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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 55 records · Page 3

Elastocaloric evidence for a multicomponent superconductor stabilized within the nematic state in Ba(Fe 1− x Co x ) 2 As 2

The iron-based high-$T_c$ superconductors (SCs) exhibit rich phase diagrams with intertwined phases, including magnetism, nematicity, and superconductivity. The superconducting $T_c$ in many of these materials is maximized in the regime of strong nematic fluctuations, making the role of nematicity in influencing the superconductivity a topic of intense research. Here, in this study, we use the AC elastocaloric effect (ECE) to map out the phase diagram of Ba(Fe 1− x Co x ) 2 As 2 near optimal doping. The ECE signature at $T_c$ on the overdoped side, where superconductivity condenses without any nematic order, is quantitatively consistent with other thermodynamic probes that indicate a single-component superconducting state. In contrast, on the slightly underdoped side, where superconductivity condenses within the nematic phase, ECE reveals a second thermodynamic transition proximate to and below $T_c$. We rule out magnetism and reentrant tetragonality as the origin of this transition and find that our observations strongly suggest a phase transition into a multicomponent superconducting state. This implies the existence of a subdominant pairing instability that competes strongly with the dominant $s^±$ instability. Our results highlight the significant role of nematic order in determining the pairing symmetry close to optimal doping in this extensively studied iron-based SC, while also demonstrating the power of ECE in uncovering strain-tuned phase diagrams of quantum materials.

Ghosh, Sayak [Stanford University, CA (United Stat↗

Accelerating Thermochemical Equilibrium Calculations for Nuclear Reactor Applications

Thermochemical properties play a key role in modeling and simulation of several key phenomena in nuclear reactors. There has been an increasing interest in incorporating CALPHAD-based formulations in multiphysics simulations including for Molten Salt Reactors where knowledge of phase evolution of the salt and the chemical potentials of various elements are of utmost importance in source term analyses and redox control. However, the size of such simulations is often limited by the high computational cost of full thermodynamic equilibrium calculations. This work discusses the current efforts aimed at accelerating thermochemical equilibrium calculations for multiphysics simulations performed using the open-source finite element / finite volume code Multiphysics Object Oriented Simulation Environment (MOOSE) [1]. While several methods have been proposed for accelerating phase equilibrium calculations [2], most focus on relatively small systems and often rely on a- priori knowledge of the state-space of the system. Nuclear materials, however, are often multi-component systems owing to the evolution of composition under irradiation and an approach based on a-priori mapping of phase diagram is often not enough. This work is aimed at demonstrating an on-the-fly surrogate modeling framework that uses active learning to reduce the number of full equilibrium calculations that must be performed. By combining with efficient coupling approaches, the surrogate framework helps in reducing the computational cost of thermodynamic equilibrium informed multiphysics simulations of nuclear materials. The performance is benchmarked against full coupling with the thermochemistry library Thermochimica [3]. This work uses a machine learning based approach for constructing surrogate models to predict the stable phases in a multicomponent system. The surrogates were constructed using neural networks and Gaussian process classification. In this work, we compare the relative performance of the two methods. We also demonstrate the use of caching previous calculations by interpolating the values from nearest neighbors. References [1] Lindsay, A.D., et al. "2.0 – MOOSE: Enabling massively parallel multiphysics simulation", SoftwareX, 20 (2022): 101202. [2] Roos, W.A. and Zietsman J.H. "Accelerating complex chemical equilibrium calculations – A Review", Calphad, 77 (2022): 102380. [3] Piro, M.H.A., et al. "The thermochemistry library Thermochimica", Computational Materials Science, 67 (2013): 266-272.

