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Results for “High resolution X-ray diffraction”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

High-resolution bandpass x-ray imaging with crystal reflectors: Overcoming geometric aberrations

The imaging problem of a specular reflector is revisited. Retaining terms through the second order in the reflector surface expansion, we derive the form of the aberration-limiting aperture for arbitrary magnification, assuming no bandwidth limitations. A permissible relative aperture size of the reflector is limited by a set relative aberration tolerance and scales with the tangent of the central glancing angle of incidence. These limiting aberrations become practically insignificant near backscattering. The results extend to x-ray diffracting crystals in symmetric Bragg geometry shaped as an ellipsoid of revolution. This geometry permits polychromatic imaging for hard x-rays over a bandwidth defined by the accepted range of Bragg angles, thereby suppressing aberrations of higher orders. We assess ellipsoidal crystal imagers using ray tracing simulations for two high-magnification designs with Bragg angles far from and close to backscattering. Finally, in both cases, the ellipsoidal crystals produce images of higher quality compared to those formed by equivalent toroidal crystal imagers.

Bragg reflection↗
DOE OSTI2026

Visualization of Thermal and Strain Dynamics in X-ray Optics by Time-Resolved Rocking Curve Imaging

The absorption of intense X-ray pulses from free-electron lasers by X-ray crystal optics triggers rapid thermal and mechanical responses, including lattice compression, expan- sion, and strain-wave propagation, which dynamically modify diffraction conditions and wavefront properties. These effects pose significant challenges for next-generation high- repetition-rate X-ray sources, particularly for crystal monochromators used in XFEL beam- lines and self-seeding. Here, we demonstrate time-resolved rocking curve imaging (TrRCI) of X-ray Bragg optics with high spatial resolution (6.4 μm) and sub-1-μrad angular resolu- tion, enabling direct visualization of lattice dynamics from nanoseconds to microseconds. By combining a high-flux beamline at SPring-8, a scintillator-coupled sCMOS detector, and a synchronized femtosecond laser system, we capture lattice dynamics induced by tran- sient laser heating with a strain sensitivity on the order of 10−6 . Our results reveal transient lattice deformation and the propagation of laser-induced strain waves over millimeter-scale distances. This approach provides experimental benchmarks for understanding heat-load effects in high-repetition-rate X-ray optics.

Source record↗
DOE OSTI2026

An Atom-Precise Approach to Damp First-Order Phase Transitions and Its Implications for Neuromorphic Signal Processing

Neuromorphic computing inspired by mammalian intelligence aims to emulate the nonlinear dynamics of biological neurons and synapses to achieve fast, low-energy, and highly efficient information processing. Brain-inspired computing relies on the design and discovery of materials exhibiting nonlinear current–voltage profiles, frequently underpinned by electronic state transitions, to achieve spiking neurons and dynamically tunable synapses. A signature challenge in the design of artificial neurons is controlling the steepness of first-order transitions in active elements, as abrupt transitions are at risk of driving unstable voltage and temperature oscillations, which result in catastrophic device failure. A critical knowledge gap is the lack of structure–function correlations mapping the composition and atomistic structure of crystalline solids to nonlinear dynamical response characteristics. Here, we address the key question of how modification of atomistic structure correlates with alteration of neuron-like functionality. Constructing oscillator circuits from millimeter-scale single crystals enables high-resolution atomic structure solutions, which we use to demonstrate that the selective positioning of Pb cations modifies charge ordering along a one-dimensional CuxV2O5 framework even at low insertion stoichiometries, thereby providing an atom-precise design parameter for damping first-order transitions. We use temperature-variant X-ray diffraction and X-ray spectroscopy to elucidate the suppression of Cu-ion shuttling based on the precise positioning of Pb ions in seven-coordinated tunnel interstitial sites as the mechanistic basis for transition broadening, thus bridging a critical gap between statistical mechanics and quantum chemical descriptions of phase transitions. Such mechanistic understanding thus paves the way to site-selective modification strategies for modulating the sharpness of first-order transitions, with an exemplary demonstration here in tuning neuronal signal processing.

