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DOE OSTI2023

Wave vector and field vector orientation dependence of Fe K pre-edge X-ray absorption features in clinopyroxenes

Abstract Pre-edge X-ray absorption features are commonly used to derive redox states for transition metal oxides in crystals and glasses. Several calibrations for Fe2+ and Fe3+ in silicate glasses have utilized the general relationships among pre-edge peak intensity, energy, and redox state. However, absorption variations complicate those relationships in anisotropic crystals. Although absorption anisotropy at and above the energy of the rising edge adheres to the typical cos2 relationship observed in absorption spectroscopies at other energies, the anisotropy of the pre-edge is far more complicated. Prior studies focusing on pre-edge absorption anisotropy demonstrate a 1-cos4φ dependence of absorption magnitudes with rotation. Experiments presented here show that absorption magnitudes of the pre-edge vary as a function of both electric field vector orientation and wave vector direction. However, rotations around the field vector axis or wave vector axis individually result in cos2 dependence of absorption magnitudes. Rotations where both wave vector and field vector orientation are varied are not well fit by either model in the pre-edge. The resulting anisotropy complicates the process of measuring characteristic absorption in the pre-edge, making valence state determinations challenging for strongly anisotropic crystal structures such as pyroxene.

Geochemistry & Geophysics↗

DOE OSTI2021

Boundary detection evaluation

Illustrative embodiments are directed to a method and apparatus for evaluating boundary detection in an image. A processed image is received, wherein a detected boundary of an image of an object is identified in the processed image. A Radon transform is applied to the processed image for a plurality of angles to form a processed image histogram corresponding to the detected boundary for each of the plurality of angles. The processed image histogram for each of the plurality of angles and a corresponding ground truth histogram for each of the plurality of angles is normalized to provide a normalized processed image histogram and a normalized ground truth histogram for each of the plurality of angles, wherein the ground truth histogram corresponds to a ground truth boundary of the object for a corresponding angle. An indication of the edges of the normalized processed image histogram for each of the plurality of angles is plotted to form a boundary detection evaluation visualization.

Wantuch, Andrew C.↗

DOE OSTI2024

Boundary detection evaluation

Wantuch, Andrew C.↗

DOE OSTI2022

Effects of edge-seal design on the mechanical and thermal performance of vacuum-insulated glazing

Although vacuum-insulated glazing (VIG) has been proposed as a promising solution towards developing energy-efficient buildings, VIGs have not become popular in the market due to several technical challenges including the complexity of the fabrication process. In particular, the edge-seal is a key component that significantly affects the thermal insulation and mechanical performance, and the development of edge-seal with adequate thermal insulation, mechanical strength, and reasonable processing cost is essential to overcome such technical issues in VIG. For this purpose, effects of edge-seal design parameters on the VIG performance should be identified. In this research, we analyzed the edge-seal for thermal transport as well as structural stresses to study the effects, and then identified and evaluated the material mixes for the edge-seal requirements. Here, the finite element simulations showed the significance of VIG corner calculation on overall thermal transmittance and the importance of seal conductivity below 1 W/m.K. The experiments with the flexible seals with different ratios of fine glass powder demonstrated that the measured shear strength values for the seal with less than 30% glass powder were more than 10 times larger than the calculated shear stress values. Based on these simulation and experimental results, a flexible sealant was developed using a proprietary mix of ceramic materials that meets the requirements of the designed VIG edge-seal, including structural as well as thermal stress resistance and a low conductivity. Moreover, the sealant is self-curing under atmospheric conditions, and thus it does not require costly inline process of laser curing or oven baking.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Pulling thin single crystal silicon wafers from a melt: The new leading-edge solar substrate

The Floating Silicon Method (FSM) has been established as a viable, stable method for growing single crystal ribbons directly from a silicon melt. With intense helium jet cooling to drive the linear progress of a [111] facet, pulled in the <110> direction, ribbons in the 0.6 – 3.0 mm thickness range can be grown at linear growth rates from 0.3 mm/s to >6 mm/s as reported in the literature. We report on recent progress towards growing (100) oriented ribbons with a net thickness of less than 200 microns and a ribbon width up to 18 cm using a stable, continuous process in the Leading Edge prototype furnace. Here, the 3D details of the single crystal growth are explained by extending the mechanics of the Limit Cycle Theory, with novel Internal Side Effect morphology described by a proposed Facet Flow Theory. Grown-in crystalline defect distributions are described as well as values of critical impurities like oxygen, carbon, dopants, and metals that are relevant for use as wafers for solar cells.

