DIAD-Dual Imaging and Diffraction Beamline
E02-JEM ARM 300CF
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Kang
Xiang
,
Yueyuan
Wang
,
Shi
Huang
,
Hongyuan
Song
,
Alberto
Leonardi
,
Peter
Garland
,
Sharif
Ahmed
,
Michał M.
Kłosowski
,
Hongmei
Yang
,
Mengnie
Li
,
Jiawei
Mi
Diamond Proposal Number(s):
[31637, 35828]
Open Access
Abstract: Using quasi-simultaneous synchrotron X-ray diffraction and tomography techniques, we have studied in-situ and in real-time the nucleation and co-growth dynamics of the peritectic structures in an Al-Mn alloy during solidification. We collected ∼30 TB 4D datasets which allow us to elucidate the phases’ co-growth dynamics and their spatial, crystallographic and compositional relationship. The primary Al4Mn hexagonal prisms nucleate and grow with high kinetic anisotropy -70 times faster in the axial direction than that in the radial direction. In all cases, a ∼5 µm Mn-rich diffusion layer forms at the liquid-solid interface, creating a sharp local solute gradient that governs subsequent phase transformation. The peritectic Al6Mn phases nucleate epitaxially within this diffusion zone, initially forming a thin shell surrounding the Al4Mn with an orientation relationship of {10
0}HCP // {110}O, [0001]HCP // [001]O. Such ∼5 µm Mn-rich diffusion layers also cause solute depletion at the liquid side of the liquid-solid interface, limiting further epitaxial phase growth, but prompting phase re-nucleation and branching at crystal edges, resulting tetragonal prism structures that no longer follow the initial orientation relationship. The anisotropic interfacial kinetics and local region latent heat release also led to the formation of liquid-filled core defects at the centre of both phases. Furthermore, increasing cooling rate from 0.17 to 20°C/s can disrupt the stability of the solute diffusion zone, effectively suppressing the formation of the core defects and forcing a transition from faceted to non-faceted morphologies. Our work provides systematic new knowledge and practical approach for tailoring and controlling the peritectic structures in metallic alloys through the solidification processes.
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May 2026
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DIAD-Dual Imaging and Diffraction Beamline
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Diamond Proposal Number(s):
[33351]
Abstract: Utilizing green and renewable materials derived from biological sources is crucial for reducing environmental pollution. Natural wood is a clean and sustainable material. Densification methods have been shown to greatly enhance the mechanical properties of wood. However, the inherent hydrophilic and hygroexpansion characteristics of wood significantly limit the application of densified wood in various engineering fields. This study aimed to investigate the water absorption behavior and dimensional stability of natural and densified pine through water absorption experiments. The results showed that densified pine exhibited a similar three-stage water absorption behavior to that of natural pine. The water absorption behavior of densified pine caused by diffusion of water molecules as bound water in the cell wall (stage I), conforming to the Fickian model. In the subsequent stage II, excess water in the cell wall diffused into the cell lumen as free water. The water absorption behavior then deviated from the Fickian model and followed the Langmuir model. The significant reduction in the equilibrium moisture content of densified pine, compared to natural pine, can be attributed to a decrease in hemicellulose as well as smaller cell interstices and lumens. Moreover, unlike natural pine, where hygroexpansion was only in stage Ⅰ, densified pine expanded further in stage Ⅱ due to partial recovery of the cell lumen. Nuclear magnetic resonance (NMR), Fourier-transform infrared (FT-IR), Scanning electron microscopy (SEM) and X-ray computed tomography and diffraction techniques were employed to elucidate the effect of densification on dimensional stability and water absorption behavior of pine.
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Apr 2026
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DIAD-Dual Imaging and Diffraction Beamline
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Diamond Proposal Number(s):
[39247]
Open Access
Abstract: This work presents the design and development of a 3D printed flow cell tailored for X-ray computed microtomography of liquid–solid systems. The flow cell is manufactured using stereolithographic printing and utilizes a novel pillarless pull-through geometry. The use of the flow cell developed for K-11 DIAD (Dual Imaging and Diffraction beamline, Diamond Light Source, UK) is demonstrated with the in situ flow and selective recovery of an Sn precipitate from solution using an organic ligand. The 3D designs and components are made freely available with this publication.
