X-ray diffraction of dynamically compressed matter on the Z-accelerator.
Abstract not provided.
Ao, Tommy↗
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A machine-learning approach to measure 3D sample properties from 2D Transmission Electron Microscopy images
Transmission Electron Microscopy (TEM) is a powerful tool for the characterization of materials at the nanoscale; however, its inherent two-dimensional (2D) nature poses significant challenges to accurately measure three-dimensional (3D) properties. We introduce a supervised machine-learning model that predicts 3D structural information, such as sample thickness and curvature, from a series of conventional 2D TEM images. The model, a U-Net convolutional neural network, is trained on a large synthetic dataset generated from dynamical diffraction simulations that model TEM’s complex, nonlinear image formation, accounting for sample thickness and curvature. This physically realistic framework enables exploration of a broad parameter space impractical to sample experimentally. We demonstrate that the trained model has accurate predictions for experimental single-crystal silicon samples, achieving performance comparable to established measurement techniques. This work highlights the critical role of robust, simulation-based training in overcoming the limitations of real-world imaging artifacts and inconsistent sample geometries. By integrating machine learning with numerical simulations, we offer an efficient and scalable framework for quantitative TEM analysis, paving the way for more sophisticated 3D characterization of complex materials.
Dynamical diffraction↗
Large Angle Rocking Beam Electron Diffraction Utilizing Electron Direct Detector
Electron diffraction of a crystal is fundamentally a function of the potential of that crystal. The intensity of electron diffraction patterns is, as a result, sensitive to the charge density of atoms and bonding inside crystals. Experimentally, the traditional method to probe this information is quantitative Convergent Beam Electron Diffraction (CBED). Quantitative CBED or QCEBD is a method which uses dynamic diffraction theory to quantify CBED intensities and to extract information about crystal structure and bonding. The sensitivity of dynamical scattering is leveraged to measure crystal symmetry and crystal structure factors. At its limit, electron structure factors are measured at high accuracy allowing access to chemical bonding information, which corroborate theoretical calculations through multipole model refinements of the experimental charge density. The primary limit to QCBED is the requirement of a non-overlapping convergent beam. This subsequently limits QCBED to crystals with small unit cells which are stable under the focused probe.
Busch, Robert↗
The fast multi-frame X-ray diffraction detector at the Dynamic Compression Sector
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Sinclair, N.W.↗
Accurate quantification of lattice temperature dynamics from ultrafast electron diffraction of single-crystal films using dynamical scattering simulations
In ultrafast electron diffraction (UED) experiments, accurate retrieval of time-resolved structural parameters, such as atomic coordinates and thermal displacement parameters, requires an accurate scattering model. Unfortunately, kinematical models are often inaccurate even for relativistic electron probes, especially for dense, oriented single crystals where strong channeling and multiple scattering effects are present. This article introduces and demonstrates dynamical scattering models tailored for quantitative analysis of UED experiments performed on single-crystal films. As a case study, we examine ultrafast laser heating of single-crystal gold films. Comparison of kinematical and dynamical models reveals the strong effects of dynamical scattering within nm-scale films and their dependence on sample topography and probe kinetic energy. Applying to UED experiments on an 11 nm thick film using 750 keV electron probe pulses, the dynamical models provide a tenfold improvement over a comparable kinematical model in matching the measured UED patterns. Also, the retrieved lattice temperature rise is in very good agreement with predictions based on previously measured optical constants of gold, whereas fitting the Debye–Waller factor retrieves values that are more than three times lower. Altogether, these results show the importance of a dynamical scattering theory for quantitative analysis of UED and demonstrate models that can be practically applied to single-crystal materials and heterostructures.
36 MATERIALS SCIENCE↗
In Vitro and In Silico Studies of Chitin and Chitosan Based Nanocarriers for Curcumin and Insulin Delivery
The evaluation of drug delivery potential, molecular interactions of the polymeric nanoparticles with the drug molecule and release kinetics encounters more time consumption and also cost. In this study, we have adopted the combination of in vitro and in silico approaches to evaluate the drug delivery property of the polymeric nanoparticles viz. chitin and chitosan. Herein, two different therapeutic agents such as curcumin (a hydrophobic drug) and insulin (a therapeutic protein) were used to study the delivery potential of chitin and chitosan nanoparticles. The drug loaded chitin and chitosan nanoparticles were prepared and characterized using Fourier transform infra red spectroscopy, X-ray diffraction, dynamic light scattering and scanning electron microscopy analysis. In the in vitro drug delivery experiments, chitosan nanoparticles exhibited better encapsulation efficiency, drug loading capacity and prolonged release of the drug molecules than that of the chitin nanoparticles to both curcumin and insulin. Meanwhile the in silico experiments such as molecular docking and molecular dynamics predicted the molecular interactions and binding energy involved between the nanoparticles and the drug molecules. From this study, we suggest that the chitosan nanoparticles could be used as a carrier molecule for both curcumin and insulin. Graphical Abstract: .
