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At least 19 records

A Dispersion-Strengthened Low-Density Niobium Alloy and Its Elevated Temperature Mechanical Performance

In response to the elevated-temperature and weight-reduction demands of modern aerospace applications, a novel oxide-dispersion-strengthened low-density niobium alloy (LDNb-ODS) was fabricated using laser powder bed fusion (L-PBF). To overcome powder procurement barriers, L-PBF feedstock was produced by blending commercial Nb521, Ti64, and Cr powder with Y2O3 nanoparticles via resonant acoustic mixing. Following L-PBF and a 1400°C vacuum heat treatment, the alloy achieved a density of 6.73 g/cc and a fine mean grain size of 4.62 µm stabilized by uniform ~30 nm yttria dispersoids. Microstructural analysis revealed a chemically inhomogeneous build with lack-of-fusion defects and a titanium (Ti) shift from a nominal 31.5 wt% in the starting powder blend to 24.8 wt% in the printed part due to preferential Ti loss during printing. Elevated-temperature tensile testing demonstrated that LDNb-ODS maintained a superior specific yield strength of 60-85 MPa/(g/cc) up to 800°C, outperforming nickel-based alloys Ni625, Ni230, and GRX-810. Between 870°C and 950°C, its specific strength surpassed both Ni718 and Ni625. In rapid stress-rupture testing at 1093°C and 20.7 MPa, uncoated LDNb-ODS survived 21.4 hours (a tenfold increase over legacy C-103) while an R512E silicide coating extended rupture life to 84.8 hours, confirming that oxidation accelerates low-stress failure. These findings demonstrate that additive manufacturing of LDNb-ODS provides a viable, lightweight alternative to nickel-based superalloys for high-temperature (>850°C) aerospace components.

Low Density Niobium Alloy

Sustainable Shape Memory Elastomers with Reduced Melt Viscosity and Enhanced Stiffness

Melt reactive processing of lignin with nitrile rubber is a promising approach to synthesizing shape memory materials. The strong intramolecular interactions in lignin macromolecular structures, caused by π–π stacking in aromatic rings and hydrogen bonding, often result in large phase separation or low miscibility with rubbers. In this study, we investigated the chemical and molecular characteristics, as well as the stiffness and complex viscosity, of modified kraft lignin melt-reacted with an acrylonitrile/butadiene copolymer containing 41% acrylonitrile (NBR41). To enhance the macromolecular compatibility of kraft lignin with NBR41, kraft lignin was cross-linked with poly(propylene glycol) diglycidyl ether (PPDE) and trimethylolpropane triglycidyl ether (TTE), both rich in epoxy reactive groups capable of forming chemical bonds with hydroxyl and carboxyl groups. Here, our findings demonstrate that the modification of kraft lignin with PPDE and TTE resulted in significantly increased stiffness of the composites. The elastic modulus of NBR41-Kraft lignin-PPDE and NBR41-Kraft lignin-TTE increased by 82 and 162%, respectively. Both the yield strength and Young’s modulus of these two samples showed dramatic improvements. Specifically, the yield strength and Young’s modulus of NBR41-Kraft lignin-TTE increased nearly 4 and 3-fold, respectively, compared to the control sample. Interestingly, despite significant improvements in mechanical properties, the viscosity of NBR41-Kraft lignin-PPDE was substantially lower than that of the control sample. At 210 °C and an angular frequency of 1 rad/s, the complex viscosity of NBR41-Kraft lignin was approximately 100.25 ± 4.77 kPa·s, while that of NBR41-Kraft lignin-PPDE was significantly lower at 56 ± 0.93 kPa·s. These findings were validated through Fourier transform infrared spectroscopy, scanning electron microscopy, dynamic mechanical analysis, thermal characterization, rheological tests, and quasi-elastic neutron scattering techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Achieving ultrahigh modulus of resilience and enhanced thermal stability in ZnO x /SU-8 interpenetrating network polymer nanocomposite nanopillars

