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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 73 records · Page 4

Effect of autogenous shrinkage on microcracking and mass transport properties of concrete containing supplementary cementitious materials

It is well-known that supplementary cementitious materials (SCMs) and low water-to-binder (w/b) ratio increase autogenous shrinkage, but the impact on microcracking and long-term transport properties is less understood. This paper examines the effect of microcracking induced by autogenous shrinkage on transport properties of concretes cured up to ~3.6 years. Variables include SCM type (9% SF, 70% GGBS), w/b ratio (0.20–0.45), maximum-aggregate-size (MSA: 5–20 mm) and shrinkage reducing admixture (SRA). Oxygen diffusivity, permeability and water sorptivity were correlated with microcracks characterised using laser scanning confocal microscopy and 3D X-ray microtomography. Results show greater microcracking in mixes containing SCMs, low w/b ratio and large MSA. At the same w/b ratio and binder type, strong positive correlations are observed between transport and microcracking with increasing MSA, confirming the negative impact of autogenous shrinkage. SRA was effective in reducing these effects. The significance is compared with drying shrinkage and implications for durability are discussed.

36 MATERIALS SCIENCE↗

Modeling of multi-component precipitation and crystallization for zero-liquid-discharge desalination

This study proposes novel ZLD treatment trains that integrate multi-component chemical precipitation and multi-effect evaporative crystallization for efficient brine management. The methodology emphasizes sustainability by integrating CO₂ for chemical precipitation and reducing environmental impact, exemplified with two case studies: produced water that includes industrial waste heat utilization by adopting the emerging vacuum air-gapped membrane distillation (VAGMD) technology, and brackish groundwater that is abundant in sulphate which undergoes treatment by low-salt-rejection reverse osmosis (LSRRO) with interstage chemical precipitation. Here, this study is the first of its kind to simultaneously account for reducing risk of mineral scaling and effective recovery of valuable solids when incorporating VAGMD and LSRRO in ZLD treatment trains. Using Reaktoro and WaterTAP, both Python-based, open-source platforms, we model the recovery of high-purity magnesium, calcium, and sodium salts while optimizing energy consumption and operational efficiency in proposed ZLD pathways for case studies of produced water and brackish desalination brine management. Validation with experimental and reference data confirms the reliability of the models used. In both case studies, the optimized ZLD process achieves recovery rates of 97%, 99%, and 90% for Mg, Ca, and Na, with purities exceeding 99%, and brine volume reduced to less than 4% of the initial feed flow.

3D CT scans↗

Surface grain refinement of casting A380 aluminum alloy by ultrasonic-assisted surface mechanical grinding treatment

A novel surface processing technique, ultrasonic-assisted surface mechnical grinding treatment (U-SMGT), was proposed and applied to modify the surface micriostructure of the casting aluminum alloy (A380). Comprehensive post-process chracterization techniques including 3D profilometry, optical microscope, scanning electric microscopy (SEM), and electron backscatter diffraction (EBSD) were carried out to investigate the surface morphology and microstructure of the processed region (PR). It was found that a surface layer of grain refinement with a thickness of about 50 µm was formed. In the as-received base material (BM), large clusters of dendritic eutectic phase with a size of approximately 20 µm were isolated by α-Al matrix. Nano-indentation tests showed that hardness of the eutectic and α-Al in the as-received BM was 2.15 GPa and 1.2 GPa respectively. After U-SMGT, the large dendritic eutectic phase was broken down into much fine particles with an average size of 0.57 µm. These fine particles were uniformly distributed into the α-Al matrix. Nano-indentation measurement exhibited a hardness of 2.27 GPa within the processed region. The overall high hardness in the processed region is a result of the pinning effect of uniformly distributed fine dendrites and grain refinement of Al-matrix.

