Results for “diffusion maps” — Page 16

DOE OSTI2025

Corrosion susceptibility and chromium loss in Austenitic steels and Nickel-based alloys in molten FLiNaK at 700 °C

A comparative study was conducted to evaluate the corrosion susceptibility of 316L, 316H, Ni 200, Inconel 625, and Hastelloy N in molten FLiNaK at 700 °C for 100 h. Top-view and cross-sectional scanning electron microscopy (SEM) imaging, combined with energy-dispersive X-ray spectroscopy (EDS) mapping, was performed to investigate microstructural and compositional changes. SEM images were further processed by introducing a contrast threshold to map cavity distribution. Using EDS mapping, intergranular and intragranular Cr loss were separately characterized. The ranking of mass loss after corrosion, from highest to lowest, is as follows: 316H > 316L > Inconel 625 > Hastelloy N > Ni 200. Cr loss was found to be correlated with Mo concentration, in agreement with many previous studies, with higher Mo content resulting in reduced Cr loss. On the other hand, there is no evidence that the high carbon content in 316H enhances corrosion resistance. The relatively low solubility of carbon in austenite at the testing temperature limits the amount of dissolved carbon. Therefore, the carbon-retarded vacancy diffusion, and consequently the reduced Cr diffusion, were not observed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Model-informed, Adaptive Physical Vapor Deposition to Fabricate Hierarchical Binary-alloy Thin-films

Designing next generation thin films, tailor-made for specific applications, relies on the availability of robust processing-structure-property relationships. Traditional structure zone diagrams are limited to low-dimensional mappings, with machine-learning methods only recently attempting to relate multiple processing parameters to the final microstructure. Despite this progress, structure-processing relationships are unknown for processing conditions that vary during thin-film deposition, limiting the range of microstructures and properties achievable. In this project, we employed a phase-field computational model combined with a genetic algorithm (GA) to identify and design time-dependent processing protocols that achieve tailor-made microstructures. We simulate the physical vapor deposition of a binary-alloy thin film by employing a phase-field model, where deposition rates and diffusivities are controlled via the genetic algorithm. Our GA-guided protocols achieve targeted microstructures with lateral and vertical concentration modulations, as well as more complex, hierarchical microstructures previously not described in simple structure zone diagrams. Our algorithm provides insight to experimentalists looking for additional avenues to design novel thin-film microstructures.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Panoramic Mapping of Phonon Transport from Ultrafast Electron Diffraction and Scientific Machine Learning

Abstract One central challenge in understanding phonon thermal transport is a lack of experimental tools to investigate frequency‐resolved phonon transport. Although recent advances in computation lead to frequency‐resolved information, it is hindered by unknown defects in bulk regions and at interfaces. Here, a framework that can uncover microscopic phonon transport information in heterostructures is presented, integrating state‐of‐the‐art ultrafast electron diffraction (UED) with advanced scientific machine learning (SciML). Taking advantage of the dual temporal and reciprocal‐space resolution in UED, and the ability of SciML to solve inverse problems involving coupled Boltzmann transport equations, the frequency‐dependent interfacial transmittance and frequency‐dependent relaxation times of the heterostructure from the diffraction patterns are reliably recovered. The framework is applied to experimental Au/Si UED data, and a transport pattern beyond the diffuse mismatch model is revealed, which further enables a direct reconstruction of real‐space, real‐time, frequency‐resolved phonon dynamics across the interface. The work provides a new pathway to probe interfacial phonon transport mechanisms with unprecedented details.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Classifying the full SDSS-IV MaNGA Survey using optical diagnostic diagrams: Presentation of AGN catalogs in flexible apertures

Accurate active galactic nucleus (AGN) identifications in large galaxy samples are crucial for the assessment of the role of AGN and AGN feedback in the co-evolution of galaxies and their central supermassive black holes. Emission-line flux-ratio diagnostics are commonly used to identify AGN in optical spectra. New large samples of integral field unit observations allow exploration of the role of aperture size in the classification process. In this paper, we present galaxy classifications for all 10010 galaxies observed within the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. We use Baldwin-Philips-Terlevich line flux-ratio diagnostics combined with an Hα equivalent threshold in 60 apertures of varying size for the classification, and provide the corresponding catalogs. MaNGA-selected AGN primarily lie below the main sequence of star-forming galaxies, and reside in massive galaxies with stellar masses of ~10 11 M ⊙ and a median Hα-derived star formation rate of ~1.44M ⊙ yr -1 . We find that the number of “fake” AGN increases significantly beyond selection apertures of >1.0 R eff because of increased contamination from diffuse ionized gas (DIG). A comparison with previous works shows that the treatment of the underlying stellar continuum and flux measurements can significantly impact galaxy classification. Our work provides the community with AGN catalogs and galaxy classifications for the full MaNGA survey.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Fictitious phase separation in Li layered oxides driven by electro-autocatalysis

