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Application Table: A Bridge Connecting the Designing “With-the-Material” and “the-Material”

Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.

Materials↗
NASA NTRS2010

Modeling of Atmospheric Turbulence as Disturbances for Control Design and Evaluation of High Speed Propulsion Systems

Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying integrated couplings between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms. Then a generalized formulation is developed in frequency domain for these scale models that approximates the fractional order with the products of first order transfer functions. Given the parameters describing the conditions of atmospheric disturbances and utilizing the derived formulations, the objective is to directly compute the transfer functions that describe these disturbances for acoustic velocity, temperature, pressure and density. Utilizing these computed transfer functions and choosing the disturbance frequencies of interest, time domain simulations of these representative atmospheric turbulences can be developed. These disturbance representations are then used to first develop considerations for disturbance rejection specifications for the design of the propulsion control system, and then to evaluate the closed-loop performance.

Kopasakis, George↗
NASA NTRS2015

Iodine Satellite

The Iodine Satellite (iSat) spacecraft will be the first CubeSat to demonstrate high change in velocity from a primary propulsion system by using Hall thruster technology and iodine as a propellant. The mission will demonstrate CubeSat maneuverability, including plane change, altitude change and change in its closest approach to Earth to ensure atmospheric reentry in less than 90 days. The mission is planned for launch in fall 2017. Hall thruster technology is a type of electric propulsion. Electric propulsion uses electricity, typically from solar panels, to accelerate the propellant. Electric propulsion can accelerate propellant to 10 times higher velocities than traditional chemical propulsion systems, which significantly increases fuel efficiency. To enable the success of the propulsion subsystem, iSat will also demonstrate power management and thermal control capabilities well beyond the current state-of-the-art for spacecraft of its size. This technology is a viable primary propulsion system that can be used on small satellites ranging from about 22 pounds (10 kilograms) to more than 1,000 pounds (450 kilograms). iSat's fuel efficiency is ten times greater and its propulsion per volume is 100 times greater than current cold-gas systems and three times better than the same system operating on xenon. iSat's iodine propulsion system consists of a 200 watt (W) Hall thruster, a cathode, a tank to store solid iodine, a power processing unit (PPU) and the feed system to supply the iodine. This propulsion system is based on a 200 W Hall thruster developed by Busek Co. Inc., which was previously flown using xenon as the propellant. Several improvements have been made to the original system to include a compact PPU, targeting greater than 80 percent reduction in mass and volume of conventional PPU designs. The cathode technology is planned to enable heaterless cathode conditioning, significantly increasing total system efficiency. The feed system has been designed to include iodine compatible control valves with internal heaters and temperature sensors to coincide with the iodine-compatible thruster. A key advantage to using iodine as a propellant is that it may be stored in the tank as an unpressurized solid on the ground and before flight operations. During operations, the tank is heated to vaporize the propellant. Iodine vapor is then routed through custom flow control valves to control mass flow to the thruster and cathode assembly. The thruster then ionizes the vapor and accelerates it via magnetic and electrostatic fields, resulting in high specific impulse, characteristic of a highly efficient propulsion system. The iSat spacecraft is a 12-unit (12U) CubeSat with dimensions of about 8 inches x 8 inches x 12 inches (20 centimeters x 20 centimeters x 30 centimeters). The spacecraft frame will be constructed from aluminum with a finish to prevent iodine-driven corrosion. The iSat spacecraft includes full three-axis control and will leverage heat generated by spacecraft components and radiators for a passive thermal control system. After the CubeSat has successfully detached from its launch vehicle, it will deploy its solar panels, correct for tip-off and maintain attitude control before ground contact. An initial check-out period of two weeks is planned for testing all subsystems. The spacecraft will charge the power system while in sunlight, using momentum wheels and magnetic torque rods to rotate the vehicle to the required attitude.