36 MATERIALS SCIENCE↗

Real-time visualization of particle evolution during reactive flux-assisted processing of aluminum melts

Here, a multi-modal, multi-scale correlative tomography investigation of Al-TiC metal matrix composites processed via flux-assisted reaction synthesis is reported. Synchrotron X-ray microradiography is utilized to visualize the reaction and particle evolution in real-time. Changes in particle diameter and areal number density suggest that the process is nucleation- rather than growth-dominated. At 950 °C, the bulk of the reaction takes place in a relatively short time span of less than 600 s. The microstructure is imaged at higher resolution in 2D (scanning electron microscopy) and 3D (synchrotron X-ray nanotomography), revealing the formation of carbide particles with a hexagonal platelet morphology. We propose that the morphology arises due to the incorporation of Si impurities during the experiment. It is expected that the correlative tomography workflow and analysis may guide future metal matrix composite (MMC) processing strategies.

36 MATERIALS SCIENCE↗

CO 2 Laser Sintering of Garnet-Type Solid-State Electrolytes

We report the processing of garnet-type solid-state electrolytes remains challenging as densification conventionally requires high sintering temperatures and long processing times, which can result in severe Li loss, the formation of secondary phases, and thus high porosity and low ionic conductivity. Here, we report an ultrafast sintering method based on CO 2 laser scanning with the assistance of a heating stage. We demonstrate the rapid densification of low-packing-density Li 6.4 La 3 Zr 1.4 Ta 0.6 O 12 (LLZTO) films, which are difficult to densify by conventional furnace sintering methods. This unique approach has three fingerprint characteristics: (1) mitigation of Li loss through ultrafast sintering (dwelling time $\ll$1 s); (2) a unique anisotropic shrinkage behavior that greatly reduces film thickness; (3) wave-like surface topology from point scanning strategy that enables 3D interfacial contacts with electrode materials. Herein, highly dense (95.68%) and highly conductive (0.26 mS·cm –1 at 25 °C) LLZTO films are obtained through CO2 laser sintering. This work provides a unique, scalable, and widely applicable ultrarapid laser sintering technique to overcome the difficulties associated with classic methods for the integration of SSEs for practical all-solid-state Li-metal battery applications.

36 MATERIALS SCIENCE↗

Atom probe datasets from neutron irradiated Fe-Cr alloys

A series of model Fe–Cr alloys containing 3–18 at.% Cr was neutron irradiated at a nominal temperature of 563 K to 1.82 dpa. Solute distributions were analyzed by atom probe tomography, which revealed α′ precipitation for alloys containing more than 9 at.% Cr. Both the Cr concentration dependence of α′ precipitation and the measured matrix compositions are in agreement with the recently published Fe–Cr phase diagrams. An irradiation-accelerated precipitation process is strongly suggested. Irradiation was carried out in the Advance Test Reactor (ATR) at Idaho National Laboratory. A series of six Fe–Cr alloys of nominal compositions 3, 6, 9, 12, 15 and 18 at.% Cr was irradiated at a neutron fluence (E > 1 MeV) of 1.1 × 1021 n cm−2 at 563 ± 15 K and to a damage level of 1.82 displacements per atom (dpa). Nominal neutron flux and dpa rate are 2.3 × 1014 n cm−2 s−1 and 3.4 × 10−7 dpa s−1, respectively. The microstructures of the Fe–Cr alloys were studied by atom probe tomography (APT) using a Cameca 4000X HR instrument. APT specimens were prepared by a standard lift-out process using a Quanta 3D 200i dual beam scanning electron microscope ensuring that the analyses were performed away from grain boundaries.

Bachhav, Mukesh↗

6cr

A series of model Fe–Cr alloys containing 3–18 at.% Cr was neutron irradiated at a nominal temperature of 563 K to 1.82 dpa. Solute distributions were analyzed by atom probe tomography, which revealed α′ precipitation for alloys containing more than 9 at.% Cr. Both the Cr concentration dependence of α′ precipitation and the measured matrix compositions are in agreement with the recently published Fe–Cr phase diagrams. An irradiation-accelerated precipitation process is strongly suggested. Irradiation was carried out in the Advance Test Reactor (ATR) at Idaho National Laboratory. A series of six Fe–Cr alloys of nominal compositions 3, 6, 9, 12, 15 and 18 at.% Cr was irradiated at a neutron fluence (E > 1 MeV) of 1.1 × 1021 n cm−2 at 563 ± 15 K and to a damage level of 1.82 displacements per atom (dpa). Nominal neutron flux and dpa rate are 2.3 × 1014 n cm−2 s−1 and 3.4 × 10−7 dpa s−1, respectively. The microstructures of the Fe–Cr alloys were studied by atom probe tomography (APT) using a Cameca 4000X HR instrument. APT specimens were prepared by a standard lift-out process using a Quanta 3D 200i dual beam scanning electron microscope ensuring that the analyses were performed away from grain boundaries.