Layered oxides widely used as lithium-ion battery electrodes are designed to be cycled under conditions that avoid phase transitions. Although the desired single-phase composition ranges are well established near equilibrium, operando diffraction studies on many-particle porous electrodes have suggested phase separation during delithiation. Notably, the separation is not always observed, and never during lithiation. These anomalies have been attributed to irreversible processes during the first delithiation or reversible concentration-dependent diffusion. However, these explanations are not consistent with all experimental observations such as rate and path dependencies and particle-by-particle lithium concentration changes. Here, we show that the apparent phase separation is a dynamical artefact occurring in a many-particle system driven by autocatalytic electrochemical reactions, that is, an interfacial exchange current that increases with the extent of delithiation. We experimentally validate this population-dynamics model using the single-phase material L ix (Ni 1/3 Mn 1/3 Co 1/3 )O 2 (0.5 < x < 1) and demonstrate generality with other transition-metal compositions. Operando diffraction and nanoscale oxidation-state mapping unambiguously prove that this fictitious phase separation is a repeatable non-equilibrium effect. We quantitatively confirm the theory with multiple-datastream-driven model extraction. More generally, our study experimentally demonstrates the control of ensemble stability by electro-autocatalysis, highlighting the importance of population dynamics in battery electrodes (even non-phase-separating ones).

36 MATERIALS SCIENCE↗

DOE OSTI2023

Improving Nb3Sn Cavity Performance Using Centrifugal Barrel Polishing

Nb3Sn superconducting radiofrequency (SRF) cavities have been an ongoing research topic for many years motivated by the potential for higher accelerating gradients and quality factors compared to niobium SRF cavities. The highest performing Nb3Sn cavities are manufactured using tin vapor-diffusion coating, which creates a Nb3Sn film with a surface roughness of around 100-200 nm. This is thought to be one of the limiting factors for the accelerating gradient of Nb3Sn cavities due to enhancement of magnetic field near sharp surface features. To smooth Nb3Sn SRF cavities, we have developed a mechanical polishing procedure which uses centrifugal barrel polishing to smooth the surface followed by a secondary tin coating step to repair the surface. We show that the accelerating field of a Nb3Sn SRF cavity is improved by applying this procedure. We also investigate the quench mechanism of the polished cavity by utilizing temperature mapping to measure which regions of the cavity e xperience heating during RF operation. We then cut samples from these regions and analyze the film microstructure and chemical composition in 3D using EDS and EBSD measurements together with a focused ion-beam (FIB) tomography technique.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Perivascular network segmentations derived from high-field MRI and their implications for perivascular and parenchymal mass transport in the rat brain

A custom segmentation workflow was applied to ex vivo high-field MR images of rat brains acquired following in vivo intraventricular contrast agent infusion to generate maps of the perivascular spaces (PVS). The resulting perivascular network segmentations enabled analysis of perivascular connections to the ventricles, parenchymal solute clearance, and dispersive solute transport within PVS. Numerous perivascular connections between the brain surface and the ventricles suggest the ventricles integrate into a PVS-mediated clearance system and raise the possibility of cerebrospinal fluid (CSF) return from the subarachnoid space to the ventricles via PVS. Assuming rapid solute exchange between the PVS and CSF spaces primarily by advection, the extensive perivascular network decreased the mean clearance distance from parenchyma to the nearest CSF compartment resulting in an over 21-fold reduction in the estimated diffusive clearance time scale, irrespective of solute diffusivity. This corresponds to an estimated diffusive clearance time scale under 10 min for amyloid-beta which suggests that the widespread distribution of PVS may render diffusion an effective parenchymal clearance mechanism. Additional analysis of oscillatory solute dispersion within PVS indicates that advection rather than dispersion is likely the primary transport mechanism for dissolved compounds greater than 66 kDa in the long (> 2 mm) perivascular segments identified here, although dispersion may be significant for smaller compounds in shorter perivascular segments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Editors’ Choice—Flooded by Success: On the Role of Electrode Wettability in CO 2 Electrolyzers that Generate Liquid Products