Crystal structure↗
DOE OSTI2026

Nonlinear reversal of photoexcitation on the attosecond time scale improves ultrafast X-ray diffraction images

The complex refractive index of a material governs its light-matter interactions, with intense light fields enabling tailored nonlinear optical responses. In the X-ray regime, rapid photoionization limits the potential of nonlinear techniques by inducing irreversible electronic damage. Here we demonstrate that intense, sub-femtosecond X-ray pulses, shorter than typical Auger decay times, can partially reverse photoexcitation via stimulated emission near atomic resonances. By analyzing thousands of coherent diffraction patterns and ion spectra from neon nanoparticles exposed to sub-fs and 15-fs pulses, we observe enhanced X-ray diffraction alongside reduced energy absorption for sub-fs pulses. Theoretical modeling attributes this to dynamics akin to Rabi flopping that prolong the lifetime of resonant states and suppress electronic bleaching. These findings suggest that ultrashort, intense X-ray pulses enable active control of X-ray refractive index and damage pathways, opening avenues for improved high-resolution imaging and nonlinear spectroscopy in complex nanoscale systems.

Ulmer, Anatoli [Universität Hamburg (Germany)] (OR↗
DOE OSTI2026

Quantifying the Impact of Metal Population Distribution in MFI-Supported Mo Catalysts for Methane Dehydroaromatization

Precise evaluation of intrinsic kinetic behavior in Mo/MFI catalysts for methane dehydroaromatization (MDA) is confounded by variations in Mo dispersion and speciation, which are influenced by metal loading and zeolite acidity. This work advances the utility of H 2 -temperature programmed reduction (H 2 -TPR) for characterizing Mo/MFI catalysts by enabling quantitative comparison of MoO x populations distinguished by reduction behavior and linked to initial catalytic performance. A comprehensive H 2 reduction pathway is established through systematic H 2 - TPR studies varying catalyst composition (1–10 wt % Mo, Si/Al = 15, 40, ∞), supplemented by UV-Raman spectroscopy, X-ray powder diffraction, N 2 physisorption, NH 3 -TPD, and advanced spectroscopic analysis (in situ XAS with principal component analysis/multivariate curve resolution—alternating least squares). Two low-temperature H 2 -TPR regions capture distinct Mo populations undergoing initial Mo(VI)→Mo(IV) reduction: a lower-temperature population (Mo-RI) associated primarily with highly dispersed, anchored MoO x species expected to predominantly reside within MFI channels, and a higher-temperature population (Mo-RII) corresponding to a broader set of MoO x species that becomes increasingly bulk-like/extrazeolitic at higher Mo loading. Quantification of these populations provides practical, kinetically relevant descriptors for comparing initial MDA rates across catalysts with varying Mo loading, Si/Al ratio, and MoO x heterogeneity. Application of lower-temperature Mo-RI estimates to kinetic measurements reveals a minimum threshold of ∼0.12 × 10 –3 mol Mo-RI/g cat , above which initial forward benzene rates normalized to this population converge despite differences in metal loading and zeolite Brønsted acidity. This threshold coincides with a transition toward a common C 2 -mediated benzene-forming regime, as indicated by approach-to-equilibrium analysis of methane-to-ethane, ethane-to-ethylene, and ethylene-to-benzene reaction steps. Above this threshold, normalized initial benzene rates are nearly invariant with increasing Mo-RII/Mo-RI population ratio, indicating that excess Mo-RII populations, including bulk-like/extrazeolitic MoO x domains present at higher loading, do not measurably suppress benzene formation associated with anchored and mostly channel-confined Mo population under the initial-rate conditions examined.

