrain. A new orientation-aware reduction pipeline supports texture classification, peak fitting, and per-point zero-load referencing, requiring minimal intervention and enabling scalable industrial deployment. In large wrinkles, radial microstrain reached −14.5 µ−1, compared to −11.0 µ−1 axially; small wrinkles exhibit approximately one-third of this magnitude. Strain hotspots are identified prior to failure, and tomography confirms these regions as the origin of delamination, matrix cracking, and fiber kink banding. To verify the results analytically, a compact, orientation-aware predictor is developed, reproducing measured fields with a mean absolute error on the order of . These findings establish radial microstrain gradients as a robust, non-destructive indicator of wrinkle severity, providing unique insight and enabling defect behavior to be embedded into full-scale modeling. This supports performance-based rejection criteria and targets inspection in aerospace laminates.
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Dec 2025
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DIAD-Dual Imaging and Diffraction Beamline
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Loris
Chavée
,
Emile
Haye
,
Jochen M.
Schneider
,
Stanislav
Mráz
,
Andreas
Pflug
,
Dennis
Barton
,
Armel
Descamps
,
Claudie
Josse
,
Jérôme
Müller
,
Pavel
Moskovkin
,
James
Marrow
,
Amael
Caillard
,
Stephane
Lucas
Diamond Proposal Number(s):
[34010]
Abstract: The deposition of functional coatings on open-cell foam substrates using magnetron
sputtering is gaining popularity, particularly for applications like Oxygen Evolution
Reaction (OER)/Hydrogen Evolution Reaction (HER) catalysis, batteries, and
supercapacitors. While most research focuses on performance, little attention has
been paid to the coating growth mechanisms or properties within the foam, which could
significantly impact device performance. This work investigates the properties and
growth mechanisms of TiO₂ coatings inside porous foams, using experimental and
modeling techniques.
The structure, composition and thickness of the coating on the outermost surface of
the foam are studied using Focused Ion Beam (FIB), Scanning Transmission Electron
Microscopy (STEM), Energy-Dispersive X-Ray Spectroscopy (EDS), Selected Area
Electron Diffraction (SAED) and High-Resolution Transmission Electron Microscopy
(HRTEM). The experimental results reveal the formation of a dense, (quasi-
)stoichiometric and crystalline coating.
Numerical simulations and experiments highlight the transport of plasma particles in
the foam. Interestingly, Direct Simulation Monte Carlo (DSMC)/Particle-In-Cell Monte
Carlo (PICMC) models, coupled with Mass-Energy Analyzer (MEA) experiments,
demonstrate that the particle flux is reduced, but the particle energy distribution is not
Accepted Manuscript affected while traveling inside the foam. Using kinetic Monte Carlo (kMC) thin film
growth models provided by Virtual CoaterTM, the physical properties of the coating
inside the foam have been modeled, and the drop in coating thickness as well as the
impact of bias voltage on densification, resistivity, and optical absorption are
confirmed. Synchrotron X-Ray Diffraction (SXRD) analyses of the foam demonstrate
that the same crystalline phase is obtained along the foam thickness, but it can be
tailored with bias voltages. The decrease in the recorded SXRD signal with increasing
depth inside the foam also suggests a drop in coating thickness.
The new insights on the properties of coatings inside open-cell foams presented in this
study can be used to improve future foam-based devices.
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Dec 2025
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DIAD-Dual Imaging and Diffraction Beamline
I12-JEEP: Joint Engineering, Environmental and Processing
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Franck P.
Vidal
,
Shaghayegh
Afshari
,
Sharif
Ahmed
,
Alberto
Albiol
,
Francisco
Albiol
,
Éric
Béchet
,
Alberto Corbí
Bellot
,
Stefan
Bosse
,
Simon
Burkhard
,
Younes
Chahid
,
Cheng-Ying
Chou
,
Robert
Culver
,
Pascal
Desbarats
,
Lewis
Dixon
,
Johan
Friemann
,
Amin
Garbout
,
Marcos
García-Lorenzo
,
Jean-François
Giovannelli
,
Ross
Hanna
,
Clémentine
Hatton
,
Audrey
Henry
,
Graham
Kelly
,
Christophe
Leblanc
,
Alberto
Leonardi
,
Jean Michel
Létang
,
Harry
Lipscomb
,
Tristan
Manchester
,
Bas
Meere
,
Claire
Michelet
,
Simon
Middleburgh
,
Radu P.