Economic operation of carbon dioxide (CO 2 ) electrolyzers generating liquid products will likely require high reactant conversions and product concentrations, conditions anticipated to challenge existing gas diffusion electrodes (GDEs). Notably, electrode wettability will increase as lower surface tension products (e.g., formic acid, alcohols) are introduced into electrolyte streams, potentially leading to flooding. To understand the hydraulically stable operating envelopes in mixed aqueous-organic liquid domains, we connect intrinsic electrode wettability descriptors to operating parameters such as electrolyte flow rate and current. We first measure contact angles of water-organic product dilutions on polytetrafluoroethylene (PTFE) and graphite surfaces as planar analogues for GDE components. We then use material balances around the reactive gas-liquid-solid interface to calculate product mass fractions as functions of water sweep rate and current. Product composition maps visualize the extent to which changes in cell performance influence capillary pressure, a determinant of GDE saturation. Analyses suggest that formic acid mixtures pose little risk for GDE flooding across a wide range of conditions, but effluents containing <30% alcohol by mass may cause flooding. This study reveals opportunities to integrate microstructural features and oleophobic surface treatments into GDEs to repel aqueous-organic mixtures and expand the window of stable operating conditions.

25 ENERGY STORAGE↗

DOE OSTI2025

Q3 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q3: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis. • Benchmark between two first wall heat flux mapping methods, identify importance of various heat flux sources and physics impact of using fully coupled CESOL vs post-analysis evaluation. 2. Generate medium fidelity parametrized CAD. • Generate parametrized CAD components for the CAT example case via either user-defined modules called within the geometry generation or by defeatured/parametrized CAD, including DCLL blanket matched to divertor boundary and magnets. Define materials, labels, and boundary conditions for passing the mesh to CFD tools. 3. Demonstrate multiphysics magnet analysis. • Demonstrate magnet analysis workflow called from the FREDA workflow, and 4. Demonstrate nuclear analysis. • Add model to OpenFOAM and/or other codes possibly including Diablo to account for tritium diffusion in solids.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Chemical Interaction of Palladium in Uranium Oxycarbide Nuclear Fuel Kernel

