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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 325 records · Page 18

Cluster expansion by transfer learning for phase stability predictions

Recent progress towards universal machine-learned interatomic potentials holds considerable promise for materials discovery. Yet the accuracy of these potentials for predicting phase stability may still be limited. In contrast, cluster expansions provide accurate phase stability predictions but are computationally demanding to parameterize from first principles, especially for structures of low dimension or with a large number of components, such as interfaces or multimetal catalysts. We overcome this trade-off via transfer learning. Using Bayesian inference, we incorporate prior statistical knowledge from machine-learned and physics-based potentials, enabling us to sample the most informative configurations and to efficiently fit first-principles cluster expansions. Furthermore, this algorithm is tested on Pt:Ni, showing robust convergence of the mixing energies as a function of sample size with reduced statistical fluctuations.

36 MATERIALS SCIENCE↗

Simulating hindered grain boundary diffusion using the smoothed boundary method

Abstract Grain boundaries can greatly affect the transport properties of polycrystalline materials, particularly when the grain size approaches the nanoscale. While grain boundaries often enhance diffusion by providing a fast pathway for chemical transport, some material systems, such as those of solid oxide fuel cells and battery cathode particles, exhibit the opposite behavior, where grain boundaries act to hinder diffusion. To facilitate the study of systems with hindered grain boundary diffusion, we propose a model that utilizes the smoothed boundary method to simulate the dynamic concentration evolution in polycrystalline systems. The model employs domain parameters with diffuse interfaces to describe the grains, thereby enabling solutions with explicit consideration of their complex geometries. The intrinsic error arising from the diffuse interface approach employed in our proposed model is explored by comparing the results against a sharp interface model for a variety of parameter sets. Finally, two case studies are considered to demonstrate potential applications of the model. First, a nanocrystalline yttria-stabilized zirconia solid oxide fuel cell system is investigated, and the effective diffusivities are extracted from the simulation results and are compared to the values obtained through mean-field approximations. Second, the concentration evolution during lithiation of a polycrystalline battery cathode particle is simulated to demonstrate the method’s capability.

Materials Science↗

Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F)

An open‐source modeling platform, called Anaerobic Digestion Model No. 1 Fast (ADM1F), is introduced to achieve fast and numerically stable simulations of anaerobic digestion processes. ADM1F is compatible with an iPython interface to facilitate model configuration, simulation, data analysis, and visualization. Faster simulations and more stable results are accomplished by implementing an advanced open‐source library of numerical methods called Portable Extensive Toolkit for Scientific Computation (PETSc) to solve the ADM1 system of equations. Leveraging PETSc, ADM1F can consistently complete a steady‐state simulation under 0.2 s, over 99% faster than a benchmark ADM1 model implemented with MATLAB while achieving agreement of model outputs within 1% of those obtained with the benchmark model. For dynamic simulations, however, ADM1F has a computational speed advantage only when the influent characteristics update more frequently than every 4 h. The ability of ADM1F to be useful as a tool to study anaerobic digestion systems is demonstrated through two example implementations of ADM1F: (1) a two‐phase co‐digestion scenario evaluating the impact of the organic loading rate and the substrate composition on reactor performance and stability, and (2) a conventional digester scenario assessing the effectiveness of recovery strategies after disruptions that led to instability. These examples demonstrate how the high simulation speed and the convenience of the iPython interface allow ADM1F to complete complex analyses within minutes, much faster than computational strategies currently reported in the literature.

anaerobic co-digestion↗

Fluoro‐Ethylene‐Carbonate Plays a Double‐Edged Role on the Stability of Si Anode‐Based Rechargeable Batteries During Cycling and Calendar Aging

Abstract The energy storage density of Li‐ion batteries can be improved by replacing graphite anodes with high‐capacity Si‐based materials, though instabilities have limited their implementation. Performance degradation mechanisms that occur in Si anodes can be divided into cycling stability (capacity retention after repeated battery cycles) and calendar aging (shelf life). While cycling instabilities and improvement strategies have been researched intensively, there is little known about the underlying mechanisms that cause calendar aging. In this work, multiple electron microscope techniques are used to explore the mechanism that governs calendar aging from the sub‐nanometer‐to‐electrode scale. Plasma focused ion beam tomography is used to create 3D reconstructions of calendar aged electrodes and revealed the growth of a LiF‐rich layer at the interface between the copper current collector and the silicon material, which can lead to delamination and increased interfacial impendence. The LiF layer appeared to derive from the fluoro‐ethylene‐carbonate electrolyte additive, which is commonly used to improve cycling stability in Si‐based systems. The results reveal that additives necessary to improve cycling stability can cause performance degradation over the long‐term during calendar aging. The results show that high performing, stable systems require careful design to simultaneously mitigate both cycling and calendar aging instabilities.