36 MATERIALS SCIENCE↗

Direct numerical simulations of three-component Rayleigh–Taylor mixing and an improved model for multicomponent reacting mixtures

We present direct numerical simulations of a three-layer Rayleigh–Taylor instability (RTI) problem with a configuration based on the experiments of Suchandra & Ranjan ( J. Fluid Mech. , vol. 974, 2023, A35) and Jacobs & Dalziel ( J. Fluid Mech. , vol. 542, 2005, pp. 251–279). The problem consists of a layer of light fluid between two layers of heavy fluid with an Atwood number of 0.3. These simulations are first validated through comparison with available experimental data. The validated simulations are then utilized to analyse statistics in this three-component flow. First, length scales are examined utilizing spectra and two-point spatial correlations of velocity and species concentration fluctuations. Next, joint probability density functions (p.d.f.s) of species concentration are compared against several model p.d.f.s representing generalizations of the bivariate beta distribution. Notably, the joint p.d.f.s do not appear to be accurately described by a Dirichlet distribution, indicating the marginal distributions do not conform to a beta distribution. Finally, similarity of the present configuration to three-component mixing found in inertial confinement fusion (ICF) applications is exploited to develop and validate an improved model for the impact of multicomponent mixing on thermonuclear (TN) reaction rates. A single time instant from the present simulations is chosen for a TN burn calculation under the hypothetical assumption of ICF materials and temperatures. Total TN output from this second calculation is then compared against the prediction of the improved model. The new model is found to accurately predict TN reaction rates in both premixed and non-premixed configurations.

42 ENGINEERING↗

Concurrent Amorphization and Nanocatalyst Formation in Cu‐Substituted Perovskite Oxide Surface: Effects on Oxygen Reduction Reaction at Elevated Temperatures

Abstract The activity and durability of chemical/electrochemical catalysts are significantly influenced by their surface environments, highlighting the importance of thoroughly examining the catalyst surface. Here, Cu‐substituted La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3‐δ is selected, a state‐of‐the‐art material for oxygen reduction reaction (ORR), to explore the real‐time evolution of surface morphology and chemistry under a reducing atmosphere at elevated temperatures. Remarkably, in a pioneering observation, it is discovered that the perovskite surface starts to amorphize at an unusually low temperature of approximately 100 °C and multicomponent metal nanocatalysts additionally form on the amorphous surface as the temperature raises to 400 °C. Moreover, this investigation into the stability of the resulting amorphous layer under oxidizing conditions reveals that the amorphous structure can withstand a high‐temperature oxidizing atmosphere (≥650 °C) only when it has undergone sufficient reduction for an extended period. Therefore, the coexistence of the active nanocatalysts and defective amorphous surface leads to a nearly 100% enhancement in the electrode resistance for the ORR over 200 h without significant degradation. These observations provide a new catalytic design strategy for using redox‐dynamic perovskite oxide host materials.

Jeon, SungHyun↗

Compositionally Complex Spinel Oxides as Conversion Anodes for Lithium-Ion Batteries

Four different compositionally complex multicomponent M 3 O 4 spinels containing 5–8 distinct metals were prepared by a rapid combustion synthesis method or solvothermal synthesis. High resolution synchrotron X-ray diffraction patterns show that the materials consist primarily of spinel phases with small amounts of rock salt impurities, and, in several samples, a minor amount of contracted spinel phase. Materials were investigated as conversion anodes in lithium half-cells and delivered significantly higher capacities than two-component MgFe 2 O 4 made by combustion synthesis. X-ray absorption near-edge structure (XANES) was used to estimate the oxidation states of the metals in the pristine, lithiated (discharged) and delithiated (charged) materials to better understand the redox processes in half cells that led to the improvement. Co, Ni, and Zn are reduced to low oxidation states during lithiation (cell discharge) but are only partially oxidized. The presence of a conductive metallic network that forms after lithiation is thought to account for the improved electrochemical characteristics. Interestingly, in most of the samples, iron is not fully reduced during initial lithiation unlike what happens with a set of related high entropy spinel ferrites studied previously. Finally, the improved electrochemical properties of these materials illustrates both the advantages of complexity and the difficulties in predicting their behavior.