14 SOLAR ENERGY↗

DOE OSTI2023

Integrated RMP-based ELM-crash-control process for plasma performance enhancement during ELM crash suppression in KSTAR

The integrated Resonant Magnetic Perturbation (RMP)-based Edge-Localized Mode (ELM)-crash-control process aims to enhance the plasma performance during the RMP-driven ELM crash suppression, where the RMP induces an unwanted confinement degradation. In this study, the normalized beta ($\beta_\textrm{N}$) is introduced as a metric for plasma performance. The integrated process incorporates the latest achievements in the RMP technique to enhance $\beta_\textrm{N}$ efficiently. The integrated process triggers the n = 1 Edge-localized RMP (ERMP) at the L–H transition timing using the real-time Machine Learning (ML) classifier. The pre-emptive RMP onset can reduce the required external heating power for achieving the same $\beta_\textrm{N}$ by over 10% compared to the conventional onset. During the RMP phase, the adaptive feedback RMP ELM controller, demonstrating its performance in previous experiments, plays a crucial role in maximizing $\beta_\textrm{N}$ during the suppression phase and sustaining the $\beta_\textrm{N}$-enhanced suppression state by optimizing the RMP strength. The integrated process achieves $\beta_\textrm{N}$ up to ~2.65 during the suppression phase, which is ~10% higher than the previous KSTAR record but ~6% lower than the target of the K-DEMO first phase ($\beta_\textrm{N}$ = 2.8), and maintains the suppression phase above the lower limit of target $\beta_\textrm{N}$ (= 2.4) for ~4 s (~60$\tau_\textrm{E}$). In addition to $\beta_\textrm{N}$ enhancement, the integrated process demonstrates quicker restoration of the suppression phase and recovery of $\beta_\textrm{N}$ compared to the adaptive control with the n = 1 Conventional RMP (CRMP). The post-analysis of the experiment shows the localized effect of the ERMP spectrum in radial and the close relationship between the evolution of $\beta_\textrm{N}$ and the electron temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Smart connected worker edge platform for smart manufacturing: Part 1—Architecture and platform design

Abstract The challenge of sustainably producing goods and services for healthy living on a healthy planet requires simultaneous consideration of economic, societal, and environmental dimensions in manufacturing. Enabling technology for data driven manufacturing paradigms like Smart Manufacturing (a.k.a. Industry 4.0) serve as the technological backbone from which sustainable approaches to manufacturing can be implemented. Unfortunately, these technologies are typically associated with broader and deeper factory automation that is often too expensive and complex for the small and medium sized manufacturers (SMMs) that comprise the majority of manufacturing business in the USA and for whom their most valuable asset are the people whose jobs automation while replace. This paper describes an edge intelligent platform to integrate internet‐of‐things technologies with computing hardware, software, computational workflows for machine learning, and data ingestion, enabling SMMs to transition into smart manufacturing paradigms by leveraging the intelligence of their people. The platform leverages consumer grade electronics and sensors (affordable and portable), customized software with open source software packages (accessible), and existing communication network infrastructures (scalable). The software systems are implemented via Kubernetes orchestration of Docker containerization to ensure scalability and programmability. The platform is adaptive via computational workflow engines that produce information from data by processing with low‐cost edge computing devices while efficiently accessing resources of cloud servers as needed. The proposed edge platform connects workers to technological resources that provide computational intelligence (i.e., silicon‐based sensing and computation for data collection and contextualization) to enable decision making at the edge of advanced manufacturing.

Kim, Yoon G.↗

DOE OSTI2023

Electromagnetic turbulence simulation of tokamak edge plasma dynamics and divertor heat load during thermal quench