iSat↗
NASA NTRS2019

X-Ray Photoelectron Spectroscopy

The interaction of photon and the electron goes back to the early part of 19th century emanating from the photo-electric effect depicted by none other than Albert Einstein (Ref 1) described in 1905, and the redistribution of kinetic energy resulting from the interaction of x-ray and solids reported during early part of the century (Ref.2). The spectrum resolutions obtained at that time was not sufficient to observe distinct peaks in spectra for materials. Thus, these phenomena hardly attracted any attention for many years following these discoveries. The modern X-ray Photoelectron Spectroscopy (XPS) has been possible by the extensive and significant contribution from Kai Siegbahn and others (Ref.3, 4) of Uppsala University. Siegbahn developed and employed a high-resolution electron spectrometer that revealed electron peaks in a spectrum emerging from the interaction of x-rays and solids. Eventually, Kai Siegbahn received Nobel Prize in 1981 for his contributions to XPS. Around 1958, shifts in elemental peaks were realized in compounds when the same elements are bound to other but different elements. This discovery resulted in the chemical state identification in various chemicals as well as the oxidation states of atoms in compounds. Because of these useful physical effects, the Uppsala group named XPS with a synonymous name of ESCA (Electron Spectroscopy for Chemical Analysis) used widely today and will be used here alternatively. Therefore, XPS or ESCA not only identifies the element, but also the compound these elements form, from their chemical shifts. Compared to other micro-analytical techniques such as Energy Dispersive (EDS) or Wavelength Dispersive (WDS) techniques, XPS analyzes only few atomic layers present on the surface. This was discovered early in 1966 (Ref. 5). While this has awarded a merit to the analytical technique to analyze very thin layers such as films and coatings, it often analyzes the adsorbed superficial gases and contaminations on a sample introduced to its analytical chamber. This necessitates the surface is cleaned and the underlying material, material of interest, is exposed in a clean environment such that the material of interest is analyzed. The cleaning is accomplished by a scanning ion gun within the analytical chamber of the instrument. Ion gun uses an argon gas and is commonly attached in most modern machines. Reliable and efficient vacuum systems employed in modern machines does not allow adsorbed layers to rebuild after the surface is cleaned. Development of efficient and reliable vacuum pumps over these developmental years is yet another important step in the commercialization of XPS machines. Vacuum levels of better than 10-7 torr are essential to increase the mean free path of electrons released from the sample surface. Thus, modern machines are equipped with high capacity ion, turbo or cryogenic pumps in their analytical chambers. Today, XPS has advanced from an applied physics laboratory to industry for use in quality control as well as analysis of contaminants and has taken a dominant role in microanalysis. Its uniqueness arises from the fact that it is considered non-destructive compared to other common micro-analytical techniques using the electron and ion excitation sources. Polymers and plastics could be analyzed since the binding energies of saturated and unsaturated bonds in atoms could be separated. Extremely thin layers could be analyzed including materials with layered structures. The technique, though did not advance for many years, has now opened a new window for research as well as applications in industry due to its ability to separate and measure the chemical shifts in bound elements. Principles

Panda, Binayak↗
NASA NTRS2019

Earth Science Technology Office (ESTO) New Observing Strategies (NOS) and NOS-Testbed (NOS-T)

With the advancement of space hardware technologies such as smaller spacecraft, component and instrument miniaturization and high performance space processors, and with the advancement of software technologies in artificial intelligence, big data analysis and autonomous decision making, Earth Science is looking at novel ways to observe phenomena that previously could not have been studied or would have been too expensive to study with traditional missions. In particular, the New Observing Strategies (NOS) component of the NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) Program aims at leveraging these novel technologies as well as low cost and easy access to space to acquire multi-temporal or simultaneous multi-angular, multi-locations, multi-resolution and multi-spectral observations that will provide better multi-source measurements and will build a more dynamic and comprehensive picture of Earth Science phenomena that need to be studied and analyzed. For applications such as water resources management, air quality monitoring, biodiversity studies or disaster management, NOS will integrate the use of small instruments, small spacecraft, constellations of spacecraft and networks of sensors to design new missions that will provide the necessary measurements to improve future forecast and science modeling systems.Measurement acquisition will therefore be approached as a system of systems rather than on a mission basis, and a system of this complexity should not be expected to work without full integration and experimental characterization. Although most of the individual technologies enabling to link and coordinate multi-source observations are more or less mature, a few technologies need to be developed and all of them need to be integrated and tested as a system. In order for this validation to occur, the AIST Program is developing the NOS Testbed that includes 3 main goals:1.Validate novel NOS technologies, independently and as a system2.Demonstrate novel distributed operations concepts3.Socialize new Distributed Spacecraft Mission (DSM) and SensorWeb (SW) technologies and concepts to the science community by significantly retiring the risk of integrating these new technologies.The NOS Testbed will consist of multiple sensing nodes, simulated or actual, representing space, air and/or ground measurements, that are interconnected by a communications fabric (infrastructure that permits nodes to transmit and receive data between one another and interact with each other). Each node will be supported by hardware capabilities required to perform nodes monitoring and command & control, as well as intelligent "onboard" computing. The nodes will work together in a collaborative manner to demonstrate optimal science capabilities. The testbed will enable to validate technologies such as inter-node communication models, techniques and protocols; inter-node coordination; real-time data fusion and understanding; planning; sensor re-targeting; etc. Additionally, the testbed will have the capability to interact with various mission design tools, OSSEs and one or several forecast models. More details about the NOS Testbed will be presented at the confererence.