25 ENERGY STORAGE↗

Cluster Dynamics Modeling Needs for the Advanced Materials and Manufacturing Technologies Program

This milestone report aims to identify and assess the cluster dynamics (CD) modeling requirements within the Department of Energy's Office of Nuclear Energy (DOE-NE) Advanced Materials and Manufacturing Technologies (AMMT) program and to communicate these needs to the DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The goal is to ensure NEAMS is well-informed about the CD modeling requirements to support AMMT's mission of accelerating the development, qualification, demonstration, and deployment of advanced structural materials and manufacturing for nuclear energy applications. CD modeling is an essential tool for predicting the degradation of structural materials under irradiation, which is a key component of AMMT's accelerated qualification process. The AMMT program focuses on both additively manufactured and wrought structural alloys, such as laser powder-bed fusion 316H austenitic stainless steel, alloy 709, Haynes 244, and alloy 617. These materials require a generalized CD modeling framework to facilitate rapid model development and computational simulation. A flexible, generalized CD software, similar to the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework, would enable modeling of various cluster types, including defect clusters, defect-solute clusters, and multicomponent clusters, incorporating thermodynamics and kinetics parameters. Radiation effects, microstructural feature evolution, and multi-dimensional modeling are critical considerations for the CD model. The usability of the CD code should allow for easy modification and coupling with MOOSE-based simulations. Additionally, the software should adhere to Nuclear Quality Assurance-1 standards, include a testing suite for verification and validation, and be version-controlled within a national laboratory-managed Git repository. Benchmark problems are needed to assess code predictions and performance.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Synthesis of multicomponent oxygen evolution reaction coatings via block copolymer templating with vapor- and solution-phase precursors

Porous mixed transition metal oxide heterostructures are promising electrocatalysts due to their high surface area. However, achieving conformal multicomponent oxide coatings with controlled nanoscale architectures remains challenging. Here, we report a synthesis strategy that integrates solution-based swelling infiltration (SBI) with gas-phase sequential infiltration synthesis (SIS) in a block copolymer template to fabricate porous, high-surface-area, conformal mixed-oxide electrocatalytic coatings. In this approach, a PS75-P4VP25 block copolymer (BCP) film is first infiltrated with transition metal acetylacetonate precursors via SBI, followed by exposure to gas phase precursors of ZnO via SIS process. Thermal annealing of the infiltrated BCP films converts them into all-inorganic Fe–ZnO, Fe–Co–ZnO, and Fe–Ni–ZnO coatings. Electrochemical testing on 70 nm thick conformal coatings demonstrates promising oxygen evolution reaction (OER) activity in alkaline media, with mass-specific current densities up to 1.0 × 10 5 mA/g at an overpotential of 330 mV (vs. RHE) at ultralow loading (~0.005 g/cm 2 ). Among the compositions, Fe–Co–ZnO and amorphous Fe–Ni–ZnO show the best OER performance, delivering current densities of 2.00 and 3.04 mA/cm 2 , respectively, compared to 1.52 mA/cm 2 for Fe–ZnO.. This work establishes SBI–SIS as a versatile route for fabricating nm-thin, high-performance multicomponent oxide heterostructures on cost-efficient supports, enabling efficient catalyst utilization in electrochemical energy conversion application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mesoporous Thin Film Architectures: Addressing Material Demands through Molecular Self-Assembly