Abstract The edge plasma turbulence and transport dynamics, as well as the divertor power loads during the thermal-quench phase of tokamak disruptions, are numerically investigated with BOUT++’s flux-driven six-field electromagnetic turbulence model. Here, transient yet intense particle and energy sources are applied at the pedestal top to mimic the plasma power drive at the edge induced by a core thermal collapse, which flattens the core temperature profile. Interesting features, such as surging of divertor heat load (up to 50 times) and broadening of heat-flux width (up to four times) on the outer-divertor target plate, are observed in the simulation, in qualitative agreement with experimental observations. The dramatic changes in divertor heat load and width are due to the enhanced plasma turbulence activities inside the separatrix. Two cross-field transport mechanisms, namely, the E × B turbulent convection and the stochastic parallel advection/conduction, are identified to play important roles in this process. First, an elevated edge pressure gradient drives instabilities and subsequent turbulence in the entire pedestal region. The enhanced turbulence not only transports particles and energy radially across the separatrix via the E × B convection, which causes the initial divertor heat-load burst, but it also induces amplified magnetic fluctuation B ˜ . Once themagnetic fluctuation is large enough to break the magnetic flux surface, magnetic flutter effect provides an additional radial transport channel. In the late stage of our simulation, | B ˜ r / B 0 | reaches to 10 −4 level that completely breaks magnetic flux surfaces such that stochastic field lines are directly connecting pedestal top plasma to the divertor target plates or first wall, further contributing to the divertor heat-flux width broadening.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Developing Digital Twin Visualizations: A Methodology and Case Study on Chemical Separation Processing

As advances in digital engineering continue to push the technological boundaries, digital twin (DT) visualizations for diagnostics and safeguards advancement become much more feasible and practical. DTs generate large and complex data streams that require effective user interfaces to provide monitoring and diagnostic capabilities. Unfortunately, while these frameworks exist, there is not much research on the systematic documentation of human–computer interaction (HCI) for DT visualization. This work presents a dual-mode visualization methodology (two dimensional [2D] graphical user interface dashboard and 3D mixed reality) designed to support diagnostic tasks in DT systems and building on a validated framework and applying established HCI principles. The methodology is demonstrated through a case study of aqueous processing at Idaho National Laboratory, using experimental data from the chemical solvent extraction runs. Our interfaces display real-time alerts and monitoring to inform users of safeguards anomalies. The interfaces use immersive 3D mixed-reality visualization for further system and experiment investigation. This work demonstrates how the systematic application of HCI principles can inform DT visualization design for diagnostic and safeguards applications. While formal user evaluation studies remain as future work, this paper documents the systematic design methodology and demonstrates a proof-of-concept implementation.

3D visualization↗

DOE OSTI2026

Bent Crystal Channeling for Optimized Beam Shadowing and Proton Extraction at Mu2e

The Mu2e experiment is designed to investigate the CLFV through the observation of a neutrinoless muon-to-electron conversion in the field of an Al nucleus. The observation of such a process would be clear evidence of physics beyond the standard model. Due to the rarity of this process, a cutting-edge, intense muon beam is required to achieve an improvement of the current single-event sensitivity by 4 orders of magnitude. To achieve this goal, a primary proton beam with 8 GeV is extracted from the Fermilab Delivery Ring using the slow resonant extraction technique. Mu2e requires ~3.6x10$^{20}$ protons-on-target to meet its goal; hence, it is crucial to minimize the extraction losses. An important source of such losses are the particles impacting on the electrostatic septum blade. A very promising solution to the problem lies in the beam shadowing scheme tested at CERN SPS. In this approach, a bent crystal is strategically placed upstream of the septum, deflecting particles from the blade at a precise angle via the phenomenon of channeling. As a result, a zone with reduced particle flux is created downstream of the crystal, safeguarding the septum anode by minimizing interactions with the beam. This work explores the optimization of beam shadowing design and the process in the manufacturing and characterization of the bent crystal sample. It emphasizes the promising role of channeling in bent crystals, and it underscores the significant potential of channeling in bent crystals to assist the Mu2e experiment.

Fedeli, Pierluigi [Ferrara U.; INFN, Ferrara] (ORC↗

DOE OSTI2025

Wafer-scale waveguide sidewall roughness scattering loss characterization by image processing

