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This review article centers around structured liquids and their underlying mechanisms. The focus is on the chemistry, applications, characterization, reconfigurability, and future prospects of this class of soft materials.
Although cerium oxide (CeO 2 ) is widely used as a catalyst support, its limited defect sites and surface oxygen vacancy/mobility should be improved. The incorporation of zirconium (Zr) in the cerium (Ce) lattice is shown to increase the number of oxygen vacancies and improve catalytic activity. Using a fixed surface density (SD) of copper (∼2.3 Cu atoms per nm 2 ) as a surface species, the role of the support (Ce y Zr 1−y O 2 (y = 1.0, 0.9, 0.6, 0.5, and 0.0)) and defect site effects in the CO oxidation reaction was investigated. Spectroscopic (e.g., Raman, XRD, XPS) and microscopic (e.g., SEM-EDX, HR-TEM) characterization techniques were applied to evaluate the defect sites, crystallite size, lattice parameters, chemical composition, oxidation states of elements and microstructure of the catalysts. Here, the CO oxidation reaction with varied CO : O 2 ratios (1 : 5, 1 : 1, and 1 : 0.5 (stoichiometric)) was used as a model reaction to describe the relationship between the structure and the catalytic performance of each catalyst. Based on the characterization results of Ce y Zr 1−y O 2 materials, the addition of Zr causes physical and chemical changes to the overall material. The inclusion of Zr into the structure of CeO 2 decreased the overall lattice parameter of the catalyst and increased the number of defect sites. The prepared catalysts were able to reach complete CO conversion (∼100%) at low temperature conditions (<200 °C), each showing varied reaction activity. The difference in CO oxidation activity was then analyzed and related to the structure, wherein Cu loading, surface oxygen vacancies, reduction–oxidation ability, CuO x –support interaction and oxygen mobility in the catalyst were the crucial descriptors.
Nickel oxide nanocubes with increased (100) surface facet presence (NiO(100)) were synthesized through a molten salt synthesis procedure to probe their oxygen evolution reaction (OER) activity in order to investigate the relationship between the surface facet and OER performance. While altering the synthesis parameters to decrease NiO(100) particle sizes and agglomeration, a polycrystalline NiO nanoparticle system formed from using Li2O as a Lux-Flood base (labelled Li2O-MSS NiO, where MSS stands for molten salt synthesis). This novel synthesis was further elaborated and the obtained materials were also tested for OER activity. After thorough structural characterization to determine crystallinity, lattice spacings, and elemental distribution, their OER activity was compared versus high surface area NiO(111) nanosheets in a three-electrode rotating disk electrode (RDE) system. The activity trend of (111) > Li2O-MSS > (100) was observed. This decrease in activity of the nanocube and polycrystalline samples was explained by differences between theoretical and experimental conditions, differences in ink rheology and resulting catalyst layer properties, and significant agglomeration seen in the imaging of the sample. Methods for improving the OER activity of these samples are discussed in the conclusion of this study.
The lanthanum (La)-nickel (Ni)-aluminum (Al) hydrides (LANA: LaNi 5 − x Al x , x < 1.0) have been extensively studied for their high volumetric storage capacity and improved durability to maintain a single-phase CaCu5 structure through multiple absorption and desorption cycles. Pressure composition temperature (PCT) isotherms obtained for LANA have allowed for an understanding of the hydrogen sorption properties and the tunability of the PCT plateau region via doping. At the Savannah River Site, LaNi 4.25 Al 0.75 (LANA0.75) has been utilized as a hydrogen storage material in the tritium facilities for decades. However, the structure characterization of the LANA0.75 hydride by X-ray diffraction has not yet been reported. This study examines LANA0.75 loaded to different hydrogen-to-metal atom ratios to elucidate both the position of hydrogen sites in the lattice and the structure of a fully hydrided β phase.
Synchrotron x-ray spectroscopy was employed to determine the effects of nanostructuring on electronic band structure in V2O5, a promising cathode material and widely used catalyst. V2O5nanoparticle and bulk powders were characterized via P-XRD, electron microscopy, and diffuse reflectance ultraviolet/visible/near-infrared spectroscopy to confirm the optical bandgap. X-ray emission spectroscopy revealed the nanoparticle valence band O 2pstates to be upshifted relative to the bulk, while x-ray absorption spectroscopy and resonant inelastic x-ray scattering showed the lowest V 3dconduction band states to be static. Together, these changes (in conjunction with an increased density of unoccupied lower conduction band states) produce a shrunken bandgap in the V2O5nanoparticles that defies the Burstein-Moss effect. Changes in nanoparticle band structure are generally attributed to oxygen vacancy defects. While nanostructure bandgap reduction is in line with much previous computational work, it is unexpected from most previous experimental results. To our knowledge, this is the first synchrotron x-ray spectroscopy study of a shrunken bandgap achieved in pure V2O5nanoparticles.