25 ENERGY STORAGE↗

Rationalizing Acidic Oxygen Evolution Reaction over IrO 2 : Essential Role of Hydronium Cation

Abstract The development of active, stable, and more affordable electrocatalysts for acidic oxygen evolution reaction (OER) is of great importance for the practical application of electrolyzers and the advancement of renewable energy conversion technologies. Currently, IrO 2 is the only catalyst with high stability and activity, but a high cost. Further optimization of the catalyst is limited by the lack of understanding of catalytic behaviors at the acid‐IrO 2 interface. Here, in strong interaction with the experiment, we develop an explicit model based on grand‐canonical density function theory (GC‐DFT) calculations to describe acidic OER over IrO 2 . Compared to the explicit models reported previously, hydronium cations (H 3 O + ) are introduced at the electrochemical interface in the current model. As a result, a variation in stable IrO 2 surface configuration under the OER operating condition from previously proposed complete *O‐coverage to a mixture coverage of *OH and *O is revealed, which is well supported by in situ Raman measurements. In addition, the accuracy of predicted overpotential is increased in comparison with the experimentally measured. More importantly, an alteration of the potential limiting step from previously identified *O→*OOH to *OH→*O is observed, which opens new opportunities to advance the IrO 2 ‐based catalysts for acidic OER.

Mou, Tianyou↗

FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment (Final Report)

This report documents the FY25 Theory and Simulation Performance Target (TSPT) of developing an integrated modeling framework for fusion reactor design and assessment (FREDA). Over Q1-Q4, new capabilities were developed across both plasma and engineering domains and demonstrated on an example representation of a Compact Advanced Tokamak with a Dual Cooled Lead Lithium blanket. This represents a first-of-a-kind demonstration of coupled core-to-wall-to-engineering for a reactor. Self-consistent CESOL workflows were applied to provide core, pedestal, and SOL prediction; new modules were developed for energetic particle stability (FAR3D) and transport (TGLF-EP) analysis; and boundary plasma modeling (SOLPS-ITER, BOUT++/Hermes-3) was expanded to evaluate wall and divertor heat fluxes and interface with engineering thermal analysis. A parameterized CAD tool, TRACER, was expanded to generate medium-fidelity divertor, blanket, and coil geometries; OpenFOAM and Diablo workflows were applied for first-wall and divertor thermal analyses with helium cooling; and reduced-order models were created for high-mass-flux divertor cooling. Magnet multiphysics capabilities were verified between Elmer, Diablo, and a new MFEM-based solver, and workflows enable stress, thermal, and neutron-fluence analysis of TF coils with neutronics-driven heating. Nuclear and blanket analysis workflows were demonstrated, including tritium breeding, transport, and CFD-informed thermo-mechanical assessment. Preliminary multi-fidelity uncertainty quantification workflows were applied to boundary modeling codes and shown to achieve variance reductions with fewer high-fidelity boundary simulations. Key findings highlight the challenges of resolving the ITEP gap to find suitable balance between wall and divertor loads, neutron heating, and practical limits of PFC cooling. Next step priorities are to develop automated workflows to check boundary code convergence and detachment, implement tighter physics-engineering CAD provenance tracking, and inclusion of plasma-material interface models for SLAG and tungsten cracking behavior. Collectively, these developments establish sophisticated capabilities for predictive, multi-fidelity, whole-device modeling that integrates plasma physics, materials, magnets, and nuclear engineering to guide pathways to viable Fusion Pilot Plant design points.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effect of Ambient Organic Acids on the Water Structure at ${\rm TiO}_{2}$ Interfaces

A molecular-level understanding of the effects of ambient organic compounds on the wettability of titanium dioxide ( ${\rm TiO}_{2}$ ) surfaces is relevant to many of its energy-related and environmental applications. Herein, we focus on two common atmospheric carboxylic acids, formic and acetic acid, and characterize their adsorption/ desorption at the aqueous interfaces of anatase and rutile ${\rm TiO}_{2}$ using molecular dynamics with an ab initio deep neural network potential. Our simulations show that these acids prefer to be localized in the interfacial water layers close to the ${\rm TiO}_{2}$ surface where they are stabilized by the interaction/exchange of their acid proton with a surface oxygen, rather than chemisorb at the surface Ti sites by displacing the adsorbed water. Notably, these acids make the surface of anatase hydrophobic, whereas the larger fraction of adsorbed water dissociation can offset their effect on rutile. Furthermore, these results provide a picture where carboxylic acids control the wettability of ${\rm TiO}_{2}$ largely through acid-base chemistry at the interface rather than chemisorption on the oxide surface, a finding that can help improve the design of self-cleaning surfaces and photocatalytic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rationalizing Acidic Oxygen Evolution Reaction over IrO 2 : Essential Role of Hydronium Cation