Mesoporous thin films spark interest across a wide range of disciplines due to their tunable nanostructures, large internal surface areas, and strong compatibility with planar optical, electronic, and microfluidic devices. While attention in the porous materials community has shifted toward macroporous or disordered nanoporous systems, a resurgence in mesoporous thin film research is underway, driven by new molecular self-assembly methods, advanced materials chemistry, and improved characterization techniques. The integration of high-χN block copolymer design, kinetically persistent micelle templating, and postdeposition processing protocols now allows control over structural parameters such as pore size, wall thickness, porosity, and connectivity. These advances have overcome many of the thermodynamic and processing constraints that previously limited widespread adoption. Rather than serving only as high-surface-area supports, mesoporous thin films are engineered as active interfaces where responsive chemistries and nanoscale confinement act in tandem. Embedding switchable ligands, thermoresponsive polymers, redox mediators, or ion-selective groups directly within the pore walls enables real-time control over transport, optical, and electrochemical properties. These capabilities open up new directions in adaptive coatings, gated membranes, and fast-response biosensors. To further expand their functional scope, mesoporous films are integrated into hierarchical and multicomponent architectures. Techniques such as triblock terpolymer templating, crack-directed assembly, and nanoimprint lithography allow for control over spatial organization on the micron and submicron scale and pore system orientation. This enables programmable anisotropy, enhanced molecular diffusion, and wavelength-selective photonic behavior, essential for next-generation sensing, catalysis, and energy applications. Such structural and functional complexity requires equally sophisticated characterization. Multimodal and in situ techniques can track material dynamics under operational conditions. Recent progress includes extended-range ellipsometric porosimetry (EP) for hierarchical architectures, vacuum EP for interface energetics, time-resolved EP for diffusion kinetics, and correlative AFM-SAXS mapping. The introduction of advanced neutron-based spectroscopies, particularly quasielastic neutron scattering (QENS), promises to provide real-time access to ion transport dynamics and segmental motion under nanoscale confinement, offering a path toward deeper mechanistic understanding of structure-performance correlations in mesoporous systems. This Account reflects the technical advances made and the interdisciplinary collaborations that have shaped our collective vision. The particular dimensions of mesopores enable us to subtly tune interactions at the molecular, interfacial, and mesoscopic levels that permit us to harness nanoconfinement. What emerges is a versatile, modular platform capable of chemical gating, energy transduction, and sensing with a level of tunability unmatched by other porous materials. We highlight critical challenges including the need for more robust large-area processing, a deeper understanding of dynamic behavior under cycling, and better integration with device-level architectures. Our strategies support the transition of mesoporous thin films into active high-performance components in next-generation energy, environmental, and biomedical systems.

oxides↗

Redistribution of Ru in Fe 2 O 3 –Ru Nanocatalysts through an Oxidative Pretreatment Improves Reverse Water–Gas Shift Activity

We have synthesized Fe–Ru nanoparticles via a solvothermal method to create catalysts for the reverse water–gas shift reaction and demonstrated the impact of reductive and oxidative pretreatments on both catalytic performance and structure. Catalytic testing showed improved activity after exposure to O 2 at 600 °C. In contrast, the activity became lower if then exposed to H 2 at 600 °C. Environmental scanning transmission electron microscopy and scanning electron microscopy showed that exposure to O 2 at 600 °C changes the morphology and completely oxidizes Fe into Fe 2 O 3 . Exposure to H 2 at elevated temperature caused Ru coalescence at the surface of the nanoparticle, forming clusters which decreased the optimization of Ru. Reoxidation of the particles exposed to H 2 , however, caused a redistribution of Ru that appears beneficial in maximizing Ru exposure and synergy with Fe oxide, with no major changes in the morphology and oxide structure. Furthermore, our diagnostics demonstrate the complex and reversible rearrangements possible in these multicomponent particles and the benefits of oxidative pretreatment to enhance or regenerate Fe–Ru catalysts in other important catalytic reactions such as Fischer–Tropsch synthesis.

Fe−Ru nanoparticles↗

Efficient Capture and Release of the Rare-Earth Element Neodymium in Aqueous Solution by Recyclable Covalent Organic Frameworks

Rare-earth elements (REEs) are present in a broad range of critical materials. The development of solid adsorbents for REE capture could enable the cost-effective recycling of REE-containing magnets and electronics. In this context, covalent organic frameworks (COFs) are promising candidates for REE adsorption due to their exceptionally high surface area. Despite having attractive physical properties, COFs are heavily underutilized for REE capture applications due to their limited lifecycle in aqueous acidic environments, as well as synthetic challenges associated with the incorporation of ligands suitable for REE capture. Here, in this work, we show how the Ugi multicomponent reaction can be leveraged to postsynthetically modify imine-based COFs for the introduction of a diglycolic acid (DGA) moiety, an efficient scaffold for REE capture. The adsorption capacity of the DGA-functionalized COF was found to be more than 40 times higher than that of the pristine imine COF precursor and more than four times higher than that of the next-best reported DGA-functionalized solid support. This rationally designed COF has appealing characteristics of high adsorption capacity, fast and efficient capture and release of the REE ions, and reliable recyclability, making it one of the most promising adsorbents for solid–liquid REE ion extractions reported to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Orientation microscopy–assisted grain boundary analysis for protonic ceramic cell electrolytes