Young’s modulus is an important parameter for characterizing the strength of, and wave propagation through, a given material. This study improves the estimation of Young’s modulus using the impulse excitation technique based on an experimental analysis of 19 borosilicate glass bars. Analysis of the frequency equations relating Young’s modulus to the out-of-plane and in-plane flexural resonant frequencies of rectangular prisms has been conducted for both the fundamental frequency and its overtones at higher orders of vibration. Furthermore, the Young’s moduli of three novaculite rocks with various porosities were then measured up to the seventh order of vibration to validate the optimum shear constant equation for estimating Young’s modulus. Young’s modulus was found to be nearly frequency independent for these rock samples.
This project, funded by the U.S. Department of Energy (DOE) – Office of Fossil Energy under Award Number DE-FE0032177, aimed to assess the feasibility of an integrated Laser-Induced Breakdown Spectroscopy (LIBS) system with advanced machine learning (ML) models for real-time characterization and potential control of hydrogen gasifiers running on waste materials as feedstocks. This was a multidisciplinary effort that encompassed the acquisition and standardized analysis of individual and blended feedstocks—comprising biomass, coal waste, and plastic waste, followed by the development of a dynamic LIBS bench system for material sample analysis and development of predictive ML models. Comprehensive laboratory testing enabled the creation of a robust elemental dataset that served as the foundation for ML model training. Techniques such as Random Forest, Gradient Boosting, Support Vector Regression, and Neural Networks were employed to predict key feedstock properties, including higher heating value (HHV), moisture content, thermal conductivity, and ash composition with high accuracy. The results were validated against experimental data and demonstrated strong potential for real-time application in gasifier control systems. The project concluded with a study on the integration of the LIBS+ML approach for gasifier control and a techno-economic analysis of the implementation of the approach into hydrogen (H 2 ) gasification systems. Dissemination of results was carried out at a DOE meeting. This work establishes a scalable framework for automated, in-line feedstock quality assessment, offering significant implications for process optimization and emissions reduction in hydrogen production.
Under this agreement, Laminar will loan Argonne a 50L Taylor Vortex Reactor (TVR) and provide mechanical troubleshooting guidance and consulting to ensure the successful setup of the pilot-scale synthesis process. The U.S. Department of Energy (DOE) will allocate funding for the labor and materials required for the study. To evaluate the physical and electrochemical properties of the materials produced by the 50L TVR, Argonne will perform comprehensive characterizations, including XRD, SEM, PSA, ICP, tap density, and coin half-cell testing. Throughout the collaboration, Argonne will provide feedback and recommendations for mechanical improvements to the reactor system. Furthermore, Argonne will credit Laminar as a collaborator in any presentations or publications resulting from data generated by the system. Laminar will retain no rights to experimental results or intellectual property generated through the experiments conducted with the 50L TVR at Argonne.
A new family of nanostructured ternary intermetallic compounds − named the ZIP phases − is introduced in this work. The ZIP phases exhibit dualistic atomic ordering, i.e., they form two structural variants: one with the fcc diamond cubic structure (space group Fd$\bar{3}$m) and one with the hexagonal structure (space group P6 3 /mmc). They are also characterized by metallic behavior, ionic bonding, and atomic zigzagging. Powder metallurgical routes involving pressure-assisted densification are adopted to demonstrate ZIP phase synthesis in the Nb-Si-Ni, Nb-Si-Co, Ta-Si-Ni, V-Si-Ni, and Nb-Si-Fe ternary systems. Crucially, reactive hot pressing is capable of producing high-purity ZIP phase materials after the judicious, elemental system-specific optimization of the processing route. Synthesis of phase-pure materials – demonstrated in the Nb-Si-Ni ternary system by the synthesis of quasi phase-pure Nb 3 SiNi 2 and Ni 3 SiNb 2 ZIP phase-based materials – is a steppingstone to the prospective exploitation of the ZIP phases. Characterization of Nb 3 SiNi 2 and Ni 3 SiNb 2 involves crystal structure determination, spatially resolved chemical analysis, and determination of select thermal, electrical, magnetic, mechanical, and physical properties. Density functional theory is used to assess the stability of Nb 3 SiNi 2 & Ni 3 SiNb 2 and derivative binary compounds at different temperatures, also exploring the exfoliation of these two ZIP phases along specific surfaces to produce 2D derivatives.
