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At least 937 records · Page 52

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DOE OSTI2020

Investigation of the benefits of diabatic microreactors for process intensification of the water-gas shift reaction within the steam reforming process

Presently, the steam reforming process is the largest industrial source of hydrogen. Improving its efficiency can help to reduce associated carbon emissions and hydrogen production costs. Intensifying the water-gas shift reaction using microreactors with integrated cooling is one way of achieving this. In this study, a 2-D computational model of one of these microreactors is developed, validated with experimental data, and then used to demonstrate how microreactors can enhance the conversion of the water-gas shift reaction beyond what can be achieved using conventional packed bed reactors. These results are then generalized into a full system model of the steam reforming process to demonstrate how microreactors can reduce hydrogen production costs. The results suggest that microreactors can significantly reduce the required reactor volume and catalyst loading for the water-gas shift reaction and can similarly reduce the hydrogen production costs associated with the steam reforming process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Multi-dimensional modeling of mixture preparation in a direct injection engine fueled with gaseous hydrogen

With the recent advances of direct injection (DI) technology, introducing hydrogen into the combustion chamber through DI is being considered as a viable approach to circumvent backfire and pre-ignition encountered in early generations of hydrogen engines. As part of a broader vision to develop a robust numerical model to study hydrogen spark ignition (SI) combustion in internal combustion (IC) engines, the present numerical investigation focuses on mixture preparation in a hydrogen DI SI engine. This study is carried out with a single hole injector with gaseous hydrogen injected at 100 bar injection pressure. Simulations are carried out for high and low tumble configurations and validated against optical data acquired from planar laser induced fluorescence (PLIF) measurements. Varying mesh configurations are investigated for the impact on in-cylinder mixture distribution. A particular emphasis is placed on the effect of nozzle geometry and mesh orientation near the wall. Overall, the computational model is found to predict the mixture distribution in the combustion cylinder reasonably well. The results showed that the alignment of mesh with the flow direction is important to achieve good agreement between numerical analysis and optical measurement data.

08 HYDROGEN↗

DOE OSTI2026

Electrochemical behavior of SnCl 2 and influence of Cu and Ni ions in molten LiCl−KCl−CaCl 2 eutectic

Reliable transport and thermodynamic data for multivalent ions in complex molten salts are scarce, limiting model fidelity for electrorefining and impurity control. Here, we report a comprehensive electrochemical characterization of SnCl₂ in LiCl–KCl–CaCl₂ (50.5–44.2–5.3 mol%) at 685 K, including the effects of Ni 2+ and Cu + impurities. Using cyclic voltammetry (CV), chronoamperometry (CA), and chronopotentiometry (CP), we quantified Sn 2+ and Ni 2+ diffusion with exceptional agreement across methods: Sn 2+ averaged (1.03 ± 0.10) × 10 −5 cm 2 s −1 , and Ni 2+ averaged (0.75 ± 0.19) × 10 −5 cm 2 s −1 . The tight confidence-interval overlap across CV, CA, and CP strengthens confidence in these values and is uncommon in molten chloride studies. Open-circuit-potential measurements provided standard apparent reduction potentials that closely match LiCl–KCl literature, indicating minimal shift with CaCl₂ present. The Sn 2+ /Sn couple behaves as a reversible two-electron soluble–insoluble process at 685 K; the Sn 4+ /Sn 2+ couple transitions to soluble–soluble behavior near 788 K, which may correlate with the decomposition of surface bound chlorostannates, though direct characterization remains to be established. In mixed systems, Cu+/Cu overlaps Sn 2+ /Sn, limiting Cusingle bondSn electroseparation, whereas the larger potential gap between Ni 2+ /Ni and Sn 2+ /Sn supports selective Ni removal. These internally consistent transport and thermodynamic data establish a validated basis for process modeling and optimization of Sn electrorefining and impurity management in LiCl–KCl–CaCl₂.

