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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

In situ coherent x-ray scattering reveals polycrystalline structure and discrete annealing events in strongly coupled nanocrystal superlattices

Solution-phase bottom up self-assembly of nanocrystals into superstructures such as ordered superlattices is an attractive strategy to generate functional materials of increasing complexity, including very recent advances that incorporate strong interparticle electronic coupling. While the self-assembly kinetics in these systems have been elucidated and related to the product characteristics, the weak interparticle bonding interactions suggest the superstructures formed could continue to order within the solution long after the primary nucleation and growth have occurred, even though the mechanism of annealing remains to be elucidated. Here, we use a combination of Bragg coherent diffractive imaging and x-ray photon correlation spectroscopy to create real-space maps of supercrystalline order along with a real-time view of the strain fluctuations in aging strongly coupled nanocrystal superlattices while they remain suspended and immobilized in solution. By combining the results, we deduce that the self-assembled superstructures are polycrystalline, initially comprising multiple nucleation sites, and that shear avalanches at grain boundaries continue to increase crystallinity long after growth has substantially slowed. This multimodal approach should be generalizable to characterize a breadth of materials in their native chemical environments, thus extending the reach of high-resolution coherent x-ray characterization to the benefit of a much wider range of physical systems. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗
DOE OSTI2024

Synchrotron-based Characterization Techniques for Radiation Detection Materials and Devices: An Overview

High-performance room-temperature radiation detectors (high energy resolution for spectrometers, high spatial resolution for imaging devices, and low defect-density for high flux applications) are needed for photon energies (>20 keV) that are not well suited for silicon detectors. Applications for such radiation detectors include nonproliferation, synchrotron, medical, astrophysics, and homeland security. Material- and device- characterization to understand and solve the limiting factors of radiation detection materials and devices is a core element of a radiation detector development R&D program. This presentation will give an overview on the two main synchrotron-based characterization techniques that have been employed by the authors in the last ~20 years: (1) White Beam X-ray Diffraction Topography and (2) Micron-scale detector mapping. A perfect (one domain) crystal (radiation detection material) is a requirement to achieve a highperformance radiation detector. White Beam X-ray Diffraction Topography (WBXDT) allows the rapid screening of the crystallinity of the detector material. With WBXDT we can quickly screen CZT and other crystals to make sure they have only one domain, and to see the presence of extended defects and strain fields.

Camarda, Giuseppe S.↗
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 OSTI2024

Helium-electrospray improves sample delivery in X-ray single-particle imaging experiments

Abstract Imaging the structure and observing the dynamics of isolated proteins using single-particle X-ray diffractive imaging (SPI) is one of the potential applications of X-ray free-electron lasers (XFELs). Currently, SPI experiments on isolated proteins are limited by three factors: low signal strength, limited data and high background from gas scattering. The last two factors are largely due to the shortcomings of the aerosol sample delivery methods in use. Here we present our modified electrospray ionization (ESI) source, which we dubbed helium-ESI (He-ESI). With it, we increased particle delivery into the interaction region by a factor of 10, for 26 nm-sized biological particles, and decreased the gas load in the interaction chamber corresponding to an 80% reduction in gas scattering when compared to the original ESI. These improvements have the potential to significantly increase the quality and quantity of SPI diffraction patterns in future experiments using He-ESI, resulting in higher-resolution structures.

Science & Technology - Other Topics↗
DOE OSTI2024

Observation of high-pressure polymorphs in bulk silicon formed at relativistic laser intensities