The modulus of resilience, a mechanical property that quantifies the maximum strain energy density a material can store during elastic deformation, is a crucial parameter for materials used in flexible displays, micro/nano-electro-mechanical system (M/NEMS) actuators, and ultra-sensitive pressure sensors. In this study, ZnO x /SU-8 nanocomposite nanopillars with a diameter of 300 nm, fully infiltrated with a uniformly distributed, interpenetrating amorphous ZnO x filler network, were synthesized via vapor-phase infiltration (VPI). In-situ uniaxial nano-compression tests revealed that the modulus of resilience of ZnO x /SU-8 reaches ∼ 12 MJ/m 3 , which is an ultrahigh value among all engineering materials with comparable strength. In addition, the synthesis fidelity, inorganic infiltration depth, and mechanical performance were all significantly improved compared to VPI-synthesized AlO x nanocomposites. Thermal stability, another key requirement for M/NEMS device materials operating under extreme environments, was also notably enhanced. Furthermore, partial crystallization of the amorphous ZnO x fillers during annealing contributed to an additional increase in modulus of resilience, reaching up to ∼ 13.9 MJ/m 3 . This work presents an effective fabrication strategy for producing nanostructured organic–inorganic hybrid nanocomposites with ultrahigh modulus of resilience and superior thermal stability, paving the way for their integration into next-generation flexible displays and high-performance M/NEMS devices working under harsh environments.

36 MATERIALS SCIENCE

Microstructural, Oxidation, and Mechanical Behavior of NbTi-Based Refractory Alloys with 5 to 10 Pct Co, Cr, and Ni Additions

NbTi-based refractory alloys with additions of Co, Cr, and Ni represent an interesting medium-entropy alloy system with potential for protective oxide film formation, high strength, and ductility. This study investigates the microstructural evolution, oxidation behavior, and mechanical properties of NbTi-based alloys containing 5 to 10 at. pct Co, Cr, and Ni. CALPHAD predictions suggest that this composition range can be heat treated to obtain a predominantly body-centered cubic matrix phase. Mechanical properties, including microhardness, yield strength, maximum strength, and specific strength are evaluated through isothermal compression tests conducted between room temperature and 800 °C. The oxidation kinetics of these alloys are assessed through discontinuous oxidation tests. Parabolic oxidation kinetics were observed for NbTi–10Ni and NbTi–5Co, while linear oxidation kinetics were found for NbTi–10Cr and NbTi–10(CoCrNi). Microstructures and oxide layers are characterized using X-ray diffraction, electron backscatter diffraction, energy-dispersive X-ray spectroscopy, and scanning electron microscopy. All alloys exhibit significant mechanical softening between room temperature and 800 °C, with elastic-perfectly plastic flow observed at 800 °C. The addition of 10 pct Cr to NbTi resulted in two BCC phases up to 1050 °C, conflicting with CALPHAD predictions of a single-phase solid solution at this temperature, and resulting in higher flow stress at 800 °C. NbTi–10(CoCrNi) exhibited the lowest flow stress at 800 °C despite having more ‘cocktail effect’ potential and insufficient molar fractions of Co, Cr, or Ni to form a desirable protective oxide film.

36 MATERIALS SCIENCE

Accurate and uncertainty-aware multi-task prediction of HEA properties using prior-guided deep Gaussian processes

Surrogate modeling techniques have become indispensable in accelerating the discovery and optimization of high-entropy alloys (HEAs), especially when integrating computational predictions with sparse experimental observations. This study systematically evaluates the training and testing performance of four prominent surrogate models—conventional Gaussian processes (cGP), Deep Gaussian processes (DGP), encoder-decoder neural networks for multi-output regression and eXtreme Gradient Boosting (XGBoost)—applied to a hybrid dataset of experimental and computational properties of the 8-component HEA system Al-Co-Cr-Cu-Fe-Mn-Ni-V. We specifically assess their capabilities in predicting correlated material properties, including yield strength, hardness, modulus, ultimate tensile strength, elongation, and average hardness under dynamic/quasi-static conditions, alongside auxiliary computational properties. The comparison highlights the strengths of hierarchical deep modeling approaches in handling heteroscedastic, heterotopic, and incomplete data commonly encountered in materials science. Our findings illustrate that combined surrogate models such as DGPs infused with machine-learned priors outperform other surrogates by effectively capturing inter-property correlations and by assimilating prior knowledge. This enhanced predictive accuracy positions the combined surrogate models as powerful tools for robust and data-efficient materials design.

