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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Practical guide to Parsing MCNP Inputs: Lessons Learned from Implementing Context-Free Parsing in MontePy

Monte Carlo N-Particle (MCNP) is a widely used Monte Carlo transport solver that began development in the 1960’s. Due to this MCNP input files uses a custom input syntax, for which there are no off-the-shelf parsing libraries available. For MontePy to create an effective Object-Oriented interface for MCNP input files, an context-free parser was implemented to be able to fully parse the files. MontePy uses a number of shortcuts and optimizations to avoid creating a single universal input file parser. . These lessons can be applied to working with the many other custom input syntax languages persistent throughout the nuclear industry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Cyber-Informed Engineering (CIE) Guide for States

The Cyber-Informed Engineering (CIE) Guide for States provides state energy offices, public utility commissions, and partner organizations with a structured framework for integrating cyber-resilient engineering practices into energy planning, grantmaking, interconnection processes, and workforce development. As grid digitalization and the adoption of distributed energy resources accelerate, states face expanding cyber-physical risks that traditional cybersecurity measures alone cannot fully address. CIE offers a proactive, consequence-focused engineering methodology that emphasizes eliminating or mitigating high-impact failure modes through design, physical controls, and operational safeguards. The guide outlines the 12 core CIE principles, demonstrates their application through state-focused use cases—including grant evaluation rubrics, interconnection reviews, allow-list development, and training programs—and provides practical tools such as scoring frameworks, impact assessment methods, and implementation checklists. It also highlights pathways for state–utility collaboration and opportunities for technical assistance from national laboratories. By adopting CIE, states can enhance grid reliability, reduce lifecycle costs, strengthen supply-chain assurance, and foster a security-aware engineering culture that aligns with broader resilience and modernization goals. November 2025

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Toward Stable, High‐Energy, Partially Disordered Mn‐Rich Spinel Cathodes by Revealing and Mitigating Surface Degradation

Mn-rich cathodes balance performance and sustainability but suffer from limited cyclability due to Mn dissolution and cathode-to-anode crosstalk. The Jahn-Teller (J-T) effect of Mn 3+ is often linked to the above phenomena, such as in spinel LiMn 2 O 4 . However, in typical voltage ranges, significant Mn 3+ only appears near the end of discharge, highlighting the need to reassess its role in driving Mn dissolution, structural degradation, and battery performance. Here, the spinel cathode's degree of disorder is tailored to expand the Mn redox range, enabling segmentation into J-T active and less active voltage ranges. Cycling at segmented voltage windows reveals surface degradation mechanisms with and without the major J-T effect. Despite a stronger J-T effect below 3.6 V vs. Li/Li + , Mn dissolution is less significant than above 3.6 V. Expanding the cycling window to 2.0–4.3 V causes severe degradation as the J-T active range induces a tetragonal phase and Mn 2+ -rich surface, driving Mn dissolution and consuming Li-ion inventory in full cells. Reducing electrolyte acidity minimizes Mn 3+ disproportionation, enabling a stable dopant-free Mn-only cathode with a 250 mAh g −1 specific capacity. These findings demonstrate that full cells using Mn-rich cathodes have the potential to avoid the notorious crosstalk problem through electrolyte engineering.

25 ENERGY STORAGE↗
DOE OSTI2026

Giant Magnetostriction in Ferrimagnetic SmFe 5 As 3

Magnetostrictive materials are of interest not only from a fundamental perspective but also for their potential applications, spanning spintronics to energy harvesting. A new magnetostrictive material—SmFe 5 As 3 —reveals a complex interplay between magnetostriction, magnetic properties, and the crystal structure behavior. The ground state of SmFe 5 As 3 is ferrimagnetic, as evidenced by magnetic susceptibility data, band-structure calculations, and XANES measurements. At T m1 = 28 ± 4 K, part of the Fe sublattice reorients, transitioning into a ferromagnetic state. This is followed by an entrance into the paramagnetic state at T m2 = 76 ± 4 K. The effects observed in the magnetic measurements are accompanied by structural phase transitions. All three phases—below T m1 , between T m1 and T m2 , and above T m2 —are described by the same structural motif of the UCr 5 P 3 type (monoclinic space group P2 1 /m), differing only in the degree of deformation of the Fe–As framework. The new material exhibits giant magnetostriction of 2500 x 10 -6 . Dilatometry measurements on a SmFe 5 As 3 single crystal indicate strongly diverse behavior, exhibiting not only negative, but also zero, as well as positive thermo-elastic effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

X‐Ray Absorption Studies of Local Structure of Dilute Ionic Species in Molten Salts