Earth Science missions; Advanced information Syste↗
DOE OSTI2023

Direct Visualization of Charge Migration in Bilayer Tantalum Oxide Films by Multimodal Imaging

Inspired by biological neuromorphic computing, artificial neural networks based on crossbar arrays of bilayer tantalum oxide memristors have shown to be promising alternatives to conventional complementary metal-oxide-semiconductor (CMOS) architectures. In order to understand the driving mechanism in these oxide systems, tantalum oxide films are resistively switched by conductive atomic force microscopy (C-AFM), and subsequently imaged by kelvin probe force microscopy (KPFM) and spatially resolved time-of-flight secondary ion mass spectrometry (ToF-SIMS). These workflows enable induction and analysis of the resistive switching mechanism as well as control over the resistively switched region of the film. In this work it is shown that the resistive switching mechanism is driven by both current and electric field effects. Reversible oxygen motion is enabled by applying low (<1 V) electric fields, while high electric fields generate irreversible breakdown of the material (>1 V). Fully understanding oxygen motion and electrical effects in bilayer oxide memristor systems is a fundamental step toward the adoption of memristors as a neuromorphic computing technology.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Insights from a coupled thermo-hydro-mechanical analysis of a layered high-temperature thermal energy storage reservoir

Coupled thermal-hydraulic-mechanical (THM) modeling is applied to investigate the performance of a seasonal high-temperature aquifer thermal energy storage operation based on data and conditions from current site investigations at the Geostorage Forsthaus pilot project in Bern (Switzerland). The model includes subhorizontal sand lenses of various lengths and dips that are embedded in a low permeability clay matrix. Thermal energy storage is simulated by seasonal injection and withdrawal of hot (up to 90 °C) water from a main well, with reservoir pressure regulated by two auxiliary wells at a distance of about 70 m from the main well. The results show how targeted injection into deeper permeable storage formations, along with active deep well pressure control, can effectively minimize geomechanical impact and the potential risk of damaging subsurface storage and sealing formations, or even surface facilities. With such pressure control, the subsurface mechanical responses are dominated by thermal strain and stress, which can be monitored with subsurface fiber optics. The study demonstrates how coupled THM modeling can be applied for the design of a safe and efficient thermal energy storage operation, and how subsurface fiber optic monitoring can be applied for performance confirmation, allowing for more confident operational forecasting.

Rutqvist, Jonny↗
DOE OSTI2021

Binding mechanism and binding free energy of amino acids and citrate to hydroxyapatite surfaces as a function of crystallographic facet, pH, and electrolytes

Hydroxyapatite (HAP) is the major mineral phase in bone and teeth. The interaction of individual amino acids and citrate ions with different crystallographic HAP surfaces has remained uncertain for decades, creating a knowledge gap to rationally design interactions with peptides, proteins, and drugs. In this contribution, we quantify the binding mechanisms and binding free energies of the 20 end-capped natural amino acids and citrate ions on the basal (001) and prismatic (010)/(020) planes of hydroxyapatite at pH values of 7 and 5 for the first time at the molecular scale. We utilized over 1500 steered molecular dynamics simulations with highly accurate potentials that reproduce surface and hydration energies of (hkl) hydroxyapatite surfaces at different pH values. Charged residues demonstrate a much higher affinity to HAP than charge-neutral species due to the formation of superficial ion pairs and ease of penetration into layers of water molecules on the mineral surface. Binding free energies range from 0 to -60 kJ/mol and were determined with ~10% uncertainty. The highest affinity was found for citrate, followed by Asp(-) and Glu(-), and followed after a gap by Arg(+), Lys(+), as well as by His(+) at pH 5. The (hkl)-specific area density of calcium ions, the protonation state of phosphate ions, and subsurface directional order of the ions in HAP lead to surface-specific binding patterns. Amino acids without ionic side groups exhibit weak binding, between -3 and 0 kJ/mol, due to difficulties to penetrate the first layer of water molecules on the apatite surfaces. We explain recognition processes that remained elusive in experiments, in prior simulations, discuss agreement with available data, and reconcile conflicting interpretations. In conclusion, the findings can serve as useful input for the design of peptides, proteins, and drug molecules for the modification of bone and teeth-related materials, as well as control of apatite mineralization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A robust deep learning workflow to predict multiphase flow behavior during geological C O 2 sequestration injection and Post-Injection periods