Chemical Interaction of Palladium in Uranium Oxycarbide Nuclear Fuel Kernel Jana Howard1,3, Guang Yang3, Haiyan Zhao1*, Patrick Warren4, Tiankai Yao3, Steven Cavazos4 Elizabeth Sooby Wood4*, Ching-heng Shiau2 1 University of Idaho, Environmental Science, Idaho Falls, Idaho, USA 2 Boise State University, Microscopy and Characterization Suite, Idaho Falls, Idaho, USA 3 Idaho National Laboratory, Idaho Falls, Idaho, USA 4 University of Texas San Antonio, Department of Physics and Astronomy, San Antonio, Texas, USA *Corresponding author: haiyanz@uidaho.edu; elizabeth.soobywood@utsa.edu Tri-structural Isotropic (TRISO) particle fuel is the preferred choice for the newest and next-generation high-temperature nuclear reactors due to its robust construction [1]. The fuel design effectively contains fission products inside the particle at extremely high temperatures [2]. However, the effect of transition metal fission products on fuel performance and structural integrity remains largely unknown, creating uncertainties in predicting fuel performance and potential failure mechanisms [2]. For example, palladium (Pd) has a strong tendency to form intermetallic phases with uranium (U). These new phases tend to be hard and brittle which could lead to fracture of fuel kernel during irradiation [3,4]. Pd is not normally produced in high concentrations in normal fission reactions however, driving the production of Pd into the locality of a Uranium Oxycarbide (UCO) nuclear fuel provides an opportunity to closely observe the diffusion and chemical interactions. This study focuses on detailed transmission electron microscopy characterization of the intermetallic phases formed by the interaction between a UCO kernel and a Pd bar after annealing at 1100 °C for 100 hours. Figure 1 provides an overview of the UCO kernel in contact with the Pd bar. The UCO-Pd sample surface was examined using a Focused Ion Beam (FIB) Quanta 3D FEG FEI in VCD detector mode at 10kV, 83pA to reveal surface features. Several key surface features in the interaction region were observed including: (1) a small area with dendritic microstructure, (2) color contrast near the UCO kernel and Pd boundary, and (3) darker and lighter regions throughout the sample surface. To analyze diffusion behavior, FIB was used to prepare lamellae from five different areas of the UCO-Pd sample, as well as one for the as-received sample. These lamellae were examined using a Scanning Transmission Electron Microscope ThermoFisher Spectra 300 (STEM-Spectra). Energy Dispersive Spectroscopy results confirmed the diffusion between the UCO fuel and Pd bar. Figure 2 shows the identified phases of UC, UO2, and Pd dispersed throughout the interaction region. It was also found that the Pd concentration decreases as the radial distance from the UCO-Pd interface increases. The Pd concentration was 36.93% atomic fraction 11µm from the interaction region then decreased to 7.51% atomic fraction at 257 µm away from the interaction region. Figure 3 shows how concentrations of U and Pd vary across the interaction zone, highlighting the extent of diffusion. This study confirms that Pd interacts with surrounding material to form U-Pd phase and diffusion zones. These diffusion zones vary in composition depending on its radial distance from the point of contact with the Pd bar. These findings contribute to a deeper understanding of the fission product behavior in high temperature nuclear fuels, aiding in the prediction and mitigation of potential fuel degradation mechanisms. A B C Fig. 1. SEM micrographs of UCO fuel kernel in contact with solid Pd bar and the lift out locations. Figure 1A shows UCO fuel kernel in contact with solid Pd bar. Figure 1B shows a higher magnification image of the UCO fuel-Pd interaction zone. Figure 1C shows lift out sites for the lamellae. A B C Fig 2. EDS maps reveal the distribution of U, O, and Pd in location 3. Figure 2A shows the distribution of uranium. Figure 2B shows the distribution of oxygen. Figure 2C shows the distribution of palladium. A B C Fig 3. Palladium and uranium concentration across interaction zone in location 2. Figure 3A shows EDS map of lift out number 2. Figure 3B shows a zoomed in EDS map taken from the interaction zone. Figure 3C shows a line graph of uranium and palladium concentrations across the interaction zone. References: 1. B.E. Wells, N.R. Phillips, K.J. Geelhood. Pacific West Laboratory. (2021). TRISO Fuel: Properties and Failure Modes. https://www.nrc.gov/docs/ML2117/ML21175A152.pdf (Accessed January 16, 2025). 2. American Nuclear Society. TRISO Fuel Development Progresses in INL, ORNL. https://www.gen-4.org/gif/upload/docs/application/pdf/2014-03/nov13nn_fuel_reprint.pdf (Accessed January 16, 2025) 3. Clark R.A., M.A. Con