Molten salts are crucial materials with exceptional properties that make them suitable for applications such as heat transfer media, coolants, and liquid fuels in molten salt nuclear reactors and the concentrated solar power industry. Understanding their properties requires unraveling the intricate mysteries of their structure. To achieve this, advanced characterization tools are essential. Among various techniques, X‐ray absorption fine structure (XAFS) stands out as a versatile method capable of studying the structure of molten salts under in situ conditions. This review highlights recent advancements in the application of XAFS for investigating the local structure of molten salts, discusses its limitations and potential improvements, and explores complementary approaches such as simulations, machine learning, and correlative experimental methods.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

A Machine Learning Approach to Quantitative Analysis of Enamel Microstructure from Scanning Electron Microscopy Images

Dental enamel, the outermost tissue of mammalian teeth, must withstand a lifetime of wear and cyclic contact. To meet this demand, enamel possesses a combination of high hardness and resistance to fracture, properties that are typically mutually exclusive. The impressive damage tolerance has been attributed largely to decussation of the enamel rods, the principal unit of its microstructure. As such, enamel is inspiring the design of next‐generation structural materials. However, quantitative descriptions of the decussated enamel rod microstructure remain limited due to challenges encountered in applying computed tomography and in acquiring quality images appropriate for traditional digital processing methods. Here, a machine learning segmentation method is applied to images of the enamel obtained using scanning electron microscopy to support quantitative analysis of the microstructure. A pretrained convolutional neural network is used to expand the input training image dataset to allow the training of a random forest classifier, which ultimately segments the image with a very small training set ( n = 3 images). A validation of this segmentation method is presented, in addition to its application to calculate relevant microstructural parameters for images of tooth enamel from selected mammalian species. The methodology applied here is equally applicable to other hard tissues.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Smaller and faster: a review of conventional and nanocalorimetry techniques for determining thermophysical properties of nuclear materials

Thermal analysis of nuclear materials is critical for the advancement of nuclear technology. The heat effects associated with heat capacity, phase transformation, and radiation damage can be measured with conventional calorimeters. However, conventional calorimetric techniques are often restricted in terms of heating rate and sample mass, especially when studying the limited amounts of materials subject to extreme conditions. In this review, we summarize conventional calorimetric studies of critical thermophysical and thermochemical properties of pure actinide metals (U, Np, Am, Pu), fast reactor metallic fuel alloy systems (U–Zr, U–Pu–Zr, Pu–U, Pu–Zr), and actinide oxides that are primary constituents or transmutation products in light water reactor fuel rods (U–O, Np–O, Am–O, Pu–O, Pu–U–O). Adiabatic and drop calorimetry have been the primary techniques used for these studies, however the development of fast scanning calorimetry using micro-electro-mechanical-based systems allows determination of thermodynamic properties from smaller sample masses. We report recent investigations that leverage the fast heating rates of nanocalorimetry by itself or combined with other characterization techniques. Furthermore, we then discuss opportunities for nanocalorimetry to provide solutions to some of the technical challenges inherent in thermal analysis of nuclear materials, namely a reduction in sample activity, emulating heating transients, investigation of phase evolution in irradiated samples, and characterization of radiation damage evolution. Nanocalorimetry has the potential to significantly advance the understanding of thermophysical properties in nuclear materials and thus accelerate the development of nuclear technology.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Implementation of Triply Periodic Minimal Surfaces (TPMS) as surface objects in OpenMC

Triply Periodic Minimal Surfaces (TPMS) represent a promising geometry for future fuel designs due to their significant surface-to-volume ratio, which facilitates efficient cooling of nuclear fuel, a crucial factor for safety and efficiency. Demonstrating the remarkable capabilities of TPMS fuel requires initial modeling and simulation. This paper presents an implementation of TPMS in the Monte Carlo code OpenMC, enabling reactor physics modeling of TPMS. Here, the primary advantages over traditional methods using CAD files include reduced memory requirements for computations and high-fidelity implementation. This implementation has been tested against CAD files loaded in Serpent2, yielding promising results with low biases in the $k_{\textrm{eff}}$, comparable to biases in the material balance sheet. The implementation presented in this work will be used in future reactor physics computations related to new reactor designs involving TPMS-based fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Butterfly valve performance factors using the multiphysics object oriented simulation environment