Photonic integrated circuits (PICs) are vital for developing affordable, high-performance optoelectronic devices that can be manufactured at an industrial scale, driving innovation and efficiency in various applications. Optical loss of modes in thin film waveguides and devices is a critical measure of their performance. Thin film growth, lithography, masking, and etching processes are imperfect processes that introduce significant sidewall and top-surface roughness and cause dominating optical losses in waveguides and photonic structures. This roughness, as perturbations couple light from guided to far-field radiation modes, leads to scattering losses that can be estimated from theoretical models. Typically, with UV-based lithography, sidewall roughness is significantly larger than wafer-top surface roughness. Atomic force microscopy (AFM) imaging measurement gives a 3D and high-resolution roughness profile, but the measurement is inconvenient, costly, and unscalable for large-scale PICs and at wafer-scale. Here, we evaluate the sidewall roughness profile based on 2D high-resolution scanning electron microscope (SEM) imaging. We characterized the loss on two homemade nitride and oxide films on 3-inch silicon wafers with 12 waveguide devices on each and correlated the scattering loss estimated from a 2D image-based sidewall profile and theoretical Payne model. The lowest loss of guided fundamental transverse electric (TE 0 ) mode is found at 0.075 dB/cm at 633 nm across 24 devices, a record at visible wavelength. Our work shows 100% success (edge continuity span exceeding 95% of image width/height) in edge detection in image processing of all images to estimate autocorrelation function and optical mode loss. These demonstrations offer valuable insights into waveguide sidewall roughness and a comparison of experimental and 2D SEM image processing based loss estimations with applications in loss characterization at wafer-scale PICs.

Khurana, Mohit (ORCID:0000000207898672)↗

DOE OSTI2020

Discrete element modeling of switchgrass particles under compression and rotational shear

Switchgrass is a perennial herbaceous plant regarded as a biomass energy crop in the United States for its highadaptability and yield potential. Processing and handling of switchgrass particles are challenging due to the erratic mechanical and flow behavior originating from their intrinsic particulate properties. Here, we present a bonded-sphere discrete element model designed specifically for switchgrass particles. The model simultaneously captures three key particulate features, i.e., fibrous particle shapes, a wide range of particle sizes, and particle deformability. Realistic yet computationally efficient particle shape templates are created based on the image analysis data of switchgrass specimens. A fitting procedure is proposed to ensure both the particle width and length distributions are captured, a unique requirement for fibrous particles. Two full-scale numerical models, i.e., a uniaxial compression model and a Schulze ring shear model, are developed using information fromphysical experiments. The model is calibrated using experimental data of chopped-small switchgrass specimens, and then, is validated using data of chopped-large specimens in both compression and ring-shear tests. Numerical results show that the numerical models capture bulk densities accurately (with an error of 3%) while slightly underestimate the bulk friction angle. Furthermore, an extensive sensitivity analysis reveals that (1) switchgrass particles with rougher edges (due to different processing techniques) exhibit a higher shear strength and a lower flowability; (2) stiffer particles yield a lower bulk density (up to 21% lower) compared to more deformable particles, indicating particle deformability should be incorporated when modeling biomass flow in a preprocessing system.

09 BIOMASS FUELS↗

DOE OSTI2021

Role of surface diffusion in formation of unique reactivity for graphite oxidation: Time-resolved measurements in a pulsed diffusion reactor

Quantification of oxidation kinetics is essential to develop graphitic materials for diverse applications: from refractories found in gas-cooled nuclear reactors to catalysts needed for chemical manufacturing. In this work, using well-defined highly oriented pyrolytic graphite, low-pressure isotopic transient experiments combined with controlled annealing periods, we resolve the role of surface diffusion and quantify oxidation kinetics with nanomole-precision. We observe an unexpected increase in reactivity following annealing which is explained by the role of surface diffusion increasing the probability for trapping mobile oxygen at more reactive edge sites. Here, the locus of adsorption and spillover to the basal plane is distinct from the trapping location creating a more active oxygen species. Isotopic products reflect the population dynamics of oxygen added at the edge and surface diffusion that relocates basal plane oxygen to more reactive edge sites. Since this process proceeds in parallel with direct oxidation reactions, it is not likely to be observed using steady-state or conventional ‘bulk’ characterization techniques. Our unique time-resolved non-equilibrium measurement in a well-defined transport regime, enables observation of three distinct behaviors: short-term deactivation due to the balance of rates in oxygen supply/product formation, reactivity increases due to surface diffusion and longer-term reactivity increase with oxygen accumulation.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Direct matter disassembly via electron beam control: electron-beam-mediated catalytic etching of graphene by nanoparticles

Here, we report electron-beam activated motion of a catalytic nanoparticle along a graphene step edge and associated etching of the edge. The catalytic hydrogenation process was observed to be activated by a combination of elevated temperature and electron beam irradiation. Reduction of beam fluence on the particle was sufficient to stop the process, leading to the ability to switch on and off the etching. Such an approach enables the targeting of individual nanoparticles to induce motion and beam-controlled etching of matter through activated electrocatalytic processes. The applications of electron-beam control as a paradigm for molecular-scale robotics are discussed.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2024