Simulation of multiphase flow in porous media is essential to manage the geologic CO 2 sequestration (GCS) process, and physics-based simulation approaches usually take prohibitively high computational cost due to the nonlinearity of the coupled physics. This paper contributes to the development and evaluation of a deep learning workflow that accurately and efficiently predicts the temporal-spatial evolution of pressure and CO 2 plumes during injection and post-injection periods of GCS operations. Based on a Fourier Neural Operator, the deep learning workflow takes input variables or features including rock properties, well operational controls and time steps, and predicts the state variables of pressure and CO 2 saturation. To further improve the predictive fidelity, separate deep learning models are trained for CO 2 injection and post-injection periods due to the difference in primary driving force of fluid flow and transport during these two phases. We also explore different combinations of features to predict the state variables. We use a realistic example of CO 2 injection and storage in a 3D heterogeneous saline aquifer, and apply the deep learning workflow that is trained from physics-based simulation data and emulate the physics process. Through this numerical experiment, we demonstrate that using two separate deep learning models to distinguish post-injection from injection period generates the most accurate prediction of pressure, and a single deep learning model of the whole GCS process including the cumulative injection volume of CO 2 as a deep learning feature, leads to the most accurate prediction of CO 2 saturation. For the post-injection period, it is key to use cumulative CO 2 injection volume to inform the deep learning models about the total carbon storage when predicting either pressure or saturation. The deep learning workflow not only provides high predictive fidelity across temporal and spatial scales, but also offers a speedup of 250 times compared to full physics reservoir simulation, and thus will be a significant predictive tool for engineers to manage the long-term process of GCS.

58 GEOSCIENCES↗
DOE OSTI2021

Stress-dominated growth of two-dimensional materials on nonplanar substrates

Curved features are ubiquitous on solid surfaces, but the effect of surface curvatures on growth of two-dimensional (2D) materials has not yet been established. Using a newly developed method based on the Metropolis algorithm and taking graphene as a prototype, we find that a curved feature on substrates can result in a variety of topological defects in 2D materials. As the feature's size increases by just nanometers, the defects can vary from adatoms, dislocation pairs, and grain boundary scars to long-range grain boundaries, in contrast to previously reported defect-free modes of rigid colloidal crystals growing on spheres. We identify an important role of curvature-induced lattice stress in lowering the growth rate over the curved features and driving a plastic instability in the materials. When the feature's size increases to several nanometers, the stress effect is compromised by an enhanced effect of geodesic curvature, yielding long-range grain boundaries as a result of increased local growth rate on the feature with respect to that on flat regions. Here we further provide a ‘phase diagram’ of defects that helps to guide a rational choice of geometrical parameters of features towards the growth of high-quality 2D materials as well as controllable creation of topological defects.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Cyber–physical vulnerability and resiliency analysis for DER integration: A review, challenges and research needs

High penetration of renewable and sustainable Distributed Energy Resources (DER) into the traditional distribution system requires a well-coordinated control strategy for the improvement of system-wide reliability and resiliency. Implementation of such a holistic control architecture requires a flexible, near real-time, and bi-directional communication framework for facilitating the participation of various agents in a multi-vendor heterogeneous smart grid. While the sustainability of energy generation is ensured, this exposes the smart grid to extrinsic cyber threats, and appropriate defense mechanism(s) must be deployed to guarantee continued reliability and resiliency of the power grid. Further, the comprehensive literature review presented in this paper discusses the latest trends in the DER control schemes with fast communication requirements and their accompanying cyber–physical vulnerabilities. These control schemes are compared and contrasted for various traits. A three-level DER system architecture has been depicted, facilitating the deployment of these control schemes. The current developments of standard communication protocols, key security mechanisms, and best practices along major standards and guidelines are explored. The impacts of different attack types with miscellaneous DER functions based on various control schemes and associated mitigation solutions are also provided. Finally, challenges and future research directions for limiting cyber-power susceptibility to enhance resiliency are summarized. The work presented here will help us enabling a cyber-resilient and sustainable smart electric grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Valence Effects of Fe Impurity for Recovered LiNi 0.6 Co 0.2 Mn 0.2 O 2 Cathode Materials