36 MATERIALS SCIENCE

Location-Specific Microstructures and Properties of Haynes 282 Alloy with Laser-Wire DED Processing

In this work, the location-specific microstructures in terms of grain morphology, texture, γ′ precipitates, carbides, and residual strains were investigated in a series of laser-wire direct energy deposition (LW-DED) Haynes 282 alloys with varied processing parameters. A bimodal grain distribution was found in these as-printed and heat-treated alloys with columnar grains within the layers and fine equiaxed grains at the interlayer regions. Dominant <001> texture along the build direction with more obvious <111> orientation preference exists at the bottom layers, compared to the top layers. The gradient γ′-precipitates size distribution contributes predominantly to the observed gradient hardness distribution in the as-printed samples. The heat-treated 282 exhibit comparable yield strengths to those conventionally-processed counterparts, while the observed small deviation in their yield strengths is attributed to the Hall-Petch effect. This work establishes the correlation between location-specific microstructures and mechanical properties, providing valuable insights into future printing parameters and heat-treatment optimization.

Haynes 282

A novel microstructural approach for TRIP/TWIP β-Ti alloys using intermetallic precipitation

Interest in metastable β-Ti has grown, due to the exceptional work hardening caused by TRansformation and TWinning Induced Plasticity (TRIP/TWIP). A current challenge is increasing the yield strength, while maintaining the benefits of TRIP/TWIP. This study presents the first report of TRIP/TWIP in a metastable β-Ti alloy containing intermetallic compounds, specifically Ti silicide precipitates. Silicon (Si) additions enable the formation of silicide particles, which can be precipitated, dissolved, and controlled through tailored heat treatments. In-situ synchrotron x-ray diffraction during tensile testing reveals primary {332}<113> twinning activates first, followed by TRIP, leading to extensive work hardening and uniform elongation in the solutionized state. In conclusion, these findings open a novel microstructural approach to the design of multiphase TRIP/TWIP titanium alloys, relying on intermetallic precipitation rather than allotropes such as α or ω phase, and lay the groundwork for future studies on intermetallic precipitation strengthening.

Materials science

Inverse design of hypoeutectoid pearlite steel microstructures using a deep learning and genetic algorithm optimization framework

Goal-oriented microstructure design in metallic materials is a challenging task due to complex structure-property relationships. Traditional experimental and computational approaches are time-intensive and economically inefficient, limiting their applicability for large-scale design space exploration. Here, in this work, we propose an end-to-end framework that integrates deep learning models with genetic optimization to design microstructures with targeted mechanical properties. Deep learning models enable accurate forward design, while their integration with genetic optimization enables efficient inverse design within a few hours, compared to days or weeks using conventional finite element simulations. The framework combines experimental characterization and finite element modeling to analyze the influence of microstructural features on the mechanical behavior of hypoeutectoid steels. Data from both experiments and simulations are used to train the deep learning models. To demonstrate its effectiveness, we apply the framework to 0.63% carbon steel with proeutectoid ferrite and pearlite phases, commonly used in industrial applications. In this study, 2D microstructures were used for modeling, selected primarily for computational efficiency and to establish proof of concept. The framework successfully optimizes microstructures for targeted yield strength, ultimate strength, and stress concentration factors while significantly reducing computational time. Beyond hypoeutectoid steels, this scalable framework can be extended to other material systems and integrated with additive manufacturing, offering an efficient approach for accelerating microstructure design for specific engineering applications.

ConvLSTM

Elucidating texture and grain morphology contributions to the micromechanical response of additively manufactured Inconel 625

Microstructural variation of additively manufactured (AM) metal components in comparison to wrought counterparts makes certification for critical applications a challenge. Microscale simulations leveraging modern computational tools may be used to supplement testing of AM microstructures, thus accelerating certification by reducing the number of experiments needed. However, as micromechanical response is closely tied to critical properties like fatigue-life and fracture, utilization of these simulations with macroscale experimental data alone is insufficient. One means to attain microscale experimental data is in situ diffraction data collected from synchrotron X-ray sources. In this work, such data were collected during in situ compression of AM Inconel 625 superalloy. Interpretation of experimental results was assisted by massive (8M element) complementary micromechanical simulations performed on sets of virtual microstructures generated using cellular automata. Together, micromechanical data from diffraction experiments and simulations were used to probe the effects of textured “track” microstructures generated during laser powder bed fusion and directional strength-to-stiffness on micromechanical response. Though fiber-averaged directional strength-to-stiffness ratios were expected to dominate given the high elastic anisotropy of the material, the combination of small variations in texture and specific grain configurations unique to AM microstructures lead to significant variability in micromechanical response after yield. The findings emphasize the importance of high-fidelity microstructural representation that captures key texture components and AM-specific morphology for property prediction of AM metals.