Butterfly valves are typically used in nuclear reactors to control incompressible fluid flow with high inlet velocities. Performance factors for butterfly valves include the pressure drop across the valve and the loss coefficient from which hydrodynamic torque and flow coefficients can be computed. This work explores a computational fluid dynamics approach for butterfly valve performance factors using the open-source Multiphysics Object Oriented Simulation Environment (MOOSE) framework. While MOOSE is often used in the nuclear energy modeling and simulation community for simulations ranging from fuel characterization to heat pipe simulation, this work employs the MOOSE open-source Navier–Stokes solver capability for simulating butterfly valve performance factors and compares those to experimentally measured results from the Advanced Test Reactor at Idaho National Laboratory at Reynolds numbers in the order of 10 6 for the partially opened configuration. The MOOSE framework results are compared against experimentally measured butterfly valve performance factors across five valve opening angles using meshes with order 10 4 – 10 5 elements. This validation serves to enable MOOSE-based multiphysics simulations incorporating the open-source Navier–Stokes module.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Uncertainty quantification of a physics-informed model based on sparse identification of a Thermal Energy Distribution System

Integrated energy systems (IES)s are crucial for enhancing the economy and efficiency of power generation sources (e.g., nuclear energy) necessary to unleash American energy dominance. These systems can be integrated with thermal energy storage (TES) and intermittent renewable energies to optimize overall energy use, peak-load regulation, and demand-side responses. However, the stabilization of energy generation, transport, and utilization introduces operational complexities that exceed the challenges of managing each sub-component individually. Currently, though IESs rely on human operators for efficiency and stability, reducing human error risk and enhancing performance through automation is highly desirable. Recent advances at Idaho National Laboratory have demonstrated successful control of the Thermal Energy Distributed System (TEDS). However, the automatic control system depends on a deterministic Sparse Identification of Nonlinear Dynamics with Control (SINDyC) model, which are trained based on simulation data from physics-based simulations. Because of uncertainties in physics-based simulation, SINDyC model results in large discrepancies against experimental data and cannot be reliably used in automatic control. In this paper, we present an innovative approach to address these discrepancies by quantifying uncertainties and developing a more robust model. We first generated trajectories by using first-principles physics codes to encapsulate the experiment. Next, we trained thousands of models by randomly sampling these trajectories. We then collapsed all those models into one probabilistic SINDyC by fitting a multivariate Gaussian distribution onto the resulting coefficient’s distribution. Despite its simplicity, our approach successfully produced 95% confidence intervals that captured the experimental trajectories. It even did so with a higher probability and better U-pooling score across six of the seven relevant quantities of interest (QoIs), as compared to other classical approaches. In conclusion, ongoing research is focusing on generating new experimental trajectories to validate this approach, and on employing Bayesian calibration to refine parametric uncertainties and guide future model development efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Development of a conduction-based model for analyzing frozen startup of alkali-metal heat pipes

One key area of interest in heat pipe modeling/simulation is to analyze the startup behavior of the liquid-metal heat pipes (LMHPs) from a frozen state. This so-called ‘frozen startup’ process involves a complex set of nonlinear mass and heat transport phenomena, including phase transitions from solid to liquid and vapor, multiphase interactions, microporous wick flow, and compressible vapor dynamics. The complexity of these processes makes it challenging to simulate LMHP’s frozen startup using conventional numerical methods or commercial computational fluid dynamics (CFD) software. This paper presents a simplified conduction-based modeling approach that can provide practical insights into the entire LMHP frozen startup process, while alleviating the challenges of modeling its complex physics. The theoretical foundation and physical assumptions of the proposed model are based solely on heat-conduction equation, allowing for a more tractable simulation without sacrificing essential physical accuracy. The proposed model was implemented in a commercial CFD software, and its prediction was compared with the experimental data obtained from sodium heat-pipe startup experiments. The comparison highlights the proposed model's ability to capture the transient thermal behavior of LMHP during frozen startup. This study not only validates the conduction-based frozen startup modeling method but also shows its potential as a practical and efficient tool for understanding the startup performance of the LMHP systems.

Microreactor↗
DOE OSTI2025

Effects of iron carbide crystal phases and dopants on the conversions of CO 2 into ethylene

The density functional theory method was used to investigate the conversions of CO 2 to ethylene formation on two common iron carbide surfaces: Fe 3 C(0 1 0) and Fe 5 C 2 (1 1 1). Based on the structure relaxation of reaction intermediates and the elementary reaction transition states. We deduced the most competitive reaction pathways for ethylene production. The main CO 2 -to-ethylene routes and the competition of side products, CO and CH 4 , are discussed. Our analyses showed that CO 2 conversion is surface structure sensitive, whereas CH 4 and C2+ hydrocarbon formations depend on the reactivity of native C atoms in the carbides. To modify the intrinsic catalyst performance, mixing dopants in Fe catalysts is an effective strategy. Furthermore, we demonstrate that doping Zn and Zr can alter the local electronic structure and enhance CO 2 adsorption on the catalyst surface.