Bachhav, Mukesh↗

Scan strategies in EBM-printed IN718 and the physics of bulk 3D microstructure development

Three-dimensional (3D) characterization provides opportunities for understanding processing-structure relationships in additively manufactured (AM) materials. Bulk samples of Inconel 718 were fabricated via electron beam melting (EBM) in order to study microstructural development as a function of energy input and beam scan strategy. TriBeam tomography of bulk Inconel 718 microstructures built under steady-state growth conditions reveals the sensitivity of microstructure formation and evolution to machine process parameters. Here, samples manufactured using a narrow range of energy input per unit build area result in varied grain morphologies and crystallographic textures. Using TRUCHAS, a thermal simulation software, the thermal history of bulk scan strategies was predicted, and combined with a calibrated microstructure-processing map to accurately predict bulk grain morphologies. The solidification parameters and the 3D measured nucleation density are used to predict the transition between columnar and equiaxed grain morphologies, providing a process map to guide AM parameter choices to locally control as-printed microstructure. A two-dimensional metric for characterizing bulk grain morphology was also found to agree well with predictions from the process map calibrated by 3D data. Combined with 3D tomography and thermal modelling, the physics of structure development were understood at a new level of detail with respect to the competing processes of grain nucleation and epitaxial growth.

36 MATERIALS SCIENCE↗

3D-Printed mmWave Quasi-Holographic Antenna for 2-D Beamforming

This paper presents the design and manufacturing of a novel 2D-scanning antenna that integrates a 3D-printed Rotman lens with a quasi-holographic leaky-wave antenna (HLWA). The proposed design achieved beam-scanning capabilities by leveraging the beamforming of the Rotman lens and the high-gain directive properties of the quasi-HLWA. The Rotman lens (RL) enables beam steering in the elevation plane by switching between input ports. The quasi-HLWA, designed using holographic principles, achieves frequency-controlled beam scanning in the azimuth plane. The entire antenna structure was fabricated using additive manufacturing with an Ink1092 substrate and silver ink for the conductive traces. This approach provides greater control over material placement and design freedom compared to traditional methods. A 25° transmission linear substrate taper was used to ensure good impedance matching between the Rotman lens and the quasi-HLWA, allowing greater gain while maintaining a good scanning range. The experimental results validate the 2D scanning capability of the proposed antenna. The antenna system provides coverage from −54° to 54° in the elevation θ plane and −28° to 28° in the azimuth plane ϕ , with a maximum measured gain of 21.3 dBi at 28 GHz with an average radiation efficiency η=60 %. The fabricated prototype was tested, and the performance was in good agreement with the simulated performance.

Rotman lens↗

Comprehension of Spatial Constraints by Neural Logic Learning from a Single RGB-D Scan

Autonomous industrial assembly relies on the precise measurement of spatial constraints as designed by computer-aided design (CAD) software such as SolidWorks. This paper proposes a framework for an intelligent industrial robot to understand the spatial constraints for model assembly. An extended generative adversary network (GAN) with a 3D long short-term memory (LSTM) network was designed to composite 3D point clouds from a single RGB-D scan. The spatial constraints of the segmented point clouds are identified by a neural-logic network that incorporates general knowledge of spatial constraints in terms of first-order logic. The model was designed to comprehend a complete set of spatial constraints that are consistent with industrial CAD software, including left, right, above, below, front, behind, parallel, perpendicular, concentric, and coincident relations. The accuracy of 3D model composition and spatial constraint identification was evaluated by the RGB-D scans and 3D models in the ABC dataset. The proposed model achieved 57.23% intersection over union (IoU) in 3D model composition, and over 99% in comprehending all spatial constraints.

