I18-Microfocus Spectroscopy
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Diamond Proposal Number(s):
[34311]
Abstract: Rice is a staple food for over half the world's population. This study uniquely investigates the spatial distribution of key micronutrients (Cu, Mn, Fe, Zn) in cooked brown, white, and parboiled rice using Synchrotron Micro-X-ray Fluorescence (sXRF) for the first time. Complementary analysis with Inductively Coupled Plasma Mass Spectrometry (ICP-MS) validates bulk elemental concentrations. Results from this dual-approach study reveal significantly higher micronutrient concentrations in brown rice compared to white or parboiled rice, with nutrients predominantly localised in the peripheral layers and minimal presence in the endosperm. Notably, sXRF imaging identified nutrient-rich pockets within the grain periphery, offering new perspectives on nutrient distribution beyond peripheral accumulation. Additional insights include the impact of rice section thickness (50 and 150 μm) and beam dwell times (0.5 and 30s) on sXRF sensitivity and resolution, highlighting trade-offs in detection capabilities, advancing our understanding of micronutrient localisation in cooked rice.
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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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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):
[35733]
Open Access
Abstract: This research examines the dynamics of reactive CO2 transport in carbonate rock, focusing on the impact of carbonic acid-induced formation damage. We provide real-time visualization of these processes by employing four-dimensional (4D) high-resolution synchrotron imaging at the I13 beamline hosted at the Diamond Light Source. We visualize and quantify the temporal effects of reactive CO2 transport at the pore scale in carbonate rock. The experiment involved injecting CO2-saturated brine through the sample with in situ scanning to track the different stages of chemical dissolution. Analysis of the images shows a channelled dissolution pattern which corresponds with a gradual increase in porosity due to pore structure changes. Pore network models were generated from the segmented images to carry out a sequence of drainage and imbibition simulations. The result demonstrated that reduced capillary entry pressure with increased pore connectivity after dissolution. Furthermore, the trapping efficiency was quantified to predict a slight decrease in dissolution as the pores become broader and better connected.
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Oct 2025
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I13-2-Diamond Manchester Imaging
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Abstract: The drying process of Li-ion batteries contributes significantly to both their manufacturing cost and electrochemical and mechanical performance. Mud cracking is a mechanical defect which occurs spontaneously as a result of capillary pressure during the final stages of the drying process. This thesis investigates the causes of mud cracking, the mechanism of their formation and their impact on ion transport and electrochemical performance. At the core of the work is the observation that mud cracks are qualitatively similar to engineered vertical channels, which have been introduced into Li-ion battery electrodes by a variety of manufacturing methods in order to enhance ion transport and improve capacity at high charge rates or in thick electrodes.
It was shown that cracks enhance potential ion flux through the electrode thickness to a greater degree than by increasing porosity by the same volume. Cracked electrodes of 70 – 130 μm dry thickness were shown to have improved discharge capacities at rates of 1 – 4 C, compared with uncracked electrodes of equivalent thickness - as much as 68 % higher capacity retention at 4C. These performance enhancements were related to 3D crack network structures determined by X-ray computed tomography imaging, which analysis showed that the arrangement of pore channels is of importance in determining the efficacy of vertical porosity in improving electrode performance. Image-based electrochemical modelling was investigated as a tool for better understanding experimental electrochemical data, and this work highlighted the value of multi-modal model validation, including literature synchrotron studies.
The formation of mud cracks during the electrode drying process was studied using in situ X-ray computed tomography. This imaging showed the microstructural evolution of battery electrodes during the drying process with unprecedented clarity and resolution, as well as the relationship between crack growth and local microstructural features. Cracking intensity and morphology were shown to be strongly influenced by coating thickness, in agreement with prior literature, as was the delamination which occurs with severe cracking. Cracks were also shown to nucleate where air bubbles are present in the slurry, and this mode of crack growth was shown to differ markedly from cracks in bubble-free coatings.
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Oct 2025
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I14-Hard X-ray Nanoprobe
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Gaewyn
Ellison
,
Rhiannon E.
Boseley
,
Meg
Willans
,
Sarah
Williams
,
Evelyn S.
Innes
,
Paige
Barnard
,
Julia
Koehn
,
Somayra S. A.
Mamsa
,
Paul
Quinn
,
Daryl L.
Howard
,
Simon A.
James
,
Mark J.