CO2 hydrogenation↗
DOE OSTI2025

Current understanding of Oxidative Coupling of Methane (OCM) reaction over supported Mn-Na 2 WO 4 catalysts

This perspective reviews the current understanding of the Oxidative Coupling of Methane (OCM) reaction over the supported Mn-Na 2 WO 4 /SiO 2 catalyst, with a focus on recent insights gained from state-of-the-art in-situ and operando spectroscopic characterization and chemical probe experiments under controlled environments. The supported Mn-Na 2 WO 4 /SiO 2 catalyst exhibits dynamic structural changes during the OCM reaction, involving multiple reactive lattice and adsorbed oxygen species, each associated with different oxide phases. These oxygen species play distinct roles in various steps of the OCM mechanism. The catalytic active sites for activation of CH 4 are associated with isolated surface Na-WO x sites on the SiO 2 support and the role of surface MnO x sites on SiO 2 is to oxidatively dehydrogenate C 2 H 6 to C 2 H 4 . Furthermore, this paper provides a detailed discussion of these roles and also introduces new experimental data from Temporal Analysis of Products (TAP) studies to clarify the ongoing debate in the literature regarding the contributions of lattice versus adsorbed oxygen species in OCM reaction product formation. Additionally, recommendations are offered for optimizing the performance of supported Mn-Na 2 WO 4 /SiO 2 catalysts to enhance CH 4 activation and C 2 product selectivity.

03 - NATURAL GAS↗
DOE OSTI2025

Mesoscale modeling of restructuring in high burnup UO 2 fuel

Here, this work aims to simulate the restructuring behavior observed in different regions of high burnup fuel, providing a first-of-its-kind restructuring model for the dark zone and rim region of high-burnup UO 2 fuel. We employed a grand-potential-based phase-field model to concurrently evaluate subgrain formation and the growth of fission gas bubbles within the fuel. An energy-based subgrain formation criterion was introduced to simulate the restructuring process. The effects of different initial conditions and different modeling parameters were systematically studied to capture how each of these parameters influences the characteristics of the restructured fuel. Subgrain formation was observed to begin around existing fission gas bubbles and proceed toward triple junctions, grain boundaries, and grain interiors. Restructuring was demonstrated to be influenced by a combination of initial dislocation densities, burnup rate, subgrain formation rate, and temperature. Under a given subgrain formation rate, the rate of restructuring increases with rising fuel temperature. A restructuring bias was observed within the microstructure, due to the variation in defect accumulation when comparing different grains. Microstructures corresponding to the dark zone and rim region can be obtained by parameterizing the model with the appropriate defect production rate, as determined based on the burnup rate and temperature. Furthermore, bubble size and distribution do not significantly affect the rate of restructuring. The predicted microstructures are consistent with experimental observations of the restructured regions. Finally, we present a correlation demonstrating the evolution of the restructuring volume fraction as a function of local burnup.

UO2↗
DOE OSTI2025

Diffusion behavior of lanthanide fission products in bcc Fe cladding: A first-principles study

Fuel-cladding chemical interaction poses significant challenges in nuclear reactors, where fission products generated from nuclear fuel interact with Fe-based cladding materials, potentially compromising their structural integrity. This study investigates the diffusion behavior of lanthanide fission products, Lanthanum (La), Cerium (Ce), Praseodymium (Pr), and Neodymium (Nd), within body-centered cubic (bcc) Fe cladding using the density functional theory, nudged elastic band method, and self-consistent mean field theory. Our results reveal significant vacancy binding energies, particularly with the 1st and 2nd nearest neighbors, which diminish beyond the 5th nearest neighbor, with La exhibiting the strongest binding affinity, followed by Nd, Ce, and Pr. The nudged elastic band calculations indicate significant high barriers for the dissociation of 1st nearest neighbor vacancy-solute pairs for all fission products. The tracer diffusion coefficients of these fission products were derived in an Arrhenius form, with a magnetic correction that accounts for the high-temperature paramagnetic state. The significant trapping effect of vacancies caused by a very dilute concentration of fission products reduces vacancy mobility, potentially leading to modifications in point defect supersaturation, void nucleation, and swelling under irradiation. These represent critical challenges for irradiated cladding materials. The tracer diffusion coefficients indicate that Nd diffuses the fastest, followed by La, Ce, and Pr. Furthermore, this study provides essential insights for understanding fission product transport in cladding materials and informs future design strategies to mitigate fuel-cladding chemical interaction, ultimately enhancing nuclear reactor safety and performance.