Abstract In the interest of continued industrialization of metal additive manufacturing in modern production environments, cost is often referenced as a primary deterrent to new adopters. Conventional economic models for additive systems, processes, and supply chains often focus on specific process applications with little generalizability, or they neglect significant costs associated with production such as machine maintenance and consumable part replacement. Compounding the latter issue are substantial knowledge gaps in consumable part wear characterization for additive and other convergent manufacturing systems. In coaxial blown powder directed energy deposition systems, gas atomized metal powder is wasted during material deposition at a rate that is partly dependent on present wear phenomena in a consumable nozzle housed in the cladding head assembly. The price and lead time required to replace the nozzle incentivizes its reuse even when visibly worn. Often this initiates a process quality decline in the form of underbuilt geometry and internal defects due to losses in powder catchment efficiency. While depositing H13 steel using a hybrid manufacturing machine tool equipped with such a deposition system, a unique partial clog with a bridge-like structure formed at the consumable nozzle exit when supporting argon gas flows failed mid-process. To further understand coaxial multi-phase powder flow in the event of support gas failure, a computational fluid dynamics simulation is tailored to relevant process parameters, H13 powder material profile, and machine operator observations collected after the incident. The resulting differences in powder flow compared to control gas flow parameters is presented and discussed. The powder flowability and performance of the clogged nozzle is then assessed by using an optical profilometer to extract the profile of the clog and recreate the clog geometry within the simulation environment. In past work this simulation has been experimentally validated for a 316L steel powder material profile and used specifically for analyzing powder stream geometry and catchment efficiency. After the initial powder flow characterization, the clog is removed, and the nozzle is reprofiled. After removing the obstructing clog, the newly unobstructed nozzle geometry, the original off the shelf nozzle geometry, and additional nozzle profiles exploring different consumable refurbishment strategies are reevaluated in the simulation. Powder catchment efficiency for all variant nozzle geometries and relevant flow variables are compared and discussed, along with potential mitigation strategies for optimizing powder flowability with worn consumables. This work expands on the known morphology of blown powder obstructions and wear defects present in consumable coaxial nozzles while discussing pragmatic simulation driven responses to unanticipated subsystem failure in hybrid manufacturing machining platforms.
The oxidation of pyrolytic carbon (PyC) deposited via fluidized bed chemical vapor deposition was characterized and compared with that of standard nuclear-grade graphite. The materials were heated at 700 to 1000 °C in a thermogravimetric analysis system under 20% v/v O 2 flow, allowing for direct comparison of dynamic oxidative mass change in each material. Further, three different PyC samples fabricated under different conditions exhibited variation in total mass loss and mass loss rate, varying by as much as 709 mg/cm 2 in total mass loss and 14.2 (mg/cm 2 )/min in mass loss rate at a single temperature. These variations highlight the correlation between PyC microstructure/defect density and oxidation susceptibility. Additionally, changes in the microstructure and composition between PyC and graphite were characterized via scanning electron microscopy and correlated to the mass loss results. The results of this work have implications toward the safety of tristructural isotropic (TRISO) and other coated particle fuels, especially under off-normal conditions, given the limited information that exists about the oxidation behavior of PyC.
Sodium layered oxides Na x MO 2 (x ≤ 1 and M = transition metal ions) have gained significant interest as sodium-ion battery (NIB) cathodes owing to their high operating voltages and potential for higher energy density compared with polyanion and Prussian blue–type cathodes. However, their practical applications are often hindered by the irreversible structural transitions leading to capacity fading during cycling. The nature and substitution of transition metal ions define the material properties and electrochemical performance. In this study, through comprehensive electrochemical characterization combined with multi-scale structural and spectroscopical analyses, we demonstrate the synergistic impacts of Lithium and Titanium doping, which not only increases overall capacity by boosting cation and anion cooperative redox contributions but also improves the rate capability and cycling stability. Specifically, Li + doping enhances the available sodium inventory for extraction, while Ti 4+ disrupts Na + /vacancy ordering at lower voltages (< 4 V) and mitigates the detrimental P2→OP4/O2 phase transition during cycling. The combined effect of Lithium and Titanium doping promotes more charge localization on Oxygen, which activates reversible lattice oxygen redox reactions at elevated voltages, contributing additional capacity beyond conventional cationic redox. This work provides crucial insights into the design of high-performance, high-capacity P2-type layered cathode materials for sodium-ion batteries.