Abstract Grain boundaries in protonic ceramic cell (PCC) electrolytes hinder proton transport, reducing interfacial conductivity. In multicomponent PCC electrolytes, the inclusion of sintering aids further accentuates the complexity of grain boundaries. In this study, we synthesize nanocrystalline BaCe 0.4 Zr 0.4 Y 0.1 Yb 0.1 O 3− δ thin films via pulsed laser deposition and analyze their grain boundary character distributions using orientation data collected by precession electron diffraction technique. The results reveal an anisotropic distribution of grain boundary characters, with notably high populations of 180°‐tilt and twist grain boundaries. These findings provide critical insights into identifying the predominant grain boundaries in this PCC electrolyte material, assessing the vast five‐dimensional grain boundary space.

Patel, Sooraj [School of Aerospace and Mechanical ↗

Short-range order parameter expansions for simple configurational energetics

Local chemical environments of multicomponent crystals are parametrized according to basis vectors of their irreducible invariant subspaces. These short-range order parameters enable Taylor expansions of configurational properties that easily incorporate additional couplings. As one example, expansions including long-range composition can describe the energies of many alloys more accurately than conventional cluster expansions while using far fewer neighbors and basis functions.

36 MATERIALS SCIENCE↗

Enhancing Hydrogen Production from Bioenergy Crops via Photoreforming

Photoreforming perennial bioenergy crops (willow, Miscanthus , and poplar) has the potential to produce H 2 with reduced environmental impacts. To understand the compositional effects of the biomass on the average rate of H 2 production over the first 30 min of reaction ( r H 2 ), the r H 2 values of model biomass component (i.e., cellulose, hemicellulose, and lignin) mixtures were compared with those from the raw biomass. The higher cellulose or hemicellulose content in multicomponent mixtures resulted in higher r H 2 , whereas lignin reduced the hydrogen production rate. However, with raw biomass, the ratio of biomass components alone did not determine the r H 2 via photoreforming, with rates of hydrogen production for different varieties of willow ranging between 1.9 μmol h -1 and 12.3 μmol h -1 , 11.8 μmol h -1 for a poplar, and 6.8 μmol h -1 for a miscanthus biomass. In addition, comparable r H 2 values of raw poplar and its extracted cellulose via an IonoSolv treatment indicated the possibility of using raw biomass materials without delignification for generating H 2 via photoreforming. Importantly, r H 2 was positively correlated with the interaction between water and the biomass, as assessed by NMR relaxation via an examination of the T 1 /T 2 ratio. A stronger water-biomass interaction resulted in a higher r H 2 . Genetic modification of biomass has been suggested as a putative way to improve the r H 2 of biomass with an enhanced interaction with water. This research enhances the understanding of factors influencing H 2 production from lignocellulosic biomass by photoreforming and supports the breeding and management of perennial biomass crops to maximize H 2 yields while minimizing land area requirements.

biomass↗

High-field superconducting halo in UTe 2

The heavy fermion material UTe 2 is a candidate topological superconductor that exhibits multiple magnetic field–induced superconducting phases. One such phase exists only at fields greater than 40 tesla, a considerable scale given its critical temperature of only 2 K. Here, in this work, we extend measurements of this state with fields outside of the bc crystallographic plane and reveal its core structure: The superconducting phase wraps around the b axis in a halo-like fashion and appears to be stabilized by a field component perpendicular to the magnetic easy axis. This angle dependence points to a multicomponent spin-triplet order parameter with a finite angular momentum of the Cooper pairs. The pairing mechanism remains enigmatic, and UTe 2 ’s specific magnetophilic superconducting tendencies seem incompatible with existing models for field-enhanced superconductivity.

Lewin, Sylvia K. [National Inst. of Standards and ↗