Berzins-Delahay↗

DOE OSTI2025

Meshfree simulation and prediction of recrystallized grain size in friction stir processed 316L stainless steel

Friction stir processing (FSP) is a promising solid-phase microstructural modification technique that can repair and enhance damaged stainless steel surfaces exposed to harsh environments. The quality of the repaired material is closely correlated to the recrystallized grain size in the stir zone (SZ), which is influenced by the thermomechanical conditions dictated by FSP process parameters. Thus, establishing a reliable relationship between these parameters and recrystallized grain size in the SZ is crucial for optimizing repair quality. However, existing experimental approaches often rely on indirect temperatures measured far from the SZ, along with rough strain rate estimations, which are imprecise and time-consuming. Meanwhile, existing mesh-based modeling methods usually face numerical challenges when dealing with the large material deformations inherent in FSP. Here, to address these issues, this study introduces a meshfree process model for FSP based on the smoothed particle hydrodynamics (SPH) method, aimed at predicting process conditions under different parameters. The model is validated using experimental data from 11 combinations of tool traverse and rotation speeds on 316 L stainless steel. Correlations between process parameters, material flow, temperature, strain, strain rate, and recrystallized grain size are revealed through SPH simulations and electron backscatter diffraction (EBSD) imaging. The results show that in situ SZ temperatures range from 1071 to 1322°C, which exceed the tool temperature by over 300°C. Furthermore, SZ temperature, strain rate, and grain size increase monotonically with higher tool temperature and faster traverse speed. A relationship is then established between the model-predicted Zener-Hollomon parameter and the recrystallized grain size based on EBSD data, expressed as ln(d) = -0.364 ln(Z) + 14.673. Finally, this relationship exhibits satisfactory accuracy with errors of less than 26.9% in predicting grain sizes at various SZ locations, which offers valuable insights for optimizing FSP repair processes for 316 L stainless steel.

316L stainless steel↗

DOE OSTI2022

High-temperature compressive creep tests of U 3 Si 2 with spark plasma sintering: Experiments and finite element modeling

This paper reports a systematic high-temperature creep behavior of dense U 3 Si 2 pellets using a spark plasma sintering (SPS) apparatus at elevated temperatures and pressures under vacuum conditions. The stress exponent was subsequently derived to be 3.21 at 1173 K and 2.17 at 1223 K, respectively, indicating a grain boundary sliding creep mechanism. The creep activation energy was determined to be 203.6 ± 19.0 kJ/mol, which agrees well with the literature. Finite element modeling was performed using the creep parameters fitted from the strain-time plot. Additionally, the results suggest an excellent match with the experimental data, confirming the validity of the experiments. Microstructure characterizations indicate that the main phase of the specimens after creep tests remains to be U 3 Si 2 , with a 4 μm thick layer of nano-sized particles induced from the diffusion between U 3 Si 2 and alumina disc used to avoid electric current passing through the sample. The successful conduct of creep experiments demonstrates the great potential of SPS to perform high-temperature mechanical testing of nuclear fuels under vacuum conditions. The subsequent finite element modeling exhibits excellent capabilities for accurately predicting material performance in the creep tests and provides a practical tool in evaluating nuclear fuels’ performance for a much-extended time scale.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Simulations of self- and Xe diffusivity in uranium mononitride including chemistry and irradiation effects

A combination of density functional theory and empirical potential atomic scale simulations have been used to determine a model for defect stability and mobility in uranium mononitride (UN), as a function of temperature (T) and N 2 partial pressure (p N 2 ). Using the model, predictions of hypo-stoichiometry under U-rich conditions compare favorably to CALPHAD calculations using the TAF-ID database. Furthermore, our predictions of U and N self-diffusivity are in good agreement with experiments carried out as a function of T at specific partial pressures under thermal equilibrium. The validated atomic scale data have then been implemented within a cluster dynamics method to simulate irradiation-enhanced defect concentrations. All defects and clusters studied have significantly enhanced concentrations, with respect to thermal equilibrium, as T is lowered. The irradiation-enhanced Xe diffusivity is compared to post-irradiation annealing and in-pile experiments. In conclusion, the contributions of various defects and clusters to non-stoichiometry, self-diffusivity, and Xe diffusivity are discussed.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2020