36 MATERIALS SCIENCE

Microstructural Evolution and Mechanical Properties of LP-DED NASA HR-1 – A Hydrogen Resistant AM Superalloy for Space Propulsion Applications

The National Aeronautics and Space Administration (NASA) has actively pursued metal additive manufacturing (AM) technologies for spaceflight applications since the late 2000s. AM offers transformative advantages in cost, schedule, part consolidation, and design flexibility. Among the various AM techniques, laser powder directed energy deposition (LP-DED) is particularly well suited for fabricating complex geometries with fine feature resolution. In propulsion systems that utilize high-pressure gaseous hydrogen—such as liquid hydrogen rocket engines—hydrogen environment embrittlement (HEE) presents a serious threat to material performance 1,2 . Mechanical property degradation under these conditions can compromise component reliability, especially under cyclic loading. To address this challenge, NASA developed NASA HR-1 (Hydrogen Resistant-1) as a solution for liquid rocket engine components operating in hydrogen-rich environments, using the LP-DED technique 3-9 . A key component in a liquid rocket engine is the exhaust nozzle, which is typically regeneratively cooled (regen) due to the high heat flux. NASA HR-1 was specifically developed for regen nozzle applications using hydrogen as a propellant, providing resistance to HEE, a critical issue for many materials. The AM version of NASA HR-1 was also formulated to achieve high ultimate tensile strength, along with high yield strength and ductility in this environment 5,6 . Low-cycle fatigue (LCF) is another important consideration in nozzle design, as components are expected to endure multiple starts and missions. Additionally, the LP-DED version of the alloy exhibits improved thermal conductivity compared to its wrought counterpart, which benefits nozzle cooling. Overall, NASA HR-1 offers an excellent balance of high strength, HEE resistance, LCF performance, thermal conductivity, and ductility to meet the demanding requirements of channel-cooled nozzles and other components used with hydrogen and other propellants. The LP-DED–processed NASA HR-1 requires several post-processing heat treatment steps to achieve the material properties desirable for its intended application 6 . These steps include stress relief, homogenization, solution annealing, and aging for precipitation hardening. The stress relief treatment mitigates residual stresses accumulated during the LP-DED process and minimizes the potential for distortion. Homogenization, a common step for AM materials, reduces elemental segregation and promotes recrystallization to develop a more equiaxed grain structure. The subsequent solution annealing treatment heats the part to a solid solution temperature to dissolve the undesirable η-phase that forms during cooling from homogenization, followed by rapid cooling to retain an η-phase–free microstructure. Finally, aging promotes precipitation of the strengthening γ′ phase in the alloy. The integration of compositional design and optimized thermal processing enables high-quality LP-DED NASA HR-1 components with excellent microstructural and mechanical stability. Improved chemical and microstructure homogeneity enhances ductility and fatigue resistance—both critical for safe and reliable operation in high-pressure hydrogen environments. NASA has successfully fabricated and hot-fire tested multiple subscale and full-scale channel wall nozzles using LP-DED NASA HR-1 5,6, 9-14 . These efforts included process refinements to support thin-wall construction and various channel geometries. Throughout development, several key observations emerged. After homogenization, the as-built columnar grain structure transforms into a fully equiaxed microstructure. However, subsequent treatments—such as solution annealing and aging—result in changes that are more difficult to track. The grain structure remains largely unchanged, and the γ′ precipitates, typically 5–10 nm in diameter, are beyond the resolution of scanning electron microscopy (SEM). While transmission electron microscopy (TEM) can resolve these fine precipitates, TEM sample preparation is time-consuming and difficult for LP-DED material. As an alternative, differential scanning calorimetry (DSC) offers a useful, qualitative approach to monitor precipitate evolution throughout different stages of heat treatment. The overall goal is to improve the understanding of how heat treatment affects the microstructure and mechanical performance of LP-DED NASA HR-1. This paper presents heat treatment design considerations, microstructural characterization, mechanical testing – including tensile and LCF testing in both air and hydrogen environments.