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns
Abstract A fast, robust pipeline for strain mapping of crystalline materials is important for many technological applications. Scanning electron nanodiffraction allows us to calculate strain maps with high accuracy and spatial resolutions, but this technique is limited when the electron beam undergoes multiple scattering. Deep-learning methods have the potential to invert these complex signals, but require a large number of training examples. We implement a Fourier space, complex-valued deep-neural network, FCU-Net, to invert highly nonlinear electron diffraction patterns into the corresponding quantitative structure factor images. FCU-Net was trained using over 200,000 unique simulated dynamical diffraction patterns from different combinations of crystal structures, orientations, thicknesses, and microscope parameters, which are augmented with experimental artifacts. We evaluated FCU-Net against simulated and experimental datasets, where it substantially outperforms conventional analysis methods. Our code, models, and training library are open-source and may be adapted to different diffraction measurement problems.
36 MATERIALS SCIENCE↗
Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications
Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
The exit-wave power-cepstrum transform for scanning nanobeam electron diffraction: robust strain mapping at subnanometer resolution and subpicometer precision
Scanning nanobeam electron diffraction (NBED) with fast pixelated detectors is a valuable technique for rapid, spatially resolved mapping of lattice structure over a wide range of length scales. However, intensity variations caused by dynamical diffraction and sample mistilts can hinder the measurement of diffracted disk centers as necessary for quantification. Robust data processing techniques are needed to provide accurate and precise measurements for complex samples and non-ideal conditions. Here we present an approach to address these challenges using a transform, called the exit wave power cepstrum (EWPC), inspired by cepstral analysis in audio signal processing. The EWPC transforms NBED patterns into real-space patterns with sharp peaks corresponding to inter-atomic spacings. We describe a simple analytical model for interpretation of these patterns that cleanly decouples lattice information from the intensity variations in NBED patterns caused by tilt and thickness. With tracking the inter-atomic spacing peaks in EWPC patterns, strain mapping is demonstrated for two practical applications: mapping of ferroelectric domains in epitaxially strained PbTiO 3 films and mapping of strain profiles in arbitrarily oriented core-shell Pt-Co nanoparticle fuel-cell catalysts. The EWPC transform enables lattice structure measurement at sub-pm precision and sub-nm resolution that is robust to small sample mistilts and random orientations.
42 ENGINEERING↗
Shock compression experiments using the DiPOLE 100-X laser on the high energy density instrument at the European x-ray free electron laser: Quantitative structural analysis of liquid Sn
X-ray free electron laser (XFEL) sources coupled to high-power laser systems offer an avenue to study the structural dynamics of materials at extreme pressures and temperatures. The recent commissioning of the DiPOLE 100-X laser on the high energy density (HED) instrument at the European XFEL represents the state-of-the-art in combining x-ray diffraction with laser compression, allowing for compressed materials to be probed in unprecedented detail. Here, we report quantitative structural measurements of molten Sn compressed to 85(5) GPa and ~3500 K. The capabilities of the HED instrument enable liquid density measurements with an uncertainty of ~1% at conditions which are extremely challenging to reach via static compression methods. We discuss best practices for conducting liquid diffraction dynamic compression experiments and the necessary intensity corrections which allow for accurate quantitative analysis. We also provide a polyimide ablation pressure vs input laser energy for the DiPOLE 100-X drive laser which will serve future users of the HED instrument.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Imaging and structure analysis of ferroelectric domains, domain walls, and vortices by scanning electron diffraction
Direct electron detectors in scanning transmission electron microscopy give unprecedented possibilities for structure analysis at the nanoscale. In electronic and quantum materials, this new capability gives access to, for example, emergent chiral structures and symmetry-breaking distortions that underpin functional properties. Quantifying nanoscale structural features with statistical significance, however, is complicated by the subtleties of dynamic diffraction and coexisting contrast mechanisms, which often results in a low signal-to-noise ratio and the superposition of multiple signals that are challenging to deconvolute. Here we apply scanning electron diffraction to explore local polar distortions in the uniaxial ferroelectric Er(Mn,Ti)O 3 . Using a custom-designed convolutional autoencoder with bespoke regularization, we demonstrate that subtle variations in the scattering signatures of ferroelectric domains, domain walls, and vortex textures can readily be disentangled with statistical significance and separated from extrinsic contributions due to, e.g., variations in specimen thickness or bending. The work demonstrates a pathway to quantitatively measure symmetry-breaking distortions across large areas, mapping structural changes at interfaces and topological structures with nanoscale spatial resolution.