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Mar 2026
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DIAD-Dual Imaging and Diffraction Beamline
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Abstract: Anode-free solid-state batteries (AF-SSBs) hold great promise for next-generation transportation electrification, offering improved safety, recyclability, and high performance (energy density >1500 Wh/L, specific energy >500 Wh/kg) at reduced cost (<$100/kWh) compared to conventional Li-ion batteries. However, their practical deployment is hindered by poor chemo-mechanical stability at the evolving anode|solid electrolyte (SE) interface, where localized ionic flux during cycling drives dendrite formation, internal short-circuiting, and premature failure. The buried and dynamic nature of this interface makes direct characterization especially challenging, and existing methods lack the ability to capture non-invasive, 3D operando insights into interfacial morphology, spatial dynamics, and strain evolution in full-cell AF-SSBs.
In this work, we conducted operando correlative synchrotron X-ray micro-computed tomography (XCT) and X-ray diffraction (XRD) at the DIAD beamline, Diamond Light Source (UK), to map interface evolution in real time. Custom PEEK-housed tube cells were cycled at 35 µA (2 mm Li | 19 mg LPSC | 3 mm stainless steel), with 13 tomographic scans collected across three charge–discharge cycles prior to short-circuiting. XCT resolved void formation, crack initiation, and fracture propagation, while XRD provided spatially resolved strain mapping and crystallographic fingerprints of interfacial contact evolution.
Our imaging data revealed pre-existing cracks within the SE pellet, as well as the nucleation of new spallation-like cracks originating at the current collector–SE interface that widened progressively during cycling. XRD mapping confirmed that these cracks coincided with regions of strain accumulation and interfacial delamination, offering a crystallographic fingerprint of contact evolution. Importantly, these structural changes could be directly correlated with electrochemical signatures: the onset of fracture formation aligned with abrupt cell polarization and preceded catastrophic short-circuiting. Together, this correlative XCT–XRD methodology provides the integrated view of how morphology, strain, and electrochemistry couple to govern failure in AF-SSBs.
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Mar 2026
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DIAD-Dual Imaging and Diffraction Beamline
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Diamond Proposal Number(s):
[38775]
Open Access
Abstract: Understanding the interactions between microstructure, strain, phase and material behavior is crucial in scientific fields such as energy storage, carbon sequestration and biomedical engineering. However, quantifying these correlations is challenging, as it requires the use of multiple instruments and techniques, often separated by space and time. The Dual Imaging and Diffraction (DIAD) beamline at Diamond Light Source is designed to address this challenge. DIAD allows its users to visualize internal structures (in two and three dimensions), identify compositional/phase changes and measure strain. It enables in situ and operando experiments that require spatially correlated information. DIAD provides two independent beams combined at one sample position, allowing `quasi-simultaneous' X-ray computed tomography and X-ray powder diffraction. A unique functionality of the DIAD configuration is the ability to perform `image-guided diffraction', where the micrometre-sized diffraction beam is scanned over the complete area of the imaging field of view without moving the specimen. This moving-beam diffraction geometry enables the study of fast-evolving and motion-susceptible processes and samples. Here, we discuss the novel moving-beam diffraction geometry, presenting the latest findings on the reliability of both the geometry calibration and the data-reduction routines used. We provide a comprehensive quantitative assessment of the moving-beam diffraction geometry implemented at the DIAD beamline, which will serve as a reference for beamline users. Our measurements confirm that diffraction is most sensitive to the moving-beam geometry for the conventional transmission geometry of the detector. The observed data confirm that the motion of the Kirkpatrick–Baez mirror coupled with a fixed-aperture slit results in a rigid translation of the beam probe, without affecting the angle of the incident-beam path to the sample. Our measurements demonstrate that a nearest-neighbor calibration can achieve the same accuracy as a self-calibrated geometry when the distance between the calibrated and probed sample regions is smaller than or equal to the beam spot size. The absolute error of the moving-beam diffraction geometry at DIAD with typical calibration setup remains below 0.01%, which is the accuracy we observe for the beamline with stable beam operation.