Superalloy

Work Hardening Model of Structure in Hall-Petch Strengthening

The microstructural length scale of metals changes by orders of magnitude under extreme processing conditions producing a concurrent wide range of mechanical strength and plasticity behaviors. A unified stress-strain σε σ(ε) model is formulated that’s based on superposing the components of asymptotic-curvilinear work hardening Θσ Θ(σ) to qualify and quantify these mechanical behaviors. This approach accounts for the rapid strengthening of metals beyond the initial yield point, through extended steady-state deformation, to the structural instability. The relationship between the softening coefficients cbi c bi of the work hardening formulation Θσ Θ(σ) and strength are found to reveal the microstructural scale in the material. Specifically, the rapid decrease in the slope of the Θσ Θ(σ) curve provides a measure for microstructural size consistent with a functional Hall-Petch relationship of strength. A successful application is shown for the tensile behavior of pure aluminum microstructures that result from extreme plastic deformation by equal-channel angle pressing.

Hall-Petch strengthening

Nitrile/Buna N Material Failure Assessment for an O-Ring used on the Gaseous Hydrogen Flow Control Valve (FCV) of the Space Shuttle Main Engine

After the rollout of Space Shuttle Discovery in April 2005 in preparation for return-to-flight, there was a failure of the Orbiter (OV-103) helium signature leak test in the gaseous hydrogen (GH2) system. Leakage was attributed to the Flow Control Valve (FCV) in Main Engine 3. The FCV determined to be the source of the leak for OV-103 is designated as LV-58. The nitrile/Buna N rubber O-ring seal was removed from LV-58, and failure analysis indicated radial cracks providing leak paths in one quadrant. Cracks were eventually found in 6 of 9 FCV O-rings among the three Shuttle Orbiters, though none were as severe as those for LV-58, OV-103. Testing by EM10 at MSFC on all 9 FCV O- rings included: laser dimensional, Shore A hardness and properties from a dynamic mechanical analyzer (DMA) and an Instron tensile machine. The following test data was obtained on the cracked quadrant of the LV-58, OV-103 O-ring: (1) the estimated compression set was only 9.5%, compared to none for the rest of the O-ring; (2) Shore A hardness for the O.D. was higher by almost 4 durometer points than for the rest of the O-ring; and (3) DMA data showed that the storage/elastic modulus E was almost 25% lower than for the rest of the O-ring. Of the 8 FCV O-rings tested on an Instron, 4 yielded tensile strengths that were below the MIL spec requirement of 1350 psi-a likely influence of rubber cracking. Comparisons were made between values of modulus determined by DNA (elastic) and Instron (Young s). Each nitrile/Buna N O-ring used in the FCV conforms to the MIL-P-25732C specification. A number of such O-rings taken from shelf storage at MSFC and Kennedy Space Center (KSC) were used to generate a reference curve of DMA glass transition temperature (Tg) vs. shelf storage time ranging from 8 to 26 years. A similar reference curve of TGA onset temperature (of rubber weight loss) vs. shelf storage time was also generated. The DMA and TGA data for the used FCV O-rings were compared to the reference curves. Correlations were also made between the DMA modulus (at 22 C) and Shore A hardness for all 9 of the FCV O-rings used among the three Shuttle Orbiters. The radial cracking in the FCV O-rings was determined to be due to ozone attack, as nitrile/Buna N rubber is susceptible to such attack. Nitrile/Buna N material under MIL-P25732C should be used in a hydraulic fluid environment to help protect it from cracking. However, the FCV O-rings were used in an air only environment. The FCV design has as much as a 9-mil gap that allows the O.D. of the O-ring to be directly exposed to ozone, pressurized air and some elevated temperatures, accelerating the weathering process that leads to O-ring cracking. Space Shuttle flights will likely not continue past 2010. Therefore, Shuttle management decided to continue using the nitrile/Buna N material for the FCVs, but have each O-ring replaced after 3 years to minimize any chances for crack initiation.