Silicon polymorphs with exotic electronic and optical properties have recently attracted significant attention due to their wide range of useful band gap characteristics. They are typically formed by static high-pressure techniques, which limits the crystal structures that can be made. This constitutes a major obstacle to study these polymorphs and their incorporation into existing technology. Approaches have attempted to address this shortcoming through using dynamic conditions and chemical precursor materials. Here, we report on an approach to create unusual crystal structures deep in the bulk of a silicon crystal by irradiating it with a laser pulse at ultrarelativistic intensity of up to 7.5 × 10 19 W/ c m 2 . Laser-generated electrons with MeV energy swiftly penetrate the target with speed close to the speed of light and deposit their energy into a large volume across the whole thickness of the sample. The relativistic electron current creates, via branching propagation and ionization, high-energy-density conditions for thermodynamically nonequilibrium phase transformation paths into new crystal polymorphs. X-ray microdiffraction and synchrotron x-ray diffraction analyses indicate, along with conventional dc-Si, the presence of exotic silicon structures in the bulk of the laser intact target volume. These structures are identified as body-centered bc8-Si, rhombohedral r8-Si, hexagonal-diamond hd-Si, and the tetragonal Si-VIII, all phases of Si that have previously been made through static techniques. Additionally, simple-tetragonal st12-Si and body-centered tetragonal bt8-Si were observed along with signatures of not yet identified diffraction spots. Both st12-Si and bt8-Si have only been observed in ultrafast laser microexplosion conditions at much lower laser intensity ∼ 10 14 W/ c m 2 and within a micron-thin surface layer. The findings here are supported by direct observation of nanoparticles with high-resolution transmission electron microscopy and corresponding fast Fourier transform analysis of their interatomic distances. The presented analyses of absorbed laser energy, generation of the MeV electron current, and deposition of energy across the whole target thickness provide a solid basis for drawing the conclusion that the observed silicon polymorphs were produced because of laser-generated high-energy electrons fast-penetrating deeply into the bulk of silicon. In contrast to solid-solid transformations, the plasma-solid transitions offer a paradigm for the creation of exotic, high-energy density materials inside the bulk of the sample by using laser pulses at relativistic intensities. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Data-driven discovery of dynamics from time-resolved coherent scattering

Coherent X-ray scattering (CXS) techniques are capable of interrogating dynamics of nano- to mesoscale materials systems at time scales spanning several orders of magnitude. However, obtaining accurate theoretical descriptions of complex dynamics is often limited by one or more factors—the ability to visualize dynamics in real space, computational cost of high-fidelity simulations, and effectiveness of approximate or phenomenological models. In this work, we develop a data-driven framework to uncover mechanistic models of dynamics directly from time-resolved CXS measurements without solving the phase reconstruction problem for the entire time series of diffraction patterns. Our approach uses neural differential equations to parameterize unknown real-space dynamics and implements a computational scattering forward model to relate real-space predictions to reciprocal-space observations. This method is shown to recover the dynamics of several computational model systems under various simulated conditions of measurement resolution and noise. Moreover, the trained model enables estimation of long-term dynamics well beyond the maximum observation time, which can be used to inform and refine experimental parameters in practice. Finally, we demonstrate an experimental proof-of-concept by applying our framework to recover the probe trajectory from a ptychographic scan. Our proposed framework bridges the wide existing gap between approximate models and complex data.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Simultaneous compression of NaCl, Au, and ruby: toward mutually consistent pressure scales

Here, we evaluate pressure consistency of equations of state (EOS) for NaCl and Au at 300 K. The simultaneous measurements of unit-cell volumes (V) with ruby R1 line shifts (Δλ) in a helium (He) loaded diamond cell effectively remove potential systematic errors. Compression and decompression data were automatically collected at 1 sec interval, yielding a dense dataset with >8,000 (V, Δλ) pairs each for NaCl and Au. Solidification of He has noticeable effects on both V and Delta lambda (hence P). Only data up to similar to 14 GPa, or 6000 (V, P) pairs, can be considered hydrostatic within the resolution. The P-V data are fitted to the Rydberg-Vinet and the 3 rd order Birch-Murnaghan EOS. Predicted pressures of these EOSs agree with those given by the Ruby2020 ruby scale to within +/- 0.05 GPa. Overall, pressures predicted by the Rydberg-Vinet EOS are in better agreement with the average of commonly used NaCl and Au pressure scales.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Multiple magnetic interactions and large inverse magnetocaloric effect in TbSi and TbSi 0.6 Ge 0.4