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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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DIAD-Dual Imaging and Diffraction Beamline
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James
Le Houx
,
Daniel
Mckay Fletcher
,
Alberto
Leonardi
,
Katherine A.
Williams
,
Nancy
Walker
,
Fernando
Alvarez-Borges
,
Ebrahim
Afsar Dizaj
,
Madhu
Murthy
,
Ronan
Smith
,
Liam
Perera
,
Navid
Aslani
,
Andrew
James
,
Sharif
Ahmed
,
Tiina
Roose
,
Siul
Ruiz
Diamond Proposal Number(s):
[30961, 32138, 33343]
Open Access
Abstract: Soil compaction and escalating global drought increase soil strength and stiffness. It remains unclear which plant root biomechanical mechanisms/traits enable growth in these harsh conditions. Here, we combine synchrotron X-ray computed tomography with spatially resolved X-ray diffraction to characterize the biomechanics of a replica root-soil system. We map the strain field around the root tip analog, finding strong agreement with finite element simulations, thereby demonstrating a promising new in vivo measurement protocol.
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Jul 2025
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Open Access
Abstract: Polyelemental nanoparticles (PE NPs), those consisting of four or more elements, exhibit unique properties from synergistic compositional effects. Examples include high entropy alloys, high entropy intermetallics, and multiphase types, including Janus and core-shell architectures. While colloidal syntheses offer excellent structural control for mono- and bi-elemental compositions, achieving the same control for PE NPs remains challenging. Here, this challenge is addressed with a NP conversion strategy wherein different types of PE NPs – including high entropy alloy, high entropy intermetallic, and multi-phase Janus nanoparticles – are achieved through thermal transformation of readily synthesized colloidal core-shell NPs. Through systematic variations in stoichiometry and metal identity to the core-shell precursor NPs, along with atomistic simulations that probe phase stabilities, the final mixing states of the various NPs are found to be governed by the balance between the enthalpy and entropy of mixing. Our annealing method allows intermediate states of mixing to be trapped, creating distinct surface ensembles that were evaluated as catalysts. This study is the first, to our knowledge, to report colloidally derived precursor NPs enabling the synthesis of all types of PE NPs in a single process. This NP conversion strategy offers a general route to diverse PE NPs.
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Apr 2025
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DIAD-Dual Imaging and Diffraction Beamline
I13-2-Diamond Manchester Imaging
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Diamond Proposal Number(s):
[32980]
Open Access
Abstract: Machine learning techniques are being increasingly applied in medical and physical sciences across a variety of imaging modalities; however, an important issue when developing these tools is the availability of good quality training data. Here we present a unique, multimodal synchrotron dataset of a bespoke zinc-doped Zeolite 13X sample that can be used to develop advanced deep learning and data fusion pipelines. Multi-resolution micro X-ray computed tomography was performed on a zinc-doped Zeolite 13X fragment to characterise its pores and features before spatially resolved X-ray diffraction computed tomography was carried out to characterise the topographical distribution of sodium and zinc phases. Zinc absorption was controlled to create a simple, spatially isolated, two-phase material. Both raw and processed data are available as a series of Zenodo entries. Altogether we present a spatially resolved, three-dimensional, multimodal, multi-resolution dataset that can be used to develop machine learning techniques. Such techniques include the development of super-resolution, multimodal data fusion, and 3D reconstruction algorithms.
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Feb 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
,
Carolyn
Atkins
,
Eric
Béchet
,
Alberto
Corbi Bellot
,
Stefan
Bosse
,
Younes
Chahid
,
Cheng-Ying
Chou
,
Robert
Culver
,
Lewis
Dixon
,
Johan
Friemann
,
Amin
Garbout
,
Clémentine
Hatton
,
Audrey
Henry
,
Christophe
Leblanc
,
Alberto
Leonardi
,
Jean Michel
Létang
,
Harry
Lipscom
,
Tristan
Manchester
,
Bas
Meere
,
Simon
Middleburgh
,
Iwan
Mitchell
,
Liam
Perera
,
Marti
Puig Fantauzzi
,
Jenna
Tugwell-Allsup
Diamond Proposal Number(s):
[29820]
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 (CT). 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 optimization problems and to train machine learning algorithms. This paper presents applications of gVXR related to XCT.
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Oct 2024
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