Mo/MFI↗
DOE OSTI2026

Crystallographic registry in epitaxial V3O5 thin films

Crystallographic orientation plays a central role in determining transport properties in correlated oxides with low-hysteresis metal–insulator transitions. Here, V3O5 thin films were grown on Al2O3 (0001) and their crystallographic registry was evaluated using x-ray diffraction and cross-sectional transmission electron microscopy. θ–2θ measurements show a single out-of-plane orientation defined by the (202) reflection. Azimuthal φ-scans of the V3O5 (310) reflection exhibit twelve discrete maxima over 360°, indicating a finite set of in-plane orientations imposed by the substrate symmetry. High-resolution TEM and fast Fourier transform analysis confirm crystallographic coherence at the film–substrate interface. The electrical conductivity exhibits a metal–insulator transition at TMIT ≈ 423 K with no measurable thermal hysteresis and a total change of ~1.6 orders of magnitude between 300 and 480 K. These results establish crystallographic registry in epitaxial V3O5 thin films and provide a structurally well-defined system for future studies of orientation-dependent transport.\r\nT

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electron Microscopy Approaches to Unraveling the Structure of Amorphous Materials

Determining atomic structures in crystalline materials—where atoms are arranged in rigid, periodic lattices—has been highly successful using probes such as electrons, X-rays, and neutrons. In contrast, amorphous materials, despite their ubiquity and technological importance, remain far more challenging to characterize with comparable accuracy and precision. This review highlights existing, emerging, and potential (scanning) transmission electron microscopy ((S)TEM) techniques for probing short- and medium-range order in amorphous materials. Approaches ranging from high-resolution (S)TEM imaging and selected electron diffraction pattern to four-dimensional STEM (4D-STEM) based pair distribution function, fluctuation electron microscopy, tomography, ptychography, and spectroscopic methods are discussed, emphasizing their ability to provide complementary insights across multiple length scales—from sub-angstrom local environments to nanometer-scale correlations. Here, we further explore the promise of multimodal and correlative strategies, as well as the growing role of machine learning and physics-informed AI in enabling real-time, quantitative interpretation of complex structural signatures. Together, these advances point toward a future where electron microscopy not only reveals the hidden order in amorphous systems but also establishes robust structure–property relationships, paving the way for materials innovation in disordered matter.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Unraveling the structure of molten salts: a review of high-energy x-ray diffraction (HEXRD) studies

High energy x-ray diffraction (HEXRD) has emerged as a pivotal technique for examining the structural properties of molten salts, which play vital roles in various high-temperature applications, such as energy storage, nuclear reactors, and metallurgy. This review provides a comprehensive analysis of recent progress in HEXRD studies of various molten salt systems, including molten halide salts, their mixtures, and salts with molecular anions, focusing on the insights into their atomic-scale arrangements. Additionally, we discuss methodological advancements that have improved the resolution and accuracy of HEXRD measurements, as well as recent developments in computational simulations, such as machine learning interatomic potentials, for interpreting results. This review aims to serve as a valuable resource for researchers in this field, offering a detailed overview of the progress of HEXRD studies of molten salts and suggesting pathways for further exploration.

Blockmon, Avery L. [Argonne National Laboratory (A↗
DOE OSTI2025

High-resolution neutron diffraction determination of noncollinear antiferromagnetic order in the honeycomb magnetoelectric Fe 4 ⁢Nb 2⁢ O 9

Magnetoelectric systems offer potential for device applications exploiting coupled states between electric and magnetic properties. Among magnetoelectric materials, Fe 4 ⁢Nb 2 ⁢O 9 has attracted special attention because of its pronounced dielectric signal at high magnetic transition temperatures. However, the magnetic ground state, which is essential information for understanding its unusual magnetoelectricity, remains unclarified. Here, we report a noncollinear magnetic ground state of Fe 4 ⁢Nb 2 ⁢O 9 . To examine the magnetoelectric effect associated with sequential magnetic and structural transitions upon cooling, we conducted combined x-ray diffraction, magnetic susceptibility, magnetization, dielectric constant, and magnetodielectric experiments. Powder neutron diffraction experiments revealed a series of magnetic Bragg peaks and clear splitting of peaks via structural transition. Magnetic Rietveld refinements, combined with group theory analysis, determined a noncollinear antiferromagnetic structure including a significant 𝑐-axis moment component at 1.5 K. This article provides insights into the understanding of its magnetoelectric properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Pattern-enhanced Resonant Soft X-ray Scattering for Operando monitoring of electrochemical solid-liquid interfaces