The development of active, stable, and more affordable electrocatalysts for acidic oxygen evolution reaction (OER) is of great importance for the practical application of electrolyzers and the advancement of renewable energy conversion technologies. Currently, IrO 2 is the only catalyst with high stability and activity, but a high cost. Further optimization of the catalyst is limited by the lack of understanding of catalytic behaviors at the acid-IrO 2 interface. Here, in strong interaction with the experiment, we develop an explicit model based on grand-canonical density function theory (GC-DFT) calculations to describe acidic OER over IrO 2 . Compared to the explicit models reported previously, hydronium cations (H 3 O + ) are introduced at the electrochemical interface in the current model. As a result, a variation in stable IrO 2 surface configuration under the OER operating condition from previously proposed complete *O-coverage to a mixture coverage of *OH and *O is revealed, which is well supported by in situ Raman measurements. In addition, the accuracy of predicted overpotential is increased in comparison with the experimentally measured. More importantly, in this study, an alteration of the potential limiting step from previously identified *O→*OOH to *OH→*O is observed, which opens new opportunities to advance the IrO 2 -based catalysts for acidic OER.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis and Evaluation of Cu@ZnO Core@Shell Nanowires for Use in the Carbon Dioxide Thermal Reduction Reaction

Copper-based core@shell nanomaterials are of interest for the catalytic hydrogenation of carbon dioxide toward value-added products. In this context, we have developed a facile, microwave-based procedure for the reliable and reproducible synthesis of Cu@ZnO core@shell nanowires. A systematic assessment of the effect of rationally varying various reaction conditions on this protocol was completed in order to better evaluate the growth process of these core–shell motifs. We determined that among different reaction parameters, it was the critical role of reaction time which enabled the quantitatively reliable growth of external shells with tunable thicknesses of up to 20 nm. As a demonstration of the material’s practical viability, catalytic testing was subsequently performed for the reverse water–gas shift reaction (CO 2 + H 2 → CO + H 2 O), with the evolution of the process followed with in situ X-ray diffraction and X-ray absorption spectroscopy in order to probe structural changes and gauge stability. These tests found the catalysts to be effective at converting CO 2 to CO, with notable stability detected in the shell layer and no observed alloying between copper and zinc. Furthermore, our studies support the idea that the Cu–ZnO and CuO x –ZnO interfaces are essential for the effective activation of CO 2 and H 2 .

36 MATERIALS SCIENCE↗

Design of lightweight BCC multi-principal element alloys with enhanced hydrogen storage using a machine learning-driven genetic algorithm

Body-centered cubic (BCC) based multi-principal element alloy (MPEA) hydrides have demonstrated significant potential for compact and efficient hydrogen storage. In this work, we first leverage machine learning (ML) models to predict the hydrogen affinity, storage capacity and phase stability of BCC MPEAs, creating a unique hydrogen-to-metal (H/M) predictor for materials with unprecedented performance. We developed a metaheuristic optimizer high-throughput framework by interfacing ML models with a genetic algorithm for the accelerated search of {Mg, Al, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Nb, Mo} based lightweight BCC MPEAs with improved hydrogen storage characteristics. We report five new MPEAs with a predicted gravimetric hydrogen storage capacity of around 3.5 wt% or more, including Cr 0.09 Mg 0.73 Ti 0.18 (4.25 wt% H) and Cr 0.21 Nb 0.11 Ti 0.35 V 0.33 (3.5 wt% H). The electronic structure of the top-performing composition, Cr 0.09 Mg 0.73 Ti 0.18 , was analyzed using density functional theory (DFT) to understand the reasons for its improved hydrogen storage properties compared to TiFe (1.90 wt% H), LaNi 5 (1.37 wt% H) or BCC MPEAs like TiVNbCr (3.70 wt% H). Temperature-dependent molecular dynamics (MD) studies were further performed on optimized BCC MPEAs to qualitatively study hydrogen mobility and analyze the effect of different elemental composition on bulk hydrogen diffusion. Our findings demonstrate how a ML assisted genetic algorithm framework can be used for efficient search of stable, lightweight and cost-effective MPEAs while minimizing the need for expensive ab initio calculations.