Global Techno-Economic Performance of Bifacial and Tracking Photovoltaic Systems

Although most of the current photovoltaic (PV) system installations use monofacial modules with fixed-tilt mounting structures, bifacial modules, trackers, and the combination of them are also getting more attention as potential candidates to further reduce the PV levelized cost of electricity (LCOE). This work is then the first to present a worldwide analysis on the yield potential and cost-effectiveness of PV farms composed of monofacial fixed-tilt and single/dual (1T/2T) tracker installations, as well as their bifacial counterparts. Our approach starts by estimating the irradiance reaching the front and rear surface of the modules for the different system designs (validated based on data from real PV systems and results from the literature) to estimate their energy production (row-row shading is neglected). Subsequently, the overall system cost during their 25-year lifetime is factored in, and LCOE is obtained. The results reveal that bifacial-1T installations increase energy yield by 35% and reach the lowest LCOE for the majority of the world (93.1% of the land area). Although dual axis trackers achieve the highest energy generation — especially for bifacial modules — their cost is still too high, and are therefore not as cost-effective. Sensitivity analyses based on the Monte Carlo and region sensitivity approach are performed to analyze the impact of input assumptions on the calculated LCOE. These reveal that our conclusions are robust in general but exact configuration to choose depends on specific site conditions. This investigation is not only of interest to the scientific community, but also can be used as a guide for PV installation companies and investors to determine the most suitable technology for a particular location.

14 SOLAR ENERGY↗

DOE OSTI2026

ROADRUNNER uranium nitride MiniFuel: Experimental design, fabrication and pre-irradiation baseline characterization for accelerated burnup testing

Uranium nitride (UN) is a promising fuel candidate for advanced reactor systems owing to its high uranium density and thermal conductivity; however, its qualification remains constrained by the scarcity of well-controlled irradiation performance data. Here, to address this limitation, the ROADRUNNER (Research On ADvancing the peRformance of UraNium Nitrides in Extreme enviRonments) campaign employs the MiniFuel platform in the High Flux Isotope Reactor (HFIR) to enable accelerated burnup irradiation testing under tightly controlled and largely isothermal conditions. This paper presents the experimental design, fuel fabrication, and pre-irradiation baseline characterization of the ROADRUNNER UN MiniFuel campaign. Thirty-six UN minidisc specimens were fabricated with systematically varied as-fabricated density (86–96% of theoretical density), carbon impurity content (961–5240 ppm), oxygen content (≤ ∼2000 ppm), and grain size (2.5–24 μm). The irradiation matrix spans nominal fuel temperatures of 873 K, 1173 K, and 1473 K and target burnups of 3.75%, 6.0%, and 7.5% fissions per initial metal atom (FIMA). Neutronic and thermal analyses were performed to define specimen-specific burnup accumulation and temperature histories, establishing the boundary conditions for subsequent in-pile behavior. Comprehensive pre-irradiation characterization—including dimensional metrology, density verification, impurity analysis, X-ray diffraction, Raman spectroscopy, scanning electron microscopy, X-ray computed tomography, and confocal profilometry—provides a detailed baseline for post-irradiation examination. Pre-irradiation data were further used to generate predictive estimates of fission gas release and swelling using existing empirical correlations. This quantitative comparison reveals substantial inter-model divergence at intermediate and elevated temperatures that exceeds propagated input uncertainties, highlighting structural gaps in the historical irradiation database. The ROADRUNNER irradiation campaign is currently underway in HFIR, with initial firs cycle completed in late 2025 and remaining targets scheduled through 2027. The experimental design and baseline dataset presented here establish the framework needed to interpret forthcoming post-irradiation measurements and to provide discriminating data for the validation and refinement of physics-based UN fuel performance models.