Unveiling interfaces at sub-nanometer scales is essential for advancing the understanding of complex chemical transformations. However, characterizing solid-liquid interfaces with high dimensional sensitivity and temporal resolution remains challenging, due to their dynamic nature and inaccessibility by conventional probes. Here we present an approach, Pattern-enhanced Resonant Soft X-ray Scattering, to overcome the challenges. Rooted in a “sample-as-optics” philosophy, this technique utilizes precisely engineered line-grating nanopatterns to modulate near-field X-ray illumination, coherently enhancing scattering signals from the line-gratings. We implement the method using Ni line-grating nanopatterns in electrochemical water oxidation. The periodic nanostructures serve as diffractive optical elements to reveal the Ni oxidation gradients and structural dynamics at the electrode-electrolyte interfaces. Finite-element simulations corroborate the observed trends by modeling variations in compositions and structures during electrocatalysis. Through integrating advanced sample design with coherent wave nature of soft X-rays, our approach opens accessible pathways to operando exploring chemical evolution and sub-nanometer dimensional variations simultaneously in electrochemical systems. This non-destructive method is efficient and element-specific, making it valuable for probing chemical and dimensional dynamics with appropriate modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Orbital-Selective Instabilities and Spin Fluctuations at the Verge of Superconductivity in Interlayer-Expanded Iron Selenide

Understanding electron correlation-driven instabilities and their coupling to structural phases is essential for deciphering multiorbital pairing in unconventional superconductors. We investigate Li x (C 5 H 5 N) y Fe 2 Se 2 (x ∼ 0.6; y ∼ 0.7−0.9), a tetragonal β-FeSe intercalate with a superconducting transition temperature (T c = 39 K) closely tied to an expanded Fe-layer spacing (∼11.4 Å). High-resolution synchrotron Xray diffraction and core-level absorption spectroscopy reveal subtle lattice distortions on cooling without a symmetry-breaking transition. Instead, the material exhibits negative thermal expansion (NTE) in the two-dimensional Fe network below T S ∼ 70 K, and stiffening of local Se−Fe−Se bond dynamics near T c . The spatially incoherent rearrangement of FeSe 4 tetrahedra and the site-local fluctuations, signal reduced electron correlations compared to those of parent β-FeSe (T c = 8 K). Complementary X-ray emission spectroscopy, a fast local probe of Fe 3d valence states, detects persistent local Fe spin moments below T S , unlike quenching in related systems. These findings indicate that decoupling of Fe planes leads to an electronically driven lattice instability. The latter emerges as NTE induced from weak, orbital-selective localization of in-plane Fe 3d states rather than conventional transverse vibrations. Governed by Hund’s coupling, this selectivity permits coexistence of local spin fluctuations with itinerant d-electrons critical for enhancing T c . These results suggest that intercalation-driven d-orbital differentiation moderates electron correlations, providing a pathway to optimize the superconductivity in low-dimensional quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Synchrotron resolved microscale mineralogy and elemental composition of individual plinthic and manganiferous nodules from agricultural soils