Doug Wingard

Revealing and Engineering Assembly Pathways of 3D DNA Origami Crystals

Recent developments in nanomaterial self-assembly demonstrate the capability to create tailored nanostructures by engineering both the binding coordination and specificity of interactions between material subunits. DNA origami frames allow for the design and fabrication of a broad variety of ordered 3D nanoscale architectures through self-assembly, facilitated by frame-to-frame bonds with designable strength and specificity. While the bond design is critical to lattice formation, the assembly process itself is often dependent on a thermal pathway. Highly ordered nanoscale frameworks, assembled from DNA frames, are predominantly crystallized through thermal annealing pathways that typically follow a “slow” cooling approach, with experiments on the time scale of days yielding DNA origami crystals in the range of 1−10 μm. This extended assembly time scale hinders the study of crystal formation pathways, necessitating a deeper understanding of factors governing successful annealing. Lack of insight into time scale also presents a practical limitation for material fabrication. Here, we investigate key factors affecting lattice assembly pathways and demonstrate that precise engineering of assembly conditions greatly reduces assembly times by up to nearly 2 orders of magnitude. We evaluate the nucleation and growth of crystals via optical and electron microscopy, and small-angle X-ray scattering techniques, mapping the time−temperature-transformation of superlattices from the melt through single-crystal optical tracking. The results show that origami frame assembly can be described by classical nucleation and growth theory, which can, in turn, be used to prescribe the growth of the crystals. Lastly, these findings are applied to demonstrate thermal pathway-dependent assembly, forming distinct assemblies based on different thermal annealing profiles.

36 MATERIALS SCIENCE

Selective Amnesia using Contrastive Subnet Erasure for Class Level Unlearning in Vision Models

We study concept-level forgetting in pretrained vision models: removing an entire semantic category so the system no longer recognizes that object in unseen images and contexts, rather than merely forgetting specific training examples. Prior work either applies blunt global projections or fine-tunes parameters, which can introduce collateral damage to unrelated features, add compute, and become unstable as forgetting strength increases. We introduce Contrastive Subnet Erasure (CSE), a training-free, encoder-centric edit that targets a compact set of channels most responsible for the class and attenuates them in a calibrated manner. The modification is algebraically folded into the subsequent layer, yielding no inference-time overhead and leaving task heads unchanged. To evaluate whether forgetting generalizes beyond the data used to specify the class, we introduce a cross dataset protocol in which the class is defined on a source dataset and performance is measured on a disjoint target dataset drawn from a different distribution with no shared images. This setup tests whether the model still fails to recognize the object when it looks different or appears in new scenes, and it helps avoid overfitting to patterns in the source dataset. Across CIFAR 10, CIFAR 100, and ImageNet under this protocol, CSE achieves stronger forgetting of the target class while better preserving non target utility than existing baselines in both single class and multi class settings. Overall, CSE provides a simple, stable, and deployment-ready mechanism for class-level unlearning in vision.

Kotevska, Olivera [ORNL] (ORCID:0000000316772243)

Exploring scenarios for enhanced fuel compression and performance on the National Ignition Facility with machine-learning-aided design techniques

Recent fusion experiments on the National Ignition Facility (NIF) have achieved ignition, producing multi-MJ fusion yields for input laser energies of roughly 2 MJ [Abu-Shawareb et al., Phys. Rev. Lett. 132, 065102 (2024)]. Building on the success of the target designs that have achieved ignition, we explore new implosion scenarios predicted to generate significantly more compression of the dense DT ice layer and correspondingly higher yields while preserving many of the key physics characteristics of present-day ignition designs. Our main result is a novel 3-shock implosion scheme that effectively minimizes the shock-induced entropy in the dense, accelerating DT shell and maximizes the resulting fuel compression subject to a fixed leading shock strength consistent with present-day ignition experiments, which is necessary to melt the crystalline high-density carbon ablator. Compared to the first NIF experiment to fulfill Lawson's ignition criterion, shot N210808 [Abu-Shawareb et al., Phys. Rev. Lett. 129, 075001 (2022)], our design exhibits a 40% increase in simulated peak areal density (ρR) and a 5× increase in 1D fusion yield using a 4% lighter ablator and identical DT payloads. We also present a complete integrated 2D hohlraum design and laser pulse specifications capable of generating the desired 3-shock drive and maintaining control of the low-mode capsule implosion symmetry, where the increase in simulated 2D yield relative to N210808 is > 10×. This new implosion regime was discovered with help from a machine-learning-enabled capsule design optimization framework. We outline the workflow this automated tool uses to identify improved design candidates by running several rounds of capsule simulations, constructing a surrogate model mapping input variations to key physics output quantities, and querying the resulting statistical model to propose adjustments to the x-ray drive and capsule to reach a set of physics objectives prescribed by the designer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Charge density fluctuations with enhanced superconductivity at the proposed quantum critical point of Sr0.77⁢Ba0.23⁢Ni2⁢As2