We present a comprehensive investigation of the electronic structure, magnetization, specific heat, and crystallography of TbSi (FeB structure type) and TbSi 0.6 ⁢Ge 0.4 (CrB structure type) compounds. Both TbSi and TbSi 0.6 ⁢Ge 0.4 exhibit two antiferromagnetic (AFM) transitions at T N⁢1 ≈ 58 and 57 K, and T N⁢2 ≈ 36 and 44 K, respectively, along with an onset of weak metamagneticlike transition around 6 T between T N⁢1 and T N⁢2 . High-resolution specific heat (C P ) measurements show the second- and first-order nature of the magnetic transition at T N⁢1 and T N⁢2 , respectively, for both samples. However, in the case of TbSi, the low-temperature (LT) AFM to high-temperature (HT) AFM transition takes place via an additional AFM phase at the intermediate temperature (IT), where both LT to IT AFM and IT to HT AFM phase transitions exhibit a first-order nature. Both TbSi and TbSi 0.6 ⁢Ge 0.4 manifest significant magnetic entropy changes (Δ⁢S M ) of 9.6 and 11.6 J/kg-K, respectively, for Δ⁢μ 0 ⁢H=7 T, at T N⁢2 . The HT AFM phase of TbSi 0.6 ⁢Ge 0.4 is found to be more susceptible to the external magnetic field, causing a significant broadening in the peaks of Δ⁢S M curves at higher magnetic fields. Temperature- and field-dependent specific-heat data have been utilized to construct the complex HT phase diagram of these compounds. As a result, temperature-dependent x-ray diffraction measurements demonstrate substantial magnetostriction and anisotropic thermal expansion of the unit cell in both samples.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Structural studies of intrinsically disordered MLL -fusion protein AF9 in complex with peptidomimetic inhibitors

AF9 (MLLT3) and its paralog ENL(MLLT1) are members of the YEATS family of proteins with important role in transcriptional and epigenetic regulatory complexes. These proteins are two common MLL fusion partners in MLL -rearranged leukemias. The oncofusion proteins MLL-AF9/ENL recruit multiple binding partners, including the histone methyltransferase DOT1L, leading to aberrant transcriptional activation and enhancing the expression of a characteristic set of genes that drive leukemogenesis. The interaction between AF9 and DOT1L is mediated by an intrinsically disordered C-terminal ANC1 homology domain (AHD) in AF9, which undergoes folding upon binding of DOT1L and other partner proteins. We have recently reported peptidomimetics that disrupt the recruitment of DOT1L by AF9 and ENL, providing a proof-of-concept for targeting AHD and assessing its druggability. Intrinsically disordered proteins, such as AF9 AHD, are difficult to study and characterize experimentally on a structural level. In this study, we present a successful protein engineering strategy to facilitate structural investigation of the intrinsically disordered AF9 AHD domain in complex with peptidomimetic inhibitors by using maltose binding protein (MBP) as a crystallization chaperone connected with linkers of varying flexibility and length. The strategic incorporation of disulfide bonds provided diffraction-quality crystals of the two disulfide-bridged MBP–AF9 AHD fusion proteins in complex with the peptidomimetics. These successfully determined first series of 2.1–2.6 Å crystal complex structures provide high-resolution insights into the interactions between AHD and its inhibitors, shedding light on the role of AHD in recruiting various binding partner proteins. We show that the overall complex structures closely resemble the reported NMR structure of AF9 AHD/DOT1L with notable difference in the conformation of the β-hairpin region, stabilized through conserved hydrogen bonds network. These first series of AF9 AHD/peptidomimetics complex structures are providing insights of the protein–inhibitor interactions and will facilitate further development of novel inhibitors targeting the AF9/ENL AHD domain.