DFT↗

Stabilizing Iodine in 2D Mixed Halide Perovskites: Dion–Jacobson Versus Ruddlesden–Popper Phases

Iodine electrochemistry plays an important role in driving iodide‐oxidation induced halide migration in 3D halide perovskites. When subjected to light illumination or electrochemical bias, mixed halide perovskites undergo halide segregation followed by iodine expulsion from the crystal lattices. To mitigate such intrinsic halide ion mobility in 3D perovskites, lower‐dimensional (2D) perovskites are employed as barriers to stabilize the perovskite layers. Interestingly, 2D halide perovskites also exhibit halide ion mobility that is dependent on the binding configuration, viz., Ruddlesden–Popper (RP) and Dion–Jacobson (DJ) phases. Hybrid RP‐DJ perovskites with a mixed Br:I ratio of 50:50 show increased stability following continuous photoirradiation. Spectroscopic studies that probe iodine migration and expulsion in photoirradiated 2D films of different configurations are presented here. The effective strategy of blending two different 2D phases (RP‐DJ) offers new opportunities to develop stable 2D/3D perovskite interfaces in solar cells.

2D halide perovskites↗

The Impact of Catalyst Layer Properties and Transport Layer Interactions on Rutile Iridium Oxide Anode Durability in Proton Exchange Membrane Electrolysis

The performance and durability of proton exchange membrane electrolyzers are governed by the interplay between catalyst inks and integration, the resulting catalyst layer (CL) structure, and the interface between the CL and porous transport layer (PTL). In this study, we examine the impact of these factors on cell performance and degradation using rutile IrO2 as the anode catalyst. The two commercial rutile IrO2 catalysts differ from each other and from the amorphous benchmark in agglomerate size and ink stability. This has implications for CL morphology and electronic connectivity. In the context of long-term pressurized operation for up to 1000 h, the selection of the PTL has a marginal effect on the durability of CLs with good structural and compositional properties, whereas poorly structured CLs demonstrate evident degradation when used with certain PTLs. Poor CL properties amplify the negative impact of non-ideal CL/PTL interfaces, demonstrating the importance of CL/PTL interface engineering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of microalloying additions on microstructural evolution and thermal stability in cast Al-Ni alloys

Enhancement of thermal stability in Al-Ni alloys through microalloying with slow-diffusing elements, specifically Zr, has been previously reported which is attributed to Zr segregation at the Al/Al 3 Ni interface. In this study, we explore the influence of microalloying Al-Ni alloys with Zr, Ti, V, and Fe on microstructural evolution, hardness, and electrical and thermal conductivity across a range of heat-treatment temperatures from 300 to 450 °C. The distribution of microalloying elements and precipitates after heat treatment is characterized using atom probe tomography (APT). Our investigation confirms Zr segregation to the Al/Al 3 Ni interface, while similar interfacial segregation is absent with the addition of Ti, V, and Fe. Additionally, our analysis of the Al 3 Ni microfiber morphology reveals that their coarsening and spheroidization rates are similar with and without interfacial segregation; thus, retaining the fiber reinforcement through interfacial segregation of slow diffusing elements may not be an effective strategy. Precipitation of L1 2 nanoparticles was found to be the dominant mechanism affecting enhanced hardness and electrical conductivity in Al-Ni-Zr alloys, attributed to precipitation strengthening and solute depletion, respectively. Similar precipitation was not observed for additions of Ti, V, and Fe following heat treatment. We provide a thermodynamic explanation for this limitation. Furthermore, the findings of this study suggest that an effective approach for designing Al-Ni alloys should involve prioritizing microalloying elements to maximize L1 2 precipitation and minimize solute content in the FCC-Al matrix post heat treatment, rather than focusing on Al/Al3Ni interfacial segregation.

36 MATERIALS SCIENCE↗

Improved charge extraction in inverted perovskite solar cells with dual-site-binding ligands

Inverted (pin) perovskite solar cells (PSCs) afford improved operating stability in comparison to their nip counterparts but have lagged in power conversion efficiency (PCE). The energetic losses responsible for this PCE deficit in pin PSCs occur primarily at the interfaces between the perovskite and the charge-transport layers. Additive and surface treatments that use passivating ligands usually bind to a single active binding site: This dense packing of electrically resistive passivants perpendicular to the surface may limit the fill factor in pin PSCs. We identified ligands that bind two neighboring lead(II) ion (Pb 2+ ) defect sites in a planar ligand orientation on the perovskite. We fabricated pin PSCs and report a certified quasi–steady state PCE of 26.15 and 24.74% for 0.05– and 1.04–square centimeter illuminated areas, respectively. The devices retain 95% of their initial PCE after 1200 hours of continuous 1 sun maximum power point operation at 65°C.