Iron and manganese oxides are strong sorbents and elemental scavengers in the environment that can form macroscopic nodules in soils. Despite their importance in the geochemical cycling of nutrients and contaminants, nodules are rarely characterized. When analyzed, they are often combined into bulk samples, obscuring individual characteristics. This study investigates the composition and mineralogy of individual plinthic and manganiferous nodules in soil from cropping systems in the Farming Systems Project in Beltsville, Maryland. Elemental composition indicates the accumulation of contaminants and nutrients, including copper in all nodules and high levels of phosphorus in select nodules. Sequential extractions determine that highly crystalline minerals comprise the nodules, locking away these nutrients and contaminants. Bulk X-ray diffraction (XRD) demonstrated distinct mineralogies in the plinthic and manganiferous nodules, with the former comprised of quartz, goethite, and kaolinite, and the latter consisting of quartz, Mn 2 O 3 , and hematite. Synchrotron and laboratory-based X-ray fluorescence (XRF) mapping gives critical insight into the elemental distribution within the nodules and elucidates spatial elemental associations, including the coupling of manganese and iron in the manganiferous nodules. XRF maps paired with µXRD provide microscale spatial resolution in mineralogy, which resolved several phases not apparent in bulk XRD, manganese’s association with goethite, and minerals indicative of redox transformations, including magnetite and maghemite. These novel results provide critical insight into the microscale mineralogy and individual elemental composition of plinthic and manganiferous nodules, as well as how they alter bulk soil geochemistry in ways largely unaccounted for in research on soil systems.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Anomalous lattice expansion of bcc Ta in helium-loaded diamond anvil cells

Anomalous lattice expansion of bcc Ta is observed in helium-loaded diamond anvil cell (DAC) experiments near 6 GPa and above 400 K, while co-loaded W, Mo, and Au exhibit normal thermal expansion. The Ta volume expansion increases with temperature, reaching ~14% near 650 K before plateauing, and is largely retained after recovery to ambient conditions. Time-resolved measurements at 500 K reveal progressive expansion over several hours, consistent with gradual, thermally activated He incorporation. The largely retained expansion during subsequent cooling and holding at 400 K indicates that the incorporated He is predominantly kinetically trapped. The data reveal two distinct regimes: below ~550 K, modest and spatially uniform expansion consistent with interstitial He trapping at isolated, randomly distributed vacancies; above ~550 K, He-vacancy cluster growth producing dramatically larger expansion, peak broadening, and a core–shell microstructure revealed by micron-resolution X-ray diffraction mapping. These results demonstrate that He is not always a passive pressure medium in DAC experiments and reveal a previously unrecognized regime of He-mediated lattice modification in Ta, complementing conventional ion-implantation studies relevant to nuclear and fusion structural materials.

Diamond anvil cell↗
DOE OSTI2026

In-Situ Visualization of a Growing Brittle Crack in Aluminum Oxynitride Using Synchrotron X-Rays and the Double-Cleavage Drilled Compression Geometry

Brittle fracture is difficult to study in situ due to the speed of a growing crack and the often-catastrophic nature of failure in brittle materials. As a result, the influence of microstructural considerations, such as orientation, grain boundary locations, and strain field, on the crack path remains poorly understood. Presented in this study is a method addressing this knowledge gap, which utilizes the double-cleavage drilled compression geometry to achieve quasi-stable fracture in aluminum oxynitride (AlON). Synchrotron X-ray micro-computed tomography is used to characterize the crack shape and length, while high-energy diffraction microscopy provides information on the strains, orientations, and shapes of grains in the microstructure surrounding the crack tip. During testing, the crack grew in discrete and irregular jumps while the fracture toughness falls within reported ranges. The crack in AlON is found to have no greater tendency to crack intergranularly as compared to transgranularly, and grains which are cracked transgranularly do not display a trend in orientation or stress when compared to those around which the crack followed a grain boundary. The high resolution of the crack path and microstructural data provides a path forward for modeling and understanding 3D brittle fracture.