Diffusion↗
DOE OSTI2024

IASCC of 304 SS in BWR environments: Effects of post-irradiation annealing and surface condition

To investigate the impact of low-temperature post-irradiation annealing (PIA) on the stress corrosion cracking of neutron-irradiated 304 stainless steel, constant extension rate tests were conducted in simulated boiling water reactor normal water chemistry (BWR-NWC) and hydrogenated water chemistry (HWC) environments. Ten tensile samples, comprising five as-irradiated and five PIA specimens, were prepared by electropolishing the gauge section of electric discharge machined (EDM) samples. Here, the annealing treatment reduced the yield strength from approximately 550 MPa to around 425 MPa and significantly restored the ductility and the strain hardening capability of the alloy. Consequently, the susceptibility of this material to irradiation-assisted stress corrosion cracking (IASCC) was effectively mitigated, which is more prominent in HWC, as evident from fractography, which indicated a decreased propensity for intergranular (IG) fracture. Furthermore, it was observed that the polished surface facilitated crack initiation more readily than the EDM surface, suggesting that the EDM process suppressed crack initiation to some extent.

Crack initiation↗
DOE OSTI2025

Corrosion of 316 L stainless steel under the natural circulation of molten NaCl-MgCl 2 salt

The corrosion behavior of 316 L stainless steel (SS) was studied via the natural circulation of molten eutectic NaCl-MgCl 2 salt through a microloop. The post-corrosion tested 316 L SS microloop sections were characterized with microscopy techniques to determine the microstructural and microchemical changes that occurred at the alloy/salt interface. It was found that 316 L SS showed heterogeneous dissolution at the hot-leg, whereas deposition of corrosion products occurred at the cold-leg. For the first time, experimentally obtained molten salt flow-induced corrosion of 316 L SS results were combined with computational thermodynamic-kinetic models to validate the dissolution and deposition in terms of elemental compositional changes at the alloy/salt interface. The thermodynamic-kinetic modeling predicted that the heterogeneous dissolution of Cr and Fe from the hot-leg section of 316 L SS persisted throughout the salt circulation. The model also estimated that, despite Cr deposition starting earlier than Fe, the total redeposition of Fe is expected to be significantly greater than that of Cr over the circulation of salt. Furthermore, the modeling accurately predicted the subsurface enrichment of Mo which is attributed to the reduced Cr activity and the relatively higher diffusion rate of Mo within the alloy matrix. Here, the agreement between modeling and experimental results confirms that Fe chlorides dissolve at the hot-leg and subsequently deposit at the cold-leg due to activity changes driven by the thermal gradient. By contrast, Cr was not detected in the cold-leg deposits, which is attributed to its weaker temperature dependence on activity, limiting its redeposition under these conditions.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Interactive effects of precipitation, temperature, and grazing pressure on the net ecosystem carbon balance of grazing lands across the continental United States

Grazing lands cover approximately one-third of the contiguous United States, support much of the nation's beef production, and are an important component of the U.S. terrestrial carbon budget. In this study, we quantified net ecosystem carbon balance (NECB), the net status of grazing lands as a carbon sink (C-sink) or source (C-source) and a key determinant of soil health and productivity. Our primary objective was to synthesize multiple years of annual NECB across heterogeneous grazing lands across the continental U.S and evaluate annual NECB against physical drivers (mean annual precipitation (MAP), mean annual temperature (MAT), vegetation, and moisture condition) and management practices (grazing pressure index (GPI) and fertilization history). We hypothesized that (1) NECB is higher in mesic and fertilized grasslands; (2) NECB increases with MAP and MAT but decreases with GPI; and (3) interactive effects exist among MAP, MAT, and GPI. Using carbon fluxes measured by eddy covariance towers and methane emissions including both enteric methane and manure derived from stocking rates across seven USDA Long-term Agroecosystem Research Network sites, we found: (1) grazing lands were a C-sink or carbon neutral at most sites; (2) vegetation type, moisture conditions, or fertilization had no significant effect on NECB; (3) NECB increased with MAP and MAT, but decreased with a higher GPI; and (4) MAT had a significant positive effect on NECB when MAP exceeded 750 mm (greater water availability). The effect of GPI on NECB was significantly negative when MAP was below 1000 mm, significantly negative when MAT < 12 °C and significantly positive when MAT > 16 °C. Thus, most grazing lands in our study acted as C-sinks unless water deficit, low temperature, or heavy grazing were interactively present. Understanding how climate and management influence NECB of grazing lands is key to maintaining resilient agroecosystems that secure beef production and sustain rural prosperity.

LTAR↗