Science & Technology - Other Topics↗

Topological grain boundary segregation transitions

Engineering the structure of grain boundaries (GBs) by solute segregation is a promising strategy to tailor the properties of polycrystalline materials. Solute segregation triggering phase transitions at GBs has been suggested theoretically to offer different pathways to design interfaces, but an understanding of their intrinsic atomistic nature is missing. Here, we combined atomic resolution electron microscopy and atomistic simulations to discover that iron segregation to GBs in titanium stabilizes icosahedral units (“cages”) that form robust building blocks of distinct GB phases. Owing to their five-fold symmetry, the iron cages cluster and assemble into hierarchical GB phases characterized by a different number and arrangement of the constituent icosahedral units. Our advanced GB structure prediction algorithms and atomistic simulations validate the stability of these observed phases and the high excess of iron at the GB that is accommodated by the phase transitions.

36 MATERIALS SCIENCE↗

Characterization and Damping Control of Mechanical Connections to Improve Performance of Horn Stripline

Magnetic focusing horns are critical components for creating a stable beam of neutrinos for neutrino facilities, such as the Long Baseline Neutrino Facility (LBNF) and the Neutrinos and Main Injector (NuMI) beam lines at Fermilab. The pulsed magnetic horns are powered by high current electricity through long striplines. In addition to requirements for low inductance and voltage standoff, the striplines must survive in a harsh radiation environment for the operational life of the component, specified as the 100 million pulses requirement for LBNF. Each stripline assembly consists of four (eight layers that splits off to 2 pairs of four layers at the horn interface) layers of Al 6101-T6. As an electromechanical system, the stripline layers are bolted together with ceramic isolators for electrical insulation and connections must facilitate passive cooling and mechanical stability. The striplines experience vibrational force in addition to clamping force, repetitive thermal and electro-magnetic loading. The holes of stripline plates for ceramic joints represent one of the weak links for potential failure [1,2]. By characterizing the contact behavior of these joints and optimizing their damping properties through finite element analysis and experimental modal analysis, stripline performance and longevity can be improved. This study not only helps predict the behavior of the striplines but also improves their performance to meet the required operational lifetime.

Liu, Zunping [Fermilab]↗

Integrated Molten Salt Reactor Modeling Capabilities in NEAMS Thermal Hydraulics Tools

The DOE neams program supports a full range of computational thermal fluids analysis capabilities and code developments for a broad range of advanced reactor concepts. The research and development approach under the thermal fluids technical area synergistically combines three length and time scales in a hierarchical multi-scale approach. To enable multi-scale thermal fluids capability using these codes, a key joint effort has been underway to develop an integrated system- and engineering-scale thermal fluids analysis capability, through integration of SAM and Pronghorn codes, both based on the MOOSE framework. This report summarizes recent advances in developing an integrated system- and engineering-scale modeling capability for the msr concept, which has gained significant interest in recent years. A consistent framework was established by coupling Pronghorn and SAM through the Saline interface, with thermophysical properties provided by the Molten Salt Thermal Property Database (MSTDB-TP). Further improvements were made to the coupling schemes and domain-overlapping strategies, enhancing the stability and robustness of multi-code simulations. Verification and validation efforts demonstrate the accuracy of this integration across a range of benchmark problems, including one-dimensional heated pipe flows, three-dimensional natural convection loops with evolving isotopic compositions, and \gls{msre} demonstration cases. Within Pronghorn, new capabilities were introduced to model corrosion and noble-metal plating phenomena, supported by an extended thermal-hydraulics framework and refined turbulence treatments. To capture two-phase flow behavior, a multiphase Euler–Euler model was implemented in Pronghorn, including advanced closure relations, high-resolution advection techniques, and capillary force reconstruction. Preliminary verification cases confirm the fidelity of the approach, while planned validation efforts target canonical multiphase benchmarks and application to msr components such as the msre pump bowl. Finally, updates to SAM’s msr mass transfer modeling were extended to consider noble gas migration into porous structures like graphite. The point kinetics model was updated to include reactivity feedback contributions from any defined species, such as xenon. The gas transport model was expanded for applicability to gas mixtures, bubble efflux phenomena, and species transport between liquid and gas phases. A selection of multi-scale Sherwood number correlations from MOSCATO/NekRS and multi-phase correlations from literature have been added for improved accuracy in calculating mass transfer coefficients. A companion effort on developing system-level redox corrosion has also been incorporated into SAM. Collectively, these enhancements strengthen the predictive capability of SAM and Pronghorn for simulating MSR thermal-hydraulics, corrosion, multiphase behavior, and fission-product transport, providing a more complete toolset for design, safety analysis, and licensing support of next-generation \gls{msr}s.

42 - ENGINEERING↗