Mihail
,
Iwan
Mitchell
,
Liam
Perera
,
Martí
Puig
,
Malek
Racy
,
Ali
Rouwane
,
Hervé
Seznec
,
Aaron
Sújar
,
Jenna
Tugwell-Allsup
,
Pierre-Frédéric
Villard
Diamond Proposal Number(s):
[29820]
Open Access
Abstract: gVirtualXray (gVXR) is an open-source framework that relies on the Beer–Lambert law to simulate X-ray images in real time on a graphics processor unit (GPU) using triangular meshes. A wide range of programming languages is supported (C/C++, Python, R, Ruby, Tcl, C#, Java, and GNU Octave). Simulations generated with gVXR have been benchmarked with clinically realistic phantoms (i.e. complex structures and materials) using Monte Carlo (MC) simulations, real radiographs and real digitally reconstructed radiographs (DRRs), and X-ray computed tomography (XCT). It has been used in a wide range of applications, including real-time medical simulators, proposing a new densitometric radiographic modality in clinical imaging, studying noise removal techniques in fluoroscopy, teaching particle physics and X-ray imaging to undergraduate students in engineering, and XCT to masters students, predicting image quality and artifacts in material science, etc. gVXR has also been used to produce a high number of realistic simulated images in optimisation problems and to train machine learning algorithms. This paper presents a comprehensive review of such applications of gVXR.
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Nov 2025
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I13-2-Diamond Manchester Imaging
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Diamond Proposal Number(s):
[22053, 31714]
Abstract: Accurate predictions of the size and morphology of microstructural features, including defects such as porosity, are essential for predicting the performance of engineering components. Although several multiscale approaches exist in the literature, including direct simulations and volume-averaged models, their predictions are limited due to large computational times and relatively low accuracy. This work utilises transfer learning to link the macroscopic field variable distributions to the mesoscale, in order to estimate sub-grid microstructural defects. Specifically, the model parameters are corrected using experimental measurements of sub-grid scale defects. The proposed methodology is illustrated for predicting porosity in an aluminium alloy automotive component produced using high pressure die casting. The model uses a physics-based localised porosity model for combined gas and shrinkage porosity to train an artificial neural network. This trained machine learning model is subsequently re-trained using macroscale field variables and experimental X-ray microtomography porosity measurements from industrial component made using different process conditions. An unseen region of the same component is used for further testing of the performance of the model. The results show good prediction of pore size distribution and location. These results are then used to determine component fatigue life. Thus, a full process-structure-property model is established. The framework has the potential to be applied to a large class of problems involving predictions of microstructural features over entire macroscopic components.
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Nov 2025
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I12-JEEP: Joint Engineering, Environmental and Processing
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Abstract: This thesis develops and evaluates a fully automated deep learning workflow for segmenting voids and material phases in X-ray computed tomography of carbon fibre and flax fibre polymer composites. For the carbon fibre system, fibre, matrix, and void masks were generated through a reproducible Python-based pipeline combining slice-wise intensity normalisation, two-stage void detection, morphological refinement, and Otsu-based fibre–matrix separation, followed by targeted manual verification in Dragonfly. For the flax fibre system, segmentation masks were produced and refined manually and unified into a consistent three-phase labelling scheme (matrix, fibre, void). These reference datasets were then used to train five lightweight convolutional neural network architectures (UNet++, UNet3+, Attention UNet, DeepLabV3+ Transformer, and LR-ASPP Transformer) under identical conditions, using paired 256 × 256 patches, controlled label-safe augmentation, and a fixed slice-level train–validation split. A higher-load carbon fibre state (140 N) was withheld entirely from training and used exclusively to evaluate the models on previously unseen microstructural damage. The results demonstrate that compact encoder–decoder networks can accurately localise voids and robustly separate fibre and matrix phases across both composite systems, including under low contrast and evolving damage, while maintaining computational efficiency suitable for routine XCT workflows.
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Nov 2025
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I13-2-Diamond Manchester Imaging
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Diamond Proposal Number(s):
[35733]
Open Access
Abstract: Underground carbon dioxide (CO2) storage is a critical approach for mitigating climate change by sequestering CO2 in deep geological formations. The interaction between injected super critical (sc) CO2 and resident brine within pores results in complex two-phase flow dynamics that influence the efficiency and security of storage. While previous studies have mainly focused on capillary-dominated regimes, where fluid phases flow at low velocities, the transitional intermittent flow regime—characterised by higher flow rates and complex displacement dynamics—remains less understood. This study investigates the onset and development of intermittent flow pathways in CO2-brine systems through high-resolution synchrotron X-ray micro-computed tomography imaging of a carbonate rock sample. The core-flooding experiments were conducted under 8 MPa and 50 °C to examine pore-scale fluid configuration changes as a function of capillary number (Ca). The results indicate that intermittent flow emerges at lower Ca values than previously observed in oil-brine systems, with a distinct transition from Darcy flow to intermittent flow. Moreover, the saturation of the intermittent phase stabilises beyond a threshold Ca, suggesting another phase transition within the intermittent flow regime. These findings provide new insights into the fundamental mechanisms of two-phase flow dynamics at the pore scale, revealing a stable intermittent flow regime at higher flow rates, with potential implications for improved injectivity under non-equilibrium conditions.