Lopes, Denise Adorno [Oak Ridge National Laborator↗

DOE OSTI2025

Gaussian integral method for void fraction

Here, a novel method, the Gaussian Integral Method (GIM), is presented for calculating void fractions in Computational Fluid Dynamics–Discrete Element Method (CFD-DEM) simulations. GIM is versatile and applicable to various grid types, including structured and unstructured polyhedral meshes, without requiring special boundary treatments. An optimization technique is introduced to make GIM independent of grid resolution and type. The method is validated against experimental data from a fluidized bed, demonstrating that GIM produces realistic simulations closely resembling experimental observations. Additionally, unstructured polyhedral grids using GIM outperform structured grids of equivalent resolution, yielding results more aligned with experimental data. The gradient of the void fraction is computed in the CFD solver and utilized in the DEM solver for precise estimation at particle locations. Overall, GIM provides an effective solution for void fraction calculations in particulate media simulations with complex geometries, enhancing the accuracy and applicability of CFD-DEM simulations for industrial processes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Development of phenomena identification and ranking table for Westinghouse lead fast reactor’s safety

The Westinghouse Lead-cooled Fast Reactor (LFR) is a medium-size, passively safe, economic, Gen-IV nuclear reactor. An important effort within the Westinghouse LFR program is the development of the safety analysis methodology, which comprises computer code development, model development, and experimental testing. A key initial task associated with the development of the safety analysis methodology is the identification of processes and phenomena that affect the plant's capability to meet selected safety performance indicators. This is accomplished through the development of a Phenomena Identification and Ranking Table (PIRT) for selected accident scenarios which, for this specific PIRT effort, included selected postulated design basis accidents and hypothetical beyond design basis accidents in LFRs. This paper describes the role of PIRT in the development of the Westinghouse LFR safety analysis methodology and the process used in the PIRT development. Specifically, the Westinghouse LFR PIRT assessed importance of pertinent phenomena and identified gaps in their knowledge-base by evaluating current modeling capabilities and data available for validation. The ultimate goal was to provide guidance on computer code development and validation efforts and to prioritize testing to support LFR design and licensing. The key phenomena and processes that are deemed highly important for the safety performance indicators, but for which the state of knowledge is low, are presented. The testing program and analyses development are planned to address significant phenomena in the PIRT.

Lead fast reactor↗

DOE OSTI2025

A simulation pipeline for fast neutron imaging and spectroscopy using quantified detector attributes

Radiation imaging capabilities, essential in the nuclear nonproliferation regime, facilitate source localization and, in certain cases, spectroscopy. Scatter-based neutron cameras, which can measure the neutron signatures from special nuclear material, hold particular interest. Systems incorporating organic scintillators can extract neutron energy spectra, potentially distinguishing fission neutron sources from others, such as alpha-neutron sources. The development and testing of a scatter-based neutron imager, however, can be challenging without having an accurate simulation model or first constructing a prototype. This work describes a simulation pipeline that takes output from MCNPX-PoliMi simulations and creates the expected back-projection neutron images and neutron energy spectra. This pipeline was developed to improve the modeling of fast neutron imagers and bridge the current gap in literature, which predominantly focuses on gamma-ray Compton imager models. This work also reports on the significance of various real-world system considerations and their effects on the simulated detector responses. The pipeline was verified and validated with experimental data collected using a 252 Cf spontaneous fission source using a fast neutron scattering imager developed at the University of Michigan.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Climate change is intensifying rainfall erosivity and soil erosion in West Africa