X-ray absorption spectroscopy (XAS) is a powerful characterization technique for probing the local chemical environment of absorbing atoms. However, analyzing XAS data presents significant challenges, often requiring extensive, computationally intensive simulations, as well as significant domain expertise. These limitations hinder the development of fast, robust XAS analysis pipelines that are essential in high-throughput studies and for autonomous experimentation. Here, we address these challenges with OmniXAS, a framework that contains a suite of transfer learning approaches for XAS prediction, each uniquely contributing to improved accuracy and efficiency, as demonstrated on the K-edge spectra database covering eight 3d transition metals (Ti–Cu). The OmniXAS framework is built upon three distinct strategies. First, we use M3GNet [Nat. Comput. Sci. 2, 718 (2022)] to derive latent representations of the local chemical environment of absorption sites as input for XAS prediction, achieving significant improvements over conventional featurization techniques. Second, we employ a hierarchical transfer learning strategy, training a universal multitask model across elements before fine-tuning for element-specific predictions. Models based on this cascaded approach after elementwise fine-tuning outperform element-specific models by up to 69%. Third, we implement cross-fidelity transfer learning, adapting a universal model to predict spectra generated by simulation of a different fidelity with a much higher computational cost. This approach improves prediction accuracy by up to 11% over models trained on the target fidelity alone. Our approach significantly boosts the throughput of XAS modeling by orders of magnitude as compared to first-principles simulations and is extendable to XAS prediction for a broader range of elements. The proposed transfer learning framework is generalizable to enhance deep-learning models that target other properties in materials research.
A 90W-7Ni-3Fe (wt.%) tungsten heavy alloy has been sequentially Ni + and He + ion irradiated at 700 °C to simulate the high temperature irradiation environment of a fusion reactor interior. W/Ni–Fe-W dual-phase alloys have been proposed to serve as plasma facing materials and require detailed investigation of their behavior under fusion relevant conditions to assess their overall applicability. To evaluate material performance under five years of simulated fusion reactor service, microstructural characterization of the nanoscale defect distribution has been performed on both constituent phases, revealing peak swelling in the W phase of approximately 0.03%. The γ-phase (Ni–Fe-W) is found to swell approximately 0.68% under the same irradiation conditions, indicating significant cavity formation and growth. Additionally, a novel multi-projection imaging approach has been applied to determine the extent of damage segregation along the dual-phase W-to-γ interface and exposes that these interfaces act as sink sites for the accumulation of cavities. Interphase boundaries are noted to possess an 11.8% areal coverage of defects along the boundary plane, primarily on the γ-phase side of the boundary. The accumulation of cavities at these interphase boundaries is anticipated to adversely affect overall material toughness, and this work reveals a pressing need for mechanical property testing of irradiated W–Ni-Fe dual-phase alloys.
This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.
This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.
This report summarizes activities conducted to understand and mitigate the negative consequences that moisture ingressions have upon the operations of pyroprocessing equipment. The objectives of the work conducted in FY25 were to characterize (1) the physicochemical properties of particles generated as a result of moisture ingressions, and (2) the corrosion of relevant structural materials with the introduction of moisture. Compositional and morphological analyses of the generated particles were conducted through a suite of characterization technologies, including X-ray diffraction, microscopy, and particle size analysis. The results gathered this year were compared to those obtained in FY24 when studies with oxygen ingressions were conducted on CeCl 3 -LiCl-KCl and UCl 3 -LiCl-KCl systems. Investigations involving performance evaluations of industrially relevant structural alloys were also conducted under moisture ingress conditions. In-line electrochemical monitoring of the bulk salt was augmented with microscopy of alloy samples to quantify the concentration and accumulation of corrosion products in the bulk salt. The results reported in this work provide a more holistic understanding of the effects of atmospheric ingressions on molten chloride salt chemistry such that effective redox control strategies may be implemented.
Defects play a significant role in the material properties of carbon fibers (CF). Several defects result in the formation of sp 3 bonds in an otherwise sp 2 -dominant graphitic structure. Understanding the distribution of these defects within CF provides insight into their properties and the effect of manufacturing conditions. Reports showed time-of-flight secondary ion mass spectrometry (ToF-SIMS) is capable of characterizing the spatial distribution of sp 2 and sp 3 content in carbon materials. Here, ToF-SIMS was utilized to investigate the spatial distribution of sp 3 defects in T700, T1000, and M46 CF. M46 had the lowest sp 3 content. Center-to-edge analysis revealed that T700 CF had a gradient of sp 3 defects starting from the center and increasing to the edge, whereas M46 CF had a sudden increase in sp 3 defects roughly 1 μm from the edge. Comparatively, T1000 CF had a relatively uniform radial distribution of sp 3 defects, except for a newly identified sp 2 rich region at 0.8 μm from the center. This is hypothesized to originate from a skin–core structure that forms during CF manufacturing. As a result, this work demonstrates the utility of ToF-SIMS for characterizing the spatial distribution of sp 3 defects within CF, establishing new ways to understand CF formation.