XRF-XFS-XAS-Auto v1.0 - Beta release

This software allows to analyze XRF maps, XFS spectra and XAS spectra collected at the Advanced Light Source's Beamline 10.3.2. Features include: 1) XRF maps: - process XRF maps, all elemental maps are saved as bmp automatically and labeled with the incident energy used, the scale bar is also labeled and can be controlled. - XRF elemental correlation plots, save the correlation plots automatically - Extract single or multiple transects in XRF maps on one or several regions of interest, each transect profile is numbered and saved in a corresponding folder, along with the corresponding maps showing transect location. 2) XFS spectra - save in log10 scale the XFS spectra, either a single or multiple files all at once. The files are saved as .bmp. - XFS spectra are labeled according to tabulated fluorescence emission lines. 3) XAS spectra - allows to plot individual scalers in the raw data. - allows calibration of the spectra using an Io internal glitch present in all spectra and performing 1st derivative. - Least-square linear combination fitting of XANES or extended XANES spectra using a database of standards using 1, 2 or 3 components maximum. It also provides the 5 top combinations and provide the user for the possibility of saving the 2nd, 3rd, 4th and 5th best combinations in addition to the best one. The processed spectra (pre-edge background substracted, post-edge normalized), the fits and residuals are automatically saved. A table of the component, with fit% and SSN is provided and saved automatically as well.

Fakra, Sirine↗

DOE OSTI2022

Large-Scale Additive Manufacturing of Silicon Carbide with Process Monitoring

This report summarizes new capabilities in additive manufacturing (AM) of large-scale silicon carbide (SiC) components under the Advanced Materials and Manufacturing Technologies (AMMT) program. SiC is a promising material that is being considered for many advanced reactor designs due to its high temperature strength, radiation tolerance, minimal neutron absorption, and oxidation resistance [1-8]. One of the primary limitations to using SiC as an in-core structural material is the inability to fabricate large SiC components with complex geometries. While under the former Transformational Challenge Reactor (TCR) program, ceramic AM systems at the Oak Ridge National Laboratory (ORNL) were limited in the quantity and overall size achievable for producing ceramic AM components. To address this, ORNL has improved its infrastructure for binder jet and chemical vapor infiltration (CVI) processes with cutting-edge equipment coming online in a newly renovated laboratory space capable of producing larger components and higher throughput without compromise on part size. This report details the laboratory renovation progress, focusing specifically on the DesktopMetal (formerly ExOne) X25Pro binder jet, a large scale CVI furnace, and the added functionality of a software tool called Peregrine for quality assurance and control purposes.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A Novel Standard Gibbs Energy of Formation Model for High-Enthalpy Water Systems

This work provides an advanced standard molar Gibbs energy of formation model, informed by molecular statistical thermodynamics (MST), and validated by mineral solubility and ion association reactions. This new model aligns with experimental data within uncertainties and highlights the role of specific MST interactions around the critical point. This work will provide a reliable tool for the optimization of industrial processes operating at the edges of the supercritical domain.

Hall, Derek↗

DOE OSTI2025

Mesoscale Modeling of Dislocation Cell Structure Evolution and Radiation-Induced Segregation in Additively Manufactured Austenitic Stainless Steel

Structural alloys under irradiation develop radiation-induced segregation (RIS) at point defect sinks, which lead to undesired changes in the alloy's properties. Additively manufactured austenitic stainless steels are expected to yield a distinct response to irradiation damage owing to their unique as-printed dislocation cell structure. In this talk, we present the development of a mesoscale model for dislocation cell structure evolution coupled with RIS using the MOOSE framework. The evolution of network dislocations within spatially distinct cells and cell walls are modeled using climb-mediated edge annihilation and generation processes. Starting with initial microstructures of as-printed non-equilibrium segregations at dislocation cell walls, our 2D and 3D simulations explore the effects of irradiation temperature, dose rate, dislocation sink bias, and specimen thickness on microstructure evolution. The results will be compared against experimental characterizations of in-situ and ex-situ ion-irradiated samples, and the implications of evolving cell structure on irradiation damage response will be discussed.

additive manufacturing↗