Wang, Dali↗

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

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.

36 MATERIALS SCIENCE↗

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

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.

36 MATERIALS SCIENCE↗

Guiding the design of oxidation-resistant Fe-based single atom alloy catalysts with insights from configurational space

The high activity and selectivity of Fe-based heterogeneous catalysts toward a variety of reactions that require the breaking of strong bonds are offset in large part by their considerable instability with respect to oxidative deactivation. While it has been shown that the stability of Fe catalysts is considerably enhanced by alloying them with precious metals (even at the single-atom limit), rational design criteria for choosing such secondary metals are still missing. Since oxidative deactivation occurs due to the strong binding of oxygen to Fe and reduction by adsorbed hydrogen mitigates the deactivation, we propose here to use the binding affinity of oxygen and hydrogen adatoms as the basis for rational design. As it would also be beneficial to use cheaper secondary metals, we have scanned over a large subset of 3d–5d mid-to late transition metal single atoms and computationally determined their effect on the oxygen and hydrogen adlayer binding as a function of chemical potential and adsorbate coverage. We further determine the underlying chemical origins that are responsible for these effects and connect them to experimentally tunable quantities. Our results reveal a reliable periodic trend wherein oxygen binding is weakened greatest as one moves right and down the periodic table. Hydrogen binding shows the same trend only at high (but relevant) coverages and otherwise tends to have its binding slightly increased in all systems. Trends with secondary metal coverage are also uncovered and connected to experimentally tunable parameters.

Hensley, Alyssa↗

Uncovering the three-dimensional structure of upconverting core–shell nanoparticles with multislice electron ptychography

In photon upconverting core–shell nanoparticles, structure strongly dictates performance. Typical imaging in scanning transmission electron microscopy has sufficient resolution to probe the atomic structure of these nanoparticles, but contrast, dose, and projection limitations make conventional methods insufficient for fully characterizing these structures. Phase retrieval techniques provide a promising alternative imaging mode, and, in particular, multislice electron ptychography can recover depth-dependent information. Here, we study beam-sensitive photon upconverting core–shell nanoparticles with a multislice ptychography approach using a low electron dose to avoid damage. Large strain fields arise in these heterostructures due to the mismatch in lattice parameter between the core and the shell. We reconstruct both a nanoparticle that appears defect-free and one that has a large break in the side and map the distribution of strain in 3D by computing distortion fields from high-resolution potential images of each slice. In the defect-free nanoparticle, we observe twisting of the shell, while in the broken nanoparticle, we measure the 3D position of the crack, the core, and dislocations. These results highlight the advantage of multislice electron ptychography to recover 3D information from a single scan, even under strict electron dose requirements from beam-sensitive samples.

74 ATOMIC AND MOLECULAR PHYSICS↗

Assessment of a tomography-informed polyhedral discrete element modelling approach for complex-shaped granular woody biomass in stress consolidation

The design of handling equipment for granular biomass primarily requires experiments. Discrete element models (DEM) can provide designers with detailed insight into the behaviour of granular materials. However, granular biomass comprising complex-shaped particles is difficult to model with DEM. A tomography-informed DEM approach and an exhaustive assessment of the ability of the approach to predict the bulk behaviour of milled pines using experimental data is presented. Nano-CT scan was conducted to obtain 3D particle surface geometries as the basis for particle shape approximation by a polyhedral model and a sphero-polyhedral model. These models were applied in the simulation of a compressibility test. Our parametric study showed that particle Young's modulus and restitution coefficient are the two main properties influencing the simulated bulk behaviour of the DEM particles and that the level of approximating DEM particle shape for real particles is critical for accurately replicating the bulk behaviour of milled pines. The polyhedral model demonstrated better suitability than its sphero-polyhedral counterpart for modelling pine particles. The polyhedral model calibrated in a compressibility test was then applied in the simulations of a friction test without additional parameter tuning. Interlocking was dominant in the shear of bulk pine particles. Remarkably, the polyhedral model predicted the frictional behaviour of the pine particles when compared to the experimental results. The limitations of the model, as well as possible ways for enhancement, are discussed. This work provided novel insights into the suitability of complex-shaped DEM models for granular woody biomass.