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Nov 2025
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DIAD-Dual Imaging and Diffraction Beamline
E02-JEM ARM 300CF
I12-JEEP: Joint Engineering, Environmental and Processing
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Abstract: This thesis presents a comprehensive investigation into the ultrasound-assisted processing of Al alloys and graphite materials using ultrafast synchrotron X-ray imaging and megahertz (MHz) X-ray free electron laser (XFEL) microscopy techniques, with emphasis on understanding the multiscale and multiphysics mechanisms driving multiphase evolution of Al alloy in solidification and the layer exfoliation of graphite materials. The unifying theme is the exploration of how ultrasonically generated physical phenomena, i.e., cavitation, shockwaves, and acoustic streaming, govern microstructural evolution at multiple scales. This comparative approach provides a comprehensive understanding of ultrasound-matter interactions, revealing universal principles that can be applied to optimize processing parameters for a wide range of materials. The key findings are summarized as follows:(1) In-situ synchrotron X-ray tomography and diffraction revealed, for the first time, the nucleation and co-growth dynamics of multiple Fe-rich intermetallics and their dynamic interactions with the Al dendrites of the recycled Al-5Cu-1.5Fe-1Si alloy in solidification under ultrasound melting processing (USMP). USMP significantly refined the α-Al dendrites, modified the morphologies of α-Fe and β-Fe phases, and altered their spatial distributions, thereby enhancing structural homogeneity and potentially improving mechanical properties. (2) By taking the full advantage of MHz XFEL microscopy, we have imaged and quantified, at ns time scale and μm length scale simultaneously, the local shockwaves produced by the implosion of a single cavitation bubble, multiple bubbles and bubble clouds, as well as the layer exfoliation dynamics under such shockwave impacts. The results confirmed that exfoliation is governed not by a single implosion event, but by repeated cyclic forces induced by shockwave impact, with exfoliation behaviour strongly dependent on local defects and graphite structure. (3) Using quasi-simultaneous synchrotron X-ray tomography and diffraction, we have studied in-situ the complicated peritectic reaction mechanisms involving Al4Mn and Al6Mn phases in an Al-8Mn alloy during the solidification process. The real-time evolution of the spatial and orientation relationships between these intermetallics was quantified for the first time, revealing the highly anisotropic faceted growth and intricate coalescence patterns that deviated from the equilibrium solidification models.
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Nov 2025
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B16-Test Beamline
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Diamond Proposal Number(s):
[30528]
Open Access
Abstract: This paper demonstrates a new approach that exploits both lattice strain mapping via Wide Angle X-ray Scattering (WAXS) and Digital Volume Correlation (DVC) of Computed Tomography (CT) to understand the material response at different length scales in Carbon Fibre Reinforced Polymers (CFRPs) under in-situ loading, a phenomenon of substantial importance for the modelling, design, and certification of composite structures. WAXS gives insight into fibre lattice strain, while DVC provides sub-laminate response in the CFRP. A detailed numerical simulation was also developed to compare with these novel experimental methods. This approach is the first demonstration that the strain within the crystalline regions of the fibre is distinct from the sub-laminate behaviour, with up to 80 % and 36 % differences in the longitudinal and transverse directions, respectively, as a result of the complex microstructure of the fibres. An improved understanding of composite behaviour is fundamental to understanding how strain accommodation leads to structural failure, providing routes to refine part rejection criteria and reduce the environmental impact of this increasingly widespread material class.
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Oct 2025
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I13-2-Diamond Manchester Imaging
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Diamond Proposal Number(s):
[31134]
Open Access
Abstract: Growth kinetics and orientation selection play a significant role in microstructure evolution during metal solidification, while gravity-induced convection adds significant complexity to the process. In-situ, time-resolved X-ray imaging of solidifying grain-refined Al–20 wt.% Cu alloy onboard the MASER-13 sounding rocket enabled the study of equiaxed dendrite growth under diffusion-controlled conditions, eliminating the influence of gravity. A machine learning-enabled analytical pipeline was developed to extract and evaluate the spatiotemporal behaviour of a large number of individual dendrites, including their growth characteristics, rotations and interactions. Post-flight synchrotron X-ray computed tomography and electron backscatter diffraction were used to reconstruct the three-dimensional dendrite structure with embedded details of crystallographic orientations. Correlated data analysis confirmed that most dendrites grew along directions parallel to the {100} plane under highly isothermal, diffusion-controlled conditions. However, growth along atypical directions was also observed, even in this simplified regime. The benchmark data revealed variation in dendrite arm evolution, influenced by local grain interactions and crystallographic orientation selection. It is shown that the equiaxed grains have random crystallographic orientations and evidence suggests that these survive from shortly after nucleation in the bulk liquid under microgravity conditions. The data processing protocols demonstrated here highlight the potential of integrating advanced experimental techniques with modern data science approaches to analyse solidification microstructure formation in metallic alloys under terrestrial and microgravity conditions.
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Oct 2025
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