36 - MATERIALS SCIENCE↗

DOE OSTI2025

Chemical Interaction of Palladium in Uranium Oxycarbide Nuclear Fuel Kernel

Chemical Interaction of Palladium in Uranium Oxycarbide Nuclear Fuel Kernel Jana Howard1,3, Guang Yang3, Haiyan Zhao1*, Patrick Warren4, Tiankai Yao3, Steven Cavazos4 Elizabeth Sooby Wood4*, Ching-heng Shiau2 1 University of Idaho, Environmental Science, Idaho Falls, Idaho, USA 2 Boise State University, Microscopy and Characterization Suite, Idaho Falls, Idaho, USA 3 Idaho National Laboratory, Idaho Falls, Idaho, USA 4 University of Texas San Antonio, Department of Physics and Astronomy, San Antonio, Texas, USA *Corresponding author: haiyanz@uidaho.edu; elizabeth.soobywood@utsa.edu Tri-structural Isotropic (TRISO) particle fuel is the preferred choice for the newest and next-generation high-temperature nuclear reactors due to its robust construction [1]. The fuel design effectively contains fission products inside the particle at extremely high temperatures [2]. However, the effect of transition metal fission products on fuel performance and structural integrity remains largely unknown, creating uncertainties in predicting fuel performance and potential failure mechanisms [2]. For example, palladium (Pd) has a strong tendency to form intermetallic phases with uranium (U). These new phases tend to be hard and brittle which could lead to fracture of fuel kernel during irradiation [3,4]. Pd is not normally produced in high concentrations in normal fission reactions however, driving the production of Pd into the locality of a Uranium Oxycarbide (UCO) nuclear fuel provides an opportunity to closely observe the diffusion and chemical interactions. This study focuses on detailed transmission electron microscopy characterization of the intermetallic phases formed by the interaction between a UCO kernel and a Pd bar after annealing at 1100 °C for 100 hours. Figure 1 provides an overview of the UCO kernel in contact with the Pd bar. The UCO-Pd sample surface was examined using a Focused Ion Beam (FIB) Quanta 3D FEG FEI in VCD detector mode at 10kV, 83pA to reveal surface features. Several key surface features in the interaction region were observed including: (1) a small area with dendritic microstructure, (2) color contrast near the UCO kernel and Pd boundary, and (3) darker and lighter regions throughout the sample surface. To analyze diffusion behavior, FIB was used to prepare lamellae from five different areas of the UCO-Pd sample, as well as one for the as-received sample. These lamellae were examined using a Scanning Transmission Electron Microscope ThermoFisher Spectra 300 (STEM-Spectra). Energy Dispersive Spectroscopy results confirmed the diffusion between the UCO fuel and Pd bar. Figure 2 shows the identified phases of UC, UO2, and Pd dispersed throughout the interaction region. It was also found that the Pd concentration decreases as the radial distance from the UCO-Pd interface increases. The Pd concentration was 36.93% atomic fraction 11µm from the interaction region then decreased to 7.51% atomic fraction at 257 µm away from the interaction region. Figure 3 shows how concentrations of U and Pd vary across the interaction zone, highlighting the extent of diffusion. This study confirms that Pd interacts with surrounding material to form U-Pd phase and diffusion zones. These diffusion zones vary in composition depending on its radial distance from the point of contact with the Pd bar. These findings contribute to a deeper understanding of the fission product behavior in high temperature nuclear fuels, aiding in the prediction and mitigation of potential fuel degradation mechanisms. A B C Fig. 1. SEM micrographs of UCO fuel kernel in contact with solid Pd bar and the lift out locations. Figure 1A shows UCO fuel kernel in contact with solid Pd bar. Figure 1B shows a higher magnification image of the UCO fuel-Pd interaction zone. Figure 1C shows lift out sites for the lamellae. A B C Fig 2. EDS maps reveal the distribution of U, O, and Pd in location 3. Figure 2A shows the distribution of uranium. Figure 2B shows the distribution of oxygen. Figure 2C shows the distribution of palladium. A B C Fig 3. Palladium and uranium concentration across interaction zone in location 2. Figure 3A shows EDS map of lift out number 2. Figure 3B shows a zoomed in EDS map taken from the interaction zone. Figure 3C shows a line graph of uranium and palladium concentrations across the interaction zone. References: 1. B.E. Wells, N.R. Phillips, K.J. Geelhood. Pacific West Laboratory. (2021). TRISO Fuel: Properties and Failure Modes. https://www.nrc.gov/docs/ML2117/ML21175A152.pdf (Accessed January 16, 2025). 2. American Nuclear Society. TRISO Fuel Development Progresses in INL, ORNL. https://www.gen-4.org/gif/upload/docs/application/pdf/2014-03/nov13nn_fuel_reprint.pdf (Accessed January 16, 2025) 3. Clark R.A., M.A. Con

36 - MATERIALS SCIENCE↗

DOE OSTI2022

Long-time integration of parametric evolution equations with physics-informed DeepONets

Ordinary and partial differential equations (ODEs/PDEs) play a paramount role in analyzing and simulating complex dynamic processes across all corners of science and engineering. In recent years machine learning tools are aspiring to introduce new effective ways of simulating such equations, however existing approaches are not able to reliably return stable and accurate predictions across long temporal horizons. We aim to address this challenge by introducing an effective framework for learning evolution operators that map random initial conditions to associated ODE/PDE solutions within a short time interval. Such operators can be parametrized by deep neural networks that are trained in an entirely self-supervised manner without requiring one to generate any paired input-output observations. Global long-time predictions across a range of initial conditions can be then obtained by iteratively evaluating the trained model using each prediction as the initial condition for the next evaluation step. Here, this introduces a new approach to temporal domain decomposition that is shown to be effective in performing accurate long-time simulations for a wide range of parametric ODE and PDE systems, from wave propagation, to reaction-diffusion dynamics and stiff chemical kinetics, introducing a new way of rapidly emulating non-equilibrium processes in science and engineering.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Mapping of fracture and ionic conductivity changes in ion implanted solid electrolytes: Insights from molecular dynamics