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

Dynamic compression effects of H 2 ⁡O in a dynamic diamond anvil cell: Origin of metastable ice VII and its crystal growth kinetics

We report on the structural verification of metastable ice VII solidifying in the phase space of ice VI at 1.80 GPa at room temperature. Using time-resolved (TR) x-ray diffraction and TR ruby luminescence paired with high-speed microphotography utilizing a dynamic diamond anvil cell, an initial compression rate range from 0.12 to 95.84 GPa/s was explored. The solidification pressure of metastable ice VII has a potential sigmoidal dependence upon compression rate with a turnover compression rate of ∼80 GPa/s. The preferred crystallization of ice VII in the stability field of ice VI is due to the increased nucleation rate of ice VII over ice VI at 1.77 GPa that is driven by the surface energy difference between the liquid and solid phases along with the change in Gibbs free energy of solidification. The dynamic pressure-volume–compression behaviors of ice phases (VI and VII) show a lattice stiffening in both phases, especially during the compression loading. It is also found that the compression rate greatly affects the solid-solid phase transition between ice VI and VII but does not affect the liquid-solid transition between water and ice VI as much. Lastly, a third phase transition was found to occur after metastable ice VII transforms into high-density amorphous (HDA) ice, which could be a disordered hydrogen-bonded network configuration of ice VII forming out of HDA ice facilitated by the decoupling of the oxygen movement and reorientation of the H 2⁡ O molecule. These results demonstrate the complexity of a seemingly simple molecule H 2⁡ O, how it can readily change its static properties with the modification of (de)compression rate, and highlight the need to use multiple TR structural and spectroscopic probes at higher time resolutions to realize the most comprehensive understanding.

Chemical bonding↗
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 OSTI2024

Scaling and merging time-resolved pink-beam diffraction with variational inference

Time-resolved x-ray crystallography (TR-X) at synchrotrons and free electron lasers is a promising technique for recording dynamics of molecules at atomic resolution. While experimental methods for TR-X have proliferated and matured, data analysis is often difficult. Extracting small, time-dependent changes in signal is frequently a bottleneck for practitioners. Recent work demonstrated this challenge can be addressed when merging redundant observations by a statistical technique known as variational inference (VI). However, the variational approach to time-resolved data analysis requires identification of successful hyperparameters in order to optimally extract signal. In this case study, we present a successful application of VI to time-resolved changes in an enzyme, DJ-1, upon mixing with a substrate molecule, methylglyoxal. We present a strategy to extract high signal-to-noise changes in electron density from these data. Furthermore, we conduct an ablation study, in which we systematically remove one hyperparameter at a time to demonstrate the impact of each hyperparameter choice on the success of our model. We expect this case study will serve as a practical example for how others may deploy VI in order to analyze their time-resolved diffraction data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Complex Structure of Molten FLiBe (2 Li F – Be F 2 ) Examined by Experimental Neutron Scattering, X-Ray Scattering, and Deep-Neural-Network Based Molecular Dynamics

The use of molten salts as coolants, fuels, and tritium breeding blankets in the next generation of fission and fusion nuclear reactors benefits from furthering the characterization of the molecular structure of molten halide salts, paving the way to predictive capability of the chemical and thermophysical properties of molten salts. Due to its neutronic, chemical, and thermochemical properties, 2 Li F - Be F 2 is a candidate molten salt for several fusion- and fission-reactor designs. We performed neutron and x-ray total-scattering measurements to determine the atomic structure of liquid 2 Li F - Be F 2 . We also performed and neural-network molecular-dynamics simulations to predict the structure obtained by neutron- and x-ray-diffraction experiments. The use of machine learning provides improvements to the efficiency in predicting the structure at a longer length scales than is achievable with simulations at significantly lower computational expense while retaining near accuracy. We found that the NNMD simulations accurately predicted the Be F 4 2 − oligomer formations seen in the experimental first-structure-factor peak. Our combination of high-resolution measurements with large-scale molecular dynamics provided an avenue to explore and experimentally verify the intermediate-range ordering beyond the first-nearest neighbor that has posed too many experimental and computational challenges in previous works. With a deeper understanding of the salt structure and ion ordering, the evolution of salt chemistry over the lifetime of a reactor can be better predicted, which is crucial to the licensing and operation of advanced fission and fusion reactors that employ molten salts. To this end, this work will serve as a reference for future studies of salt structure and macroscopic properties with and without the addition of solutes. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Orientational analysis of atomic pair correlations in nanocrystalline indium oxide thin films