Soil erosion is a critical environmental challenge with significant implications for agriculture, water quality, and ecosystem stability. Understanding its dynamics is essential for sustainable environmental management and societal welfare. Here, we analyze rainfall erosivity and erosion patterns across West Africa (WAF) during the historical (1982–2014), near future (2028–2060), and far future (2068–2100) periods under Shared Socioeconomic Pathways (SSPs 370 and 585). Using bias-corrected-downscaled (BCD) climate models validated against reference data, we ensure an accurate representation of rainfall—a key driver of erosivity (R-factor) and soil erosion. We compare Renard's approach and the Modified Fournier Index (MFI) to calculate the R-factor and note a strong correlation. However, Renard's method shows slightly lower accuracy in Sierra Leone, Guinea, and The Gambia, likely due to its inability to capture high-intensity, short-duration rainfall events. In contrast, the MFI, utilizing continuous rain gauge data, proves more reliable for these regions. We also attribute fluctuations in erosivity, such as those seen during the 2003 West Africa floods, to synoptic weather patterns influenced by multiple climate processes. Furthermore, our analysis reveals regions where future soil erosion could exceed 20 t/ha/yr due to climate change. Under the SSP 370 scenario, soil erosion in WAF is projected to rise by 14.84 % in the near future and 18.65 % in the far future, increasing further under SSP 585 to 19.86 % and 23.49 %, respectively. The most severe increases are expected in Benin and Nigeria, with Nigeria potentially facing a 66.41 % rise in erosion by the far future under SSP 585. These findings highlight the region's exposure to intensified climatic conditions and underscore the urgent need for targeted soil management and climate adaptation strategies to mitigate erosion's ecological and socioeconomic impacts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Direct numerical simulation of hypersonic turbulent boundary layers: effect of spatial evolution and Reynolds number

Direct numerical simulations (DNS) are performed to investigate the spatial evolution of flat-plate zero-pressure-gradient turbulent boundary layers over long streamwise domains ( >300δ i , with δ i the inflow boundary-layer thickness) at three different Mach numbers, 2.5, 4.9 and 10.9, with the surface temperatures ranging from quasiadiabatic to highly cooled conditions. The settlement of turbulence statistics into a fully developed equilibrium state of the turbulent boundary layer has been carefully monitored, either based on the satisfaction of the von Kármán integral equation or by comparing runs with different inflow turbulence generation techniques. The generated DNS database is used to characterize the streamwise evolution of multiple important variables in the high-Mach-number, cold-wall regime, including the skin friction, the Reynolds analogy factor, the shape factor, the Reynolds stresses, and the fluctuating wall quantities. The data confirm the validity of many classic and newer compressibility transformations at moderately high Reynolds numbers (up to friction Reynolds number Re τ ≈1200 ) and show that, with proper scaling, the sizes of the near-wall streaks and superstructures are insensitive to the Mach number and wall cooling conditions. The strong wall cooling in the hypersonic cold-wall case is found to cause a significant increase in the size of the near-wall turbulence eddies (relative to the boundary-layer thickness), which leads to a reduced-scale separation between the large and small turbulence scales, and in turn to a lack of an outer peak in the spanwise spectra of the streamwise velocity in the logarithmic region.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Simulation of Inelastic Neutron Scattering Spectra Directly from Molecular Dynamics Trajectories

Inelastic neutron scattering (INS) is a widely used technique to study atomic and molecular vibrations. With the increasing complexity of materials and thus the INS spectra, being able to simulate the spectra from various atomistic models becomes an essential step and also a major bottleneck for INS data analysis. The conventional approach using density functional theory and lattice dynamics often falls short when the materials of interest are complex (e.g., defective, disordered, heterogeneous, amorphous, large-scale), for which molecular dynamics driven by an interatomic force field is a more common approach. In this paper, we demonstrate a method to directly convert molecular dynamics trajectories into simulated INS spectra, including not only fundamental but also higher order excitations. In this work, the results are compared with data collected on various representative samples from different neutron spectrometers. This development will open great opportunities by providing the key tool to perform in-depth analysis of INS data and to validate and optimize computer models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Enhancing the Quality and Reliability of Machine Learning Interatomic Potentials through Better Reporting Practices