Biomass flow↗

Correlative STEM-APT characterization of radiation-induced segregation and precipitation of in-service BWR 304 stainless steel

In this study, radiation induced segregation and precipitation phenomena in an in-service boiling water reactor 304 stainless steel component were investigated using directly correlated 3D-atom probe tomography and scanning transmission electron microscopy. Significant quantitative differences in measured segregation at grain boundaries were found between the atom probe and energy dispersive spectroscopy measurements of the exact same locations. In particular, a much stronger Si segregation (~10 atomic% via atom probe versus ~4 atomic% via electron microscopy) and different Cr profile shapes were detected that are critical to models of radiation induced segregation and stress corrosion cracking behavior. These quantitative differences highlight the need for comparative microscopy and critical evaluation of limitations in each analytical method. Elemental segregation to dislocations and conjoined-clusters were also highlighted by atom probe; confirming and expanding upon what has been observed in test reactor neutron and accelerator-based ion irradiations.

36 MATERIALS SCIENCE↗

Thermal cycling-driven microstructural changes of eutectic Al–Si phase change materials in SS304 containers revealed by multi-modal imaging

Aluminum-based Al–Si alloys are widely used as phase change materials (PCMs) in thermal energy storage (TES) systems owing to their high volumetric latent heat and superior thermal conductivity. However, their long-term reliability is limited by degradation processes that remain insufficiently understood. In this work, we employ a multimodal, correlative characterization framework to systematically resolve the degradation behavior of eutectic Al–Si PCMs in contact with SS304 containers under repeated thermal cycling. By integrating high-resolution electron microscopy, three-dimensional X-ray fluorescence (3D XRF) imaging, and differential scanning calorimetry (DSC), we directly link spatially resolved compositional and microstructural evolution to changes in thermophysical properties. The correlative analysis reveals that elemental leaching of Fe, Cr, and Ni from the stainless-steel container into the PCM drives the formation of intermetallic compounds (IMCs) both at the interface and within the bulk PCM, leading to pronounced compositional heterogeneity. These interfacial reactions and diffusion-induced transformations progressively destabilize the Al–Si eutectic, reducing the effective phase-transforming fraction. Consistent with these observations, DSC measurements show a decrease in melting temperature and latent heat of fusion with thermal cycling. These results underscore the critical influence of interfacial reactions and material compatibility on the stability, durability, and overall performance of Al–Si-based TES systems.

25 ENERGY STORAGE↗

Revealing the aging process of solid electrolyte interphase on SiOx anode

Abstract As one of the most promising alternatives to graphite negative electrodes, silicon oxide (SiO x ) has been hindered by its fast capacity fading. Solid electrolyte interphase (SEI) aging on silicon SiO x has been recognized as the most critical yet least understood facet. Herein, leveraging 3D focused ion beam-scanning electron microscopy (FIB-SEM) tomographic imaging, we reveal an exceptionally characteristic SEI microstructure with an incompact inner region and a dense outer region, which overturns the prevailing belief that SEIs are homogeneous structure and reveals the SEI evolution process. Through combining nanoprobe and electron energy loss spectroscopy (EELS), it is also discovered that the electronic conductivity of thick SEI relies on the percolation network within composed of conductive agents (e.g., carbon black particles), which are embedded into the SEI upon its growth. Therefore, the free growth of SEI will gradually attenuate this electron percolation network, thereby causing capacity decay of SiO x . Based on these findings, a proof-of-concept strategy is adopted to mechanically restrict the SEI growth via applying a confining layer on top of the electrode. Through shedding light on the fundamental understanding of SEI aging for SiO x anodes, this work could potentially inspire viable improving strategies in the future.

25 ENERGY STORAGE↗