A quantum critical point (QCP) represents a continuous phase transition at absolute zero. In unconventional superconductors, enhanced superconducting transition temperature and magnetic fluctuation strength are often observed together, indicating magnetism-mediated superconductivity. This raises the question of whether quantum fluctuations in other degrees of freedom, such as charge, could similarly boost superconductivity. However, because charge is frequently intertwined with magnetism, isolating and understanding its specific role in Cooper pair formation pose a significant challenge. Here, we report persistent charge density fluctuations (CDFs) down to 15 K in the nonmagnetic superconductor Sr0.77⁢Ba0.23⁢Ni2⁢As2, which lie near a proposed nematic QCP associated with a sixfold enhancement of superconductivity. Our results show that the quasielastic CDFs do not condense into resolution-limited Bragg peaks but, rather, display nonsaturated strength. The phonons associated with CDFs completely soften at 25 K, with their critical behavior described by the same mathematical framework as the antiferromagnetic Fermi liquid model, yielding a fitted Curie-Weiss temperature of 𝜃≈0K. Additionally, we find that the nematic fluctuations are weakly coupled to the lattice, as evidenced by the absence of softening in nematic-coupled in-plane transverse acoustic phonons. Our discovery positions Sr𝑥⁢Ba1−𝑥⁢Ni2⁢As2 as a promising candidate for charge-fluctuation-driven superconductivity.

Aczel, Adam [ORNL] (ORCID:0000000319641943)

Direct Observations of Solute Dispersion in Rocks With Distinct Degree of Sub‐Micron Porosity

Abstract The transport of chemical species in rocks is affected by their structural heterogeneity to yield a wide spectrum of local solute concentrations. To quantify such imperfect mixing, advanced methodologies are needed that augment the traditional breakthrough curve analysis by probing solute concentration within the fluids locally. Here, we demonstrate the application of asynchronous, multimodality imaging by X‐ray computed tomography (XCT) and positron emission tomography (PET) to the study of passive tracer experiments in laboratory rock cores. The four‐dimensional concentration maps measured by PET reveal specific signatures of the transport process, which we have quantified using fundamental measures of mixing and spreading. We observe that the extent of solute spreading correlate strongly with the strength of subcore‐scale porosity heterogeneity measured by XCT, while dilution is enhanced in rocks containing substantial sub‐micron porosity. We observe that the analysis of different metrics is necessary, as they can differ in their sensitivity to the strength and forms of heterogeneity. The multimodality imaging approach is uniquely suited to probe the fundamental difference between spreading and mixing in heterogeneous media. We propose that when multi‐dimensional data is available, mixing and spreading can be independently quantified using the same metric. We also demonstrate that one‐dimensional transport models have limited predictive ability toward the internal evolution of the solute concentration, when the model is solely calibrated against the effluent breakthrough curves. The data set generated in this study can be used to build realistic digital rock models and to benchmark transport simulations that account deterministically for rock property heterogeneity.

Kurotori, Takeshi [Department of Chemical Engineer

Mechanical Characteristics of Additively Manufactured ODS 316L and 316H Alloys with and Without Post-build Processing

This research aims to explore an accelerated development path for oxide dispersion-strengthened (ODS) alloys by integrating additive manufacturing (AM) technologies with recent advances in ODS materials and traditional manufacturing methods. Novel AM and post-build processing routes have been developed for ODS austenitic alloys, specifically Fe-Cr-Ni alloys like 316L and 316H. Electron microscopy and mechanical characterizations were conducted to evaluate the effects of process variables on microstructure and properties, aiming for an economically feasible route property optimization. Traditionally, ODS alloy production involves multi-day high-energy mechanical milling of alloy powder with yttria (Y 2 O 3 ) followed by powder consolidation via extrusion or other methods and additional thermomechanical processing (TMP) for property control. Here, to address these challenges associated with this complex and costly approach, we propose exploring alternative, cost-effective processing routes focusing on AM and traditional TMP methods. The new ODS alloy processing routes have achieved up to a 400% increase in yield strength and a 60% increase in ultimate tensile strength compared to wrought stainless steels while still maintaining significant ductility and fracture toughness. This paper details the novel and economical AM-based processing routes for ODS austenitic alloys, combined with post-build TMPs, and discusses the mechanical and microstructural characteristics of the developed materials.

Byun, Thak Sang [Oak Ridge National Laboratory (OR