Recent developments in machine learning interatomic potentials (MLIPs) have empowered even nonexperts in machine learning to train MLIPs for accelerating materials simulations. However, reproducibility and independent evaluation of presented MLIP results is hindered by a lack of clear standards in current literature. In this Perspective, we aim to provide guidance on best practices for documenting MLIP use while walking the reader through the development and deployment of MLIPs including hardware and software requirements, generating training data, training models, validating predictions, and MLIP inference. We also suggest useful plotting practices and analyses to validate and boost confidence in the deployed models. Finally, we provide a step-by-step checklist for practitioners to use directly before publication to standardize the information to be reported. Altogether, we hope that our work will encourage the reliable and reproducible use of these MLIPs, which will accelerate their ability to make a positive impact in various disciplines including materials science, chemistry, and biology, among others.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Crystallization Mechanisms of Poly(vinylidene Fluoride- co -chlorotrifluoroethylene): Nucleation Transitions, Growth Kinetics, and Microstructure Evolution

The crystallization kinetics of FK-800, a commercial semicrystalline copolymer of chlorotrifluoroethylene and vinylidene fluoride (poly(CTFE-co-VDF)), dictate its microstructure and functional performance. Crystallization occurs between the glass transition (T g ≈ 31 °C) and melting point (T m ≈ 110 °C), with grain boundaries playing a key role in applications such as memristors, where they regulate filament growth. This study integrates in situ atomic force microscopy (AFM), grazing-incidence wide-angle X-ray scattering (GIWAXS), and differential scanning calorimetry (DSC) to characterize nucleation, growth, and morphology across the full crystallization window. Hot-stage AFM reveals a transition from homogeneous to heterogeneous nucleation near 45 °C and a shift from reaction-limited to diffusion-limited growth above 60 °C. Kinetics are analyzed using Lauritzen–Hoffman, Turnbull–Fisher, and Avrami models to extract surface free energies and activation barriers. A multiscale modeling framework is developed in which nucleation densities and growth rates measured by AFM are used to reconstruct Avrami kinetics, which are then validated against coverage data, and extrapolated to predict bulk crystallization behavior observed by DSC. GIWAXS confirms a primarily flat-on chain orientation at all temperatures, linking orientation to domain morphology. This integrative approach quantitatively connects nanoscale crystallization dynamics with macroscopic phase evolution, establishing a quantitative framework for modeling crystallization across time, temperature, and length scales.

Crystallization↗

DOE OSTI2025

Automated Nanocrystal Synthesis: Lessons from 25 Years of Robots, Microfluidics, and Machine Learning

Here, this perspective highlights the evolution of techniques for automating the synthesis of colloidal nanocrystals. Over the past 25 years, microfluidic reactors and robotic workflows have been developed to enhance the reproducibility of nanocrystal synthesis, facilitate rapid screening of reaction conditions, optimize material properties, and perform multistep syntheses of high-quality nanoparticles with complex heterostructures. Modern automated systems are now valued for their ability to generate robust data sets for validating physical models, supporting chemical mechanisms, training machine learning models, and for directing autonomous experimentation. We discuss the early challenges and limitations of these technologies and present key lessons for effectively utilizing automated and ML-guided tools to accelerate nanocrystal discovery for the next 25 years.

Nanocrystals↗

DOE OSTI2025

Reliable p K a Prediction through Efficient Incorporation of Anharmonicity within the Nuclear–Electronic Orbital Framework

Accurate pK a prediction is critical for understanding chemical reactivity and molecular properties across a wide range of applications. Computational approaches usually invoke a harmonic treatment of the vibrational modes for zero-point energies, as well as thermal and entropic contributions. Herein, we present a general protocol for relative pK a prediction that incorporates the significant anharmonic effects using nuclear–electronic orbital (NEO) theory. This protocol is validated against experimental data for a range of molecules in acetonitrile, including protonated nitrogen bases, nitrophenols, anilines, and diamines, as well as cobalt electrocatalysts. For simple acids, the NEO approach offers only a slight improvement over conventional density functional theory with the standard harmonic vibrational treatment, whereas for hydrogen-bonded acids, the NEO approach offers more significantly improved performance at a comparable computational cost. This accessible methodology provides a practical route for accurate pKa prediction in challenging systems and is extendable to related thermodynamic properties such as hydricities and proton-coupled redox potentials.

Density functional theory↗