36 MATERIALS SCIENCE↗
Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction
Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Evaluation of a fiber-coupled x-ray diffraction detector for dynamic compression experiments
The long-term x-ray diffraction (XRD) detector scheme compatible with Z-containment experiments will involve conversion of the diffracted x-rays to optical light, which will be transported away from the Z-Dynamic Materials Properties (DMP) load and detected on a fast-gated camera. In this so-called DIffraction SCintillator Optic (DISCO) scheme , the scintillator is coupled to a long, coherent imaging fiber bundle using a custom lens system with high numerical aperture. In addition, the DISCO diagnostic incorporates time-gating to allow measurement only during the short time window of the x-ray pulse in which XRD occurs, thereby significantly reducing unwanted background generated by the Z-DMP load. Dynamic compression experiments were performed at the Chama target chamber to evaluate the DISCO diagnostic . Specifically, a Zr sample was laser-shocked with the Chaco laser while the Z-Beamlet (ZBL) laser was used to generate x-rays, which enabled time-gated 6.7-keV XRD patterns from the compressed Zr sample to be obtained.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Hydrodynamic Analysis of a Suspended Cylinder Under Regular Wave Loading Based on Computational Fluid Dynamics
An investigation into the computation of hydrodynamic loads on a suspended cylinder in regular waves is presented. The primary goal was to perform a three-way validation of the loads between experimental measurements and simulations from two computational methods. Experimental measurements of the longitudinal in-line force on a cylinder suspended at a fixed position were available from the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project, Phase Ia. These measurements were compared to computational fluid dynamics (CFD) simulations based on the solution of Reynolds-averaged Navier-Stokes (RANS) equations, as implemented in STAR-CCM+. The study encompassed a sensitivity analysis of the loads computed in STAR-CCM+ based on wave modeling, boundary conditions, turbulence modeling, and spatial and temporal discretization. The analysis was supplemented by results generated with the offshore wind turbine engineering software OpenFAST, based on a hybrid combination of second-order potential flow and viscous drag from Morison's equation. The focus of the investigation was on the assessment of the accuracy of the computation of first- and higher-order hydrodynamic loads. Substantial differences were observed in the numerical prediction of the second and third harmonic force contribution. Local flow field analysis with CFD was applied to study the physics of wave run-up and diffraction dynamics to identify the causes.
16 TIDAL AND WAVE POWER↗
Hydrodynamic Analysis of a Suspended Cylinder Under Regular Wave Loading Based on Computational Fluid Dynamics: Preprint
An investigation into the computation of hydrodynamic loads on a suspended cylinder in regular waves is presented. The primary goal was to perform a three-way-validation of the loads between experimental measurements and simulations from two computational methods. Experimental measurements of the longitudinal inline force on a cylinder suspended at a fixed po- sition were available from the Offshore Code Comparison Col- laboration, Continued, with Correlation (OC5) project, Phase Ia. These measurements were compared to Computational Fluid Dynamics (CFD) simulations based on the solution of Reynolds- averaged Navier-Stokes (RANS) equations, as implemented in STAR-CCM plus. The study encompassed a sensitivity analysis of the loads computed in STAR-CCM plus based on wave modeling, boundary conditions, turbulence modeling, and spatial and tem- poral discretization. The analysis was supplemented by results generated with the offshore wind turbine engineering software OpenFAST, based on a hybrid combination of second-order po- tential flow and viscous drag fromMorison's equation. The focus of the investigation was on the assessment of the accuracy of the computation of first- and higher-order hydrodynamic loads. Sub- stantial differences were observed in the numerical prediction of the second and third harmonic force contribution. Local flow field analysis with CFD was applied to study the physics of wave run-up and diffraction dynamics to identify the causes.
16 TIDAL AND WAVE POWER↗
Extending the Takagi-Taupin equations for x-ray nanobeam Bragg coherent diffraction
We present an approach for simulating x-ray nanobeam Bragg coherent diffraction patterns based on the Takagi-Taupin equations. Compared to conventional methods, the current approach can be universally applied to any weakly strained system including semi-infinite crystals that diffract dynamically. It addresses issues such as the curved wave front and redivergence of the focused incident beam. In conclusion, we show excellent agreement with experimental data for a strained La 0.7 Sr 0.3 MnO 3 thin film on a SrTiO 3 substrate and a path to extracting physical information using automatic differentiation.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