Ion implantation emerges as a promising technique to address the persistent challenge of lithium (Li) filament growth in solid-state electrolytes as it can induce compressive stresses inhibiting crack growth and deflect dendrites, de facto mitigating early electrolyte failure. In this study, we examine the potential paradox of ion implantation: while aiming to enhance electrolyte performance, the radiation damage associated with implantation might inadvertently compromise both the ionic conductivity and the intrinsic fracture toughness of the material, rendering the material unsuitable for battery applications. Specifically, we employed molecular dynamics simulations to examine the scope of the downsides of ion implantation, specifically: (i) reduced ionic conductivity (due to radiation-induced amorphization) and (ii) mechanical stability (due to radiation-induced embrittlement) in ion-implanted Li 7 La 3 Zr 2 O 12 (LLZO) solid-state electrolytes. We explore how radiation damage impacts LLZO’s crystalline structure, Li-ion diffusion, and fracture properties at various temperatures and radiation damage levels. The study aims to provide insights into the competing effects of ion implantation and suggest potential engineering strategies for developing more robust solid-state electrolytes with improved conductivity and dendrite resistance.

Conductivity↗

DOE OSTI2024

Understanding Anomalous Gas-Phase Peak Shifts in Dip-and-Pull Ambient Pressure XPS Experiments

Dip-and-pull ambient pressure X-ray photoelectron spectroscopy (AP-XPS) holds promise to uncover elementary processes of (photo)electrochemistry. We show, however, that the sample for such experiments should preferably be nonporous and the potential on the surface homogeneous. We carried out dip-and-pull AP-XPS experiments on a hematite thin film sample under the photoelectrochemical oxygen evolution reaction (OER) and find unexpected O 1s core level shifts. Upon electrochemical biasing under simulated solar light illumination, the gas-phase water peak shifted more than the electrolyte peak. To uncover the origin of the unexpected larger shift of the gas-phase peak, we performed electrostatic simulations using COMSOL, to map the potential field in the relevant volume between the sample and the first aperture of the XPS spectrometer. A number of geometric models were considered. We find that when the potential on the sample surface is inhomogeneous, e.g., with ionically isolated electrolyte patches, the gas-phase peak of the spectrum can shift more than the peak due to the electrolyte film. This suggests that at the measured sample position, the local potential was not as set by the potentiostat. Despite this, we find reversible consumption and replenishment of hydroxide in the spectra, which, due to OH– being the reactant of the OER in alkaline electrolyte, makes sense chemically. We propose that this is linked to OH– diffusion across the measured sample position, driven by the potential dependent consumption and replenishment of OH– at the nearby well-connected surface regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Towards fast, accurate predictions of RF simulations via data-driven modeling: Forward and lateral models

Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. More accurate simulations with fast electron diffusion are even slower, requiring multiple hours of run time with parallel processing. The machine learning models use a database of 16,000+ GEN-RAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods implemented in πScope ensure that the database covers the range of 9 input parameters (n e0 , T e0 , I p , B t , R 0 , n ∥︀ , Z e f f , V loop , P LHCD ) with sufficient density in all regions of parameter space. The surrogate models reduce the computation time from minutes-hours to ms with high accuracy across the input parameter space. Data-driven surrogate models also allow for solving inverse and “lateral” problems. A surrogate model for the inverse problem maps from a desired current drive or power deposition profile to a set of input parameters that would result in such a profile, while a surrogate model for the lateral problem maps from a measured experimental quantity such as hard x-ray emission to a current drive or power deposition profile. In conclusion, the πScope database creation workflow is flexible and applicable to other RF simulation codes such as TORIC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Impedance-Based Detection of NO 2 Using Ni-MOF-74: Influence of Competitive Gas Adsorption