Hackett
Diamond Proposal Number(s):
[34101]
Open Access
Abstract: Understanding the role of metal ions in normal and abnormal cell function continues to emerge as a critical research area in the biological and biochemical sciences. This is especially true in the context of brain health and neurodegenerative diseases, as the brain is especially enriched in metal ions. A range of microscopy and bioanalytical techniques are available to assist in characterizing and observing changes to the brain metallome. As is the case in many other scientific fields, the integration of multiple analytical methods often yields a more complete chemical picture and deeper biological understanding. Herein, we present a case study applying 4 different analytical methods to provide spatially resolved characterization of chemical and biochemical parameters relating to the iron (Fe) metallome within a specific brain region, cornu ammonis sector 1 (CA1) of the hippocampus. The CA1 hippocampal sector was chosen for investigation due to its known endogenous enrichment in Fe and its selective vulnerability to neurodegeneration. The 4 analytical techniques applied were X-ray fluorescence microscopy (to quantify Fe distribution); X-ray absorption near-edge structure (XANES) spectroscopy to reveal information on Fe oxidation state and coordination environment; immuno-fluorescence to reveal relative abundance of Fe storage proteins (heavy chain ferritin and mitochondrial ferritin); and spatial transcriptomics to reveal gene expression pathways relevant to Fe homeostasis. Collectively, the results highlight that although pyramidal neurons in lateral and medial regions of the hippocampal CA1 sector are morphologically similar, key differences in the Fe metallome are evident. The observed differences within the hippocampal CA1 sector potentially indicate a higher oxidative environment and higher metabolic turnover in medial CA1 neurons relative to lateral CA1 neurons, which may account for the heightened vulnerability to neurodegeneration that is observed in the medial CA1 sector.
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Oct 2025
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I18-Microfocus Spectroscopy
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Diamond Proposal Number(s):
[35162]
Open Access
Abstract: Enamel erosion alters the structural integrity of the tooth surface, which can be measured using indentation techniques. However, traditional single-load indentation methods assume homogeneity within the eroded enamel, overlooking potential stratification within the subsurface lesion. This study investigates the presence of mechanical and porosity gradients within the enamel following simulated dietary acid exposure and examines how lesion depth and structure change with continued erosion. We applied varying-load micro-indentation to human enamel subjected to citric acid challenge, revealing a distinct stratification of mechanical properties. A soft superficial layer (~1- to 2-µm thick) exhibited significantly reduced hardness and was easily removed by ultrasonication, indicating its fragility. Beneath this layer, mechanical properties stabilized despite prolonged acid exposure (~3 min), suggesting a saturation point in lesion development. Profilometric analysis confirmed that although material loss increased with erosion time, the depth of the altered subsurface zone remained constant. To explore the porosity distribution, we used a novel gold nanoparticle labeling technique coupled with synchrotron-based X-ray fluorescence imaging. Nanoparticles (~20 nm) penetrated to depths of 15 to 20 µm, aligning closely with mechanical gradients inferred from indentation measurements. These findings indicate that subsurface enamel exhibits not only mechanical stratification but also corresponding variations in porosity. Our results demonstrate the limitations of single-load indentation in characterizing erosion-affected enamel and highlight the utility of multiload approaches in detecting structural heterogeneity. The correlation between mechanical softening and increased porosity suggests that the enamel subsurfaces are differentially affected. These findings raise important implications for therapeutic intervention: should remineralization strategies shift from bulk mineral delivery to layer-specific, functionally informed repair?
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Oct 2025
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B16-Test Beamline
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B.
Cline
,
D.
Banks
,
M.
Bishop
,
A.
Davis
,
J.
Harris
,
M.
Hart
,
S.
Knowles
,
T.
Nicholls
,
J.
Nobes
,
S.
Pradeep
,
M.
Roberts
,
M. C.
Veale
,
M. D.
Wilson
,
V. P.
Dhamgaye
,
O. J. L.
Fox
,
K. J. S.
Sawhney
,
S.
Scully
Diamond Proposal Number(s):
[36472]
Open Access
Abstract: In this paper, results are presented from the characterisation of a 2 mm thick Redlen Technologies high-flux-capable Cadmium Zinc Telluride (HF-CZT) sensor hybridised to the small-pixel, spectroscopic-imaging HEXITEC_MHz ASIC. Dynamic datasets were taken on the B16 Test Beamline at the Diamond Light Source to study a previously-identified 'excess-leakage-current' phenomenon in HF-CZT, where additional leakage current was temporarily generated upon the application of an X-ray flux. A study of the response of the detector as a function of X-ray intensity demonstrated a measurable excess leakage current signal above 105 ph s-1 mm-2. At a 20 keV flux of 7.81 × 106 ph s-1 mm-2, this effect contributed a signal equivalent to 3.79 ± 1.59 nA mm-2in addition to the expected photocurrent. On removal of X-rays at this flux, this excess leakage current took ∼ 10 s to decay below the noise floor of the detector. This long lifetime has implications for detectors required to operate at high frame rates and fluxes. The use of a small-pixel detector also allowed the spatial variation of this effect to be studied. A per-pixel comparison between the magnitude of the excess leakage current and the spectroscopic performance of the pixel showed no correlation. This suggests that the phenomenon is less likely to be a bulk-crystal effect and more likely the result of the properties of the CZT surface or metal/semiconductor interface. An Arrhenius analysis of the temperature-dependence of the dark and excess leakage currents in the detector yielded values of 0.69 ± 0.04 eV and 0.13 ± 0.01 eV respectively. The change in dark current with temperature is consistent with deep levels pinning the Fermi level close to the mid band gap, whilst the activation energy of the excess leakage current suggests shallower defects at the metal-semiconductor interface are responsible.
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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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