Gorske, Sara F.↗
DOE OSTI2025

Magnetoelastic-coupling-assisted first-order antiferromagnetic transitions in the corrugated honeycomb-lattice compounds (Ca, Sr) ⁢Mn 2 ⁢ P 2

Understanding the origin of unconventional magnetic order is a central theme in the research field of functional quantum materials for spin-dependent applications. In general, a paramagnetic (PM) to antiferromagnetic (AFM) transition is of thermodynamically second order in nature in the absence of a magnetic field. In the magnetically frustrated corrugated-honeycomb lattice compounds (Ca, Sr) ⁢Mn 2 ⁢ P 2 , electrical resistivity 𝜌 measurements in the 𝑎⁢𝑏 plane are reported to exhibit sharp discontinuities at the respective PM to AFM ordering temperatures 𝑇 N = 69.5 and 53 K, respectively, signifying the unusual first-order nature of the AFM transition. To reveal the origin of such anomalous transitions, high-resolution linear thermal-expansion measurements are reported for both CaMn 2 ⁢P 2 and SrMn 2 ⁢ P 2 in the 𝑎⁢𝑏 plane and along the 𝑐 axis using capacitance dilatometry. The thermal expansion measurements show a sharp discontinuity in Δ⁢𝐿/𝐿 at 𝑇 N , yielding a diverging behavior in the thermal expansion coefficient 𝛼⁡(𝑇) associated with strong magnetoelastic coupling, driving the first-order AFM transition in CaMn 2 ⁢P 2 . However, this effect is weaker in SrMn 2 ⁢P 2 , consistent with the magnetic entropy changes 𝑆⁡(𝑇) obtained from the heat-capacity measurements. Temperature-dependent 𝑎⁢𝑏-plane x-ray diffraction measurements for CaMn 2 ⁢ P 2 near its 𝑇 N yield a volume thermal expansion coefficient consistent with literature data for other materials. The uniaxial pressure derivatives of 𝑇 N in the two compounds are found to be respectively opposite in sign, presumably due to the different magnetic structures.

Pakhira, Santanu [Maulana Azad National Institute ↗
DOE OSTI2026

Learning neural representations for X-ray ptychography reconstruction with unknown probes

X-ray ptychography provides exceptional nanoscale resolution and is widely applied in materials science, biology, and nanotechnology. However, its full potential is constrained by the critical challenge of accurately reconstructing images when the illuminating probe is unknown. Conventional iterative methods and deep learning approaches are often suboptimal, particularly under the low-signal conditions inherent to low-dose and high-speed experiments. These limitations compromise reconstruction fidelity and restrict the broader adoption of the technique. In this work, we introduce the Ptychographic Implicit Neural Representation (PtyINR), a self-supervised framework that simultaneously addresses the object- and probe-recovery problem. By parameterizing both as continuous neural representations, PtyINR performs end-to-end reconstruction directly from raw diffraction patterns without requiring any pre-characterization of the probe. Extensive evaluations demonstrate that PtyINR achieves superior reconstruction quality on both simulated and experimental data, with remarkable robustness under challenging low-signal conditions. Furthermore, PtyINR offers a generalizable, physics-informed framework for addressing probe-dependent inverse problems, making it applicable to a wide range of computational microscopy problems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Informed unsupervised machine learning analysis of dislocation microstructure from high-resolution differential aperture X-ray structural microscopy data

This study leverages high-resolution differential-aperture X-ray structural microscopy (DAXM) to probe the local dislocation structure in deformed 304L-stainless steel at small strain, by measuring the lattice rotation and deviatoric elastic strain with a sub-micron resolution. For a single grain in a polycrystalline specimen, the measured lattice rotation field over the measured volume exhibited a multimodal distribution while the deviatoric elastic strain showed a single-mode distribution. An unsupervised Cauchy mixture machine learning model was developed to resolve the multimodal distribution of the lattice rotation. By mapping the lattice rotation data associated with each Cauchy peak in the model back onto the measured volume, we identify contiguous regions of the crystal rotated near the average values corresponding to the peaks of the overall rotation distribution. These regions represent the grain subdivision in the microstructure. Finally, the dislocation density tensor was also computed and its norm was laid over the rotation field to detect the subgrain boundaries. This step provided a validation of the Cauchy mixture model for the analysis of the lattice rotation distribution. The current study highlights the integration of advanced X-ray microscopy techniques with data-driven analysis methods to uncover detailed microstructure scales in deformed crystals.

Machine learning; Lattice rotation; High-energy X-↗
DOE OSTI2025

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