The application of grazing-incidence total X-ray scattering (GITXS) for pair distribution function (PDF) analysis using >50 keV X-rays from synchrotron light sources has created new opportunities for structural characterization of supported thin films with high resolution. Compared with grazing-incidence wide-angle X-ray scattering, which is only useful for highly ordered materials, GITXS/PDFs expand such analysis to largely disordered or nanostructured materials by examining the atomic pair correlations dependent on the direction relative to the surface of the supporting substrate. A characterization of nanocrystalline In 2 O 3 -derived thin films is presented here with in-plane-isotropic and out-of-plane-anisotropic orientational ordering of the atomic structure, each synthesized using different techniques. The atomic orientations of such films are known to vary based on the synthetic conditions. Here, an azimuthal orientational analysis of these films using GITXS with a single incident angle is shown to resolve the markedly different orientations of the atomic structures with respect to the planar support and the different degrees of long-range order, and hence, the terminal surface chemistries. It is anticipated that orientational analysis of GITXS/PDF data will offer opportunities to extend structural analyses of thin films by providing a means to qualitatively determine the major atomic orientation within nanocrystalline and, eventually, non-crystalline films.

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

High-Resolution Full-Field Structural Microscopy of the Voltage-Induced Filament Formation in VO 2 -Based Neuromorphic Devices

In order to make neuromorphic functions in memristive devices more efficient, information about the structural properties of filament formation at the micro- and mesoscopic scales is necessary. Despite extensive research on VO 2 , a key material due to its filament formation, local operando structural measurements remain challenging and often involve destructive specimen preparation and long rastering times, greatly limiting the scope of experimental studies. Utilizing dark-field X-ray microscopy (DFXM), a fullfield imaging modality, structural signatures of the filament formation process operando are revealed in VO 2 devices. DFXM experiments illustrate that rutile filaments contain isolated monoclinic clusters, indicating structural nonuniformity interior to the filament. The formation of the rutile phase beneath device electrodes was shown to precede filament development, followed by the formation of filament paths guided by nucleation sites within the device. Finally, a medium-term (<30 min) memory mechanism is observed in VO 2 , mediated by sites within the device gap that tend to switch at significantly lower voltages after electrical cycling, a tendency that persists through a brief thermal reset. High spatial resolution, large field-of-view, structure selectivity, and fast signal acquisition of DFXM provided insight into structural features of the filamentary channel and surrounding regions during voltage cycling.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
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↗
DOE OSTI2024

In situ Synchrotron X‐ray Metrology Boosted by Automated Data Analysis for Real‐time Monitoring of Cathode Calcination

Abstract Synchrotron X‐ray‐based in situ metrology is advantageous for monitoring the synthesis of battery materials, offering high throughput, high spatial and temporal resolution, and chemical sensitivity. However, the rapid generation of massive data poses a challenge to on‐site, on‐the‐fly analysis needed for real‐time process monitoring. Here, a weighted lagged cross‐correlation (WLCC) similarity approach is presented for automated data analysis, which merges with in situ synchrotron X‐ray diffraction metrology to monitor the calcination process of the archetypal nickel‐based cathode, LiNiO 2 . The WLCC approach, incorporating variables that account for peak shifts and width changes associated with structural transformations, enables rapid extraction of phase progression within 10 seconds from tens of diffraction patterns. Details are captured, from initial precursors to intermediates and the final layered LiNiO 2 , providing information for agile on‐site adjustments during experiments and complementing post hoc diffraction analysis by offering insights into early‐stage phase nucleation and growth. Expanding this data‐powered platform paves the way for real time calcination process monitoring and control, which is pivotal to quality control in battery cathode manufacturing.

36 MATERIALS SCIENCE↗