Chemically robust, low-power sensors are needed for the direct electrical detection of toxic gases. Metal–organic frameworks (MOFs) offer exceptional chemical and structural tunability to meet this challenge, though further understanding is needed regarding how coadsorbed gases influence or interfere with the electrical response. To probe the influence of competitive gases on trace NO 2 detection in a simulated flue gas stream, a combined structure–property study integrating synchrotron powder diffraction and pair distribution function analyses was undertaken, to elucidate how structural changes associated with gas binding inside Ni-MOF-74 pores correlate with the electrical response from Ni-MOF-74-based sensors. Data were evaluated for 16 gas combinations of N 2 , NO 2 , SO 2 , CO 2 , and H 2 O at 50 °C. Fourier difference maps from a rigid-body Rietveld analysis showed that additional electron density localized around the Ni-MOF-74 lattice correlated with large decreases in Ni-MOF-74 film resistance of up to a factor of 6 × 10 3 , observed only when NO 2 was present. These changes in resistance were significantly amplified by the presence of competing gases, except for CO 2 . Without NO 2 , H 2 O rapidly (<120 s) produced small (1–3×) decreases in resistance, though this effect could be differentiated from the slower adsorption of NO 2 by the evaluation of the MOF’s capacitance. Furthermore, samples exposed to H 2 O displayed a significant shift in lattice parameters toward a larger lattice and more diffuse charge density in the MOF pore. Evaluating the Ni-MOF-74 impedance in real time, NO 2 adsorption was associated with two electrically distinct processes, the faster of which was inhibited by competitive adsorption of CO 2 . Together, this work points to the unique interaction of NO 2 and other specific gases (e.g., H 2 O, SO 2 ) with the MOF’s surface, leading to orders of magnitude decrease in MOF resistance and enhanced NO2 detection. Finally, understanding and leveraging these coadsorbed gases will further improve the gas detection properties of MOF materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

In Situ Raman Mapping of Si Island Electrodes and Stress Modeling as a Function of Lithiation and Size

Si is known for cracking and delamination during electrochemical cycling of a battery due to the large volume change associated with Li insertion and extraction. However, it has been found experimentally that patterned Si island electrodes that are 200 nm thick and less than 7 μm wide can deform in a purely elastic manner. Inspired by this, we performed in situ Raman stress characterization of model poly-crystalline Si island electrodes using an electrochemical cell coupled with an immersion objective lens and designed for a short working distance. A 5 μm wide Si island electrode showed a parabolic stress profile during lithiation, while for a 15 μm Si island electrode, a stress plateau in the center of the electrode was observed. A continuum model with coupled electro-chemo-mechanical (ECM) physics was established to understand the stress measurement. A qualitative agreement was reached between modeling and experimental data, and the critical size effect could be explained by the Li diffusive flux as governed by competition between the Li concentration and hydrostatic stress gradients. Below the critical size, the stress gradient drives Li toward the edges, where the electrode volume is free to expand, while above the critical size, the stress plateau inhibits Li diffusion to the edge and forces destructive stress relief by cracking. Furthermore, this work represents a promising methodology for in situ characterization of ECM coupling in battery electrodes, with suggestions provided for further improvement.

25 ENERGY STORAGE↗

DOE OSTI2025

Nonideal stability analysis of differentially rotating plasmas with global curvature effects

The linear stability of global nonaxisymmetric modes in differentially rotating, magnetized, nonideal plasma is critical to classifying turbulence and transport phenomena. We investigate the competition between the local magneto-rotational instability (MRI) and the magneto-curvature instability (MCI)—a distinct nonaxisymmetric low-frequency curvature-driven global branch that appears alongside MRI. Here, to accomplish this, we developed a nonideal global spectral method, which is validated against NIMROD code simulations. This spectral approach allows for the direct derivation of an extended effective potential formalism and a resistive Alfvénic resonance condition, providing a framework for direct analysis of energy contributions and confinement mechanisms. Our study reveals that the global, low-frequency MCI persists at low magnetic Reynolds numbers (Rm), whereas the localized, high-frequency MRI is stabilized by diffusive broadening of its structure around its Alfvénic resonances. Consequently, we identify the global MCI branch as the primary onset mechanism for nonaxisymmetric magnetohydrodynamic instability in systems with finite curvature, e.g., astrophysical rotators. We establish distinct parameter regimes for mode dominance: MCI prevails in geometrically moderate-thickness disks with intermediate curvature and radial gaps, while MRI dominates in thin, low-curvature disks with large radial gaps. Mode competition is also highly sensitive to the flow profile, particularly vorticity and its gradient, with nonuniform shear profiles exhibiting more robust instability due to flow curvature (i.e., the second derivative of the flow profile) and shear contributions. A key outcome is the development of spectral diagrams derived from the global spectral method. These diagrams comprehensively map dominant instabilities and their characteristics, offering a predictive tool for critical onset parameters (i.e., flow curvature, magnetic field, and Rm) and facilitating the interpretation of experimental and simulation results. Notably, these diagrams demonstrate that the global MCI is generally the sole unstable mode at the initial onset of nonaxisymmetric instability.

Haywood, Alexander [Princeton Univ., NJ (United St↗