Iron impurities are generally included in the obtained leaching liquor solution during the hydrometallurgical recycling method of spent lithium-ion batteries (LIBs) due to the usage of iron in battery casings and machinery parts of recycling equipment, which would definitely affect the physical and electrochemical features of the recovered active materials. In this paper, the effects of iron impurity with different valence states (Fe 2+ and Fe 3+ ) and gradient concentrations (0.2, 1.0, and 5.0 at. %) for the obtained LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NCM622) cathodes are fully studied. It is found that Fe3+ impurity could easily lower the tap density and average size of NCM622 particles and even introduce some impurity phases in the NCM622 structure at high concentration (5.0 at. %), leading to much lower specific capacity, worse rate capability, and cycling performance of the Fe 3+ -based NCM622 cathode. On contrast, with certain concentrations of Fe 2+ impurity (0.2 and 1.0 at. %), the NCM622 cathode material exhibits comparable and much better electrochemical properties compared with the virgin NCM622 materials. Based on these results, the valence of Fe impurity should be considered and controlled as well as its concentration during the recycling process design for spent LIBs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Time-Resolved Observation of Hole Tunneling in van der Waals Multilayer Heterostructures

We reported a time-resolved study of quantum-mechanical tunneling of holes between two MoSe 2 monolayers that are separated by a monolayer WS 2 energy barrier. Four-layer heterostructures of MoSe 2 /WS 2 /MoSe 2 /graphene, as well as control samples, were fabricated by mechanical exfoliation and dry transfer techniques. To time-resolve the hole tunneling process, an ultrashort laser pulse was used to excite electrons and holes in both MoSe 2 layers. Here, by utilization of the graphene layer to eliminate carriers in the third MoSe 2 layer, the first MoSe 2 layer is selectively populated with the holes, which then tunnel to the third MoSe 2 layer. By monitoring decay of the hole population with an ultrashort probe pulse, we measure a hole tunneling time of about 20 ps, which is found to slightly increase with the injected carrier density. Besides the fundamental interests of real-time observation of the quantum-mechanical tunneling effect across a nanometer barrier, these results provide quantitative understanding on tunneling mechanisms of charge transfer in van der Waals heterostructures, which is useful for designing sophisticated van der Waals multilayer heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Structural evidence for intermediates during O 2 formation in photosystem II

In natural photosynthesis, the light-driven splitting of water into electrons, protons and molecular oxygen forms the first step of the solar-to-chemical energy conversion process. The reaction takes place in photosystem II, where the Mn 4 CaO 5 cluster first stores four oxidizing equivalents, the S 0 to S 4 intermediate states in the Kok cycle, sequentially generated by photochemical charge separations in the reaction center and then catalyzes the O–O bond formation chemistry. Here, we report room temperature snapshots by serial femtosecond X-ray crystallography to provide structural insights into the final reaction step of Kok’s photosynthetic water oxidation cycle, the S 3 →[S 4 ]→S 0 transition where O 2 is formed and Kok’s water oxidation clock is reset. Our data reveal a complex sequence of events, which occur over micro- to milliseconds, comprising changes at the Mn 4 CaO 5 cluster, its ligands and water pathways as well as controlled proton release through the hydrogen-bonding network of the Cl1 channel. Importantly, the extra O atom O x , which was introduced as a bridging ligand between Ca and Mn1 during the S 2 →S 3 transition disappears or relocates in parallel with Y z reduction starting at approximately 700 μs after the third flash. The onset of O 2 evolution, as indicated by the shortening of the Mn1–Mn4 distance, occurs at around 1,200 μs, signifying the presence of a reduced intermediate, possibly a bound peroxide.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

TDCOSMO. IX. Systematic comparison between lens modelling software programs: time delay prediction for WGD 2038-4008

The importance of alternative methods for measuring the Hubble constant, such as time-delay cosmography, is highlighted by the recent Hubble tension. It is paramount to thoroughly investigate and rule out systematic biases in all measurement methods before we can accept new physics as the source of this tension. In this study, we perform a check for systematic biases in the lens modelling procedure of time-delay cosmography by comparing independent and blind time-delay predictions of the system WGD 2038-4008 from two teams using two different software programs: GLEE and LENSTRONOMY. The predicted time delays from the two teams incorporate the stellar kinematics of the deflector and the external convergence from line-of-sight structures. The un-blinded time-delay predictions from the two teams agree within 1.2σ, implying that once the time delay is measured the inferred Hubble constant will also be mutually consistent. However, there is a ~4σ discrepancy between the power-law model slope and external shear, which is a significant discrepancy at the level of lens models before the stellar kinematics and the external convergence are incorporated. We identify the difference in the reconstructed point spread function (PSF) to be the source of this discrepancy. When the same reconstructed PSF was used by both teams, we achieved excellent agreement, within ~0.6σ<, indicating that potential systematics stemming from source reconstruction algorithms and investigator choices are well under control. We recommend that future studies supersample the PSF as needed and marginalize over multiple algorithms or realizations for the PSF reconstruction to mitigate the systematics associated with the PSF. A future study will measure the time delays of the system WGD 2038-4008 and infer the Hubble constant based on our mass models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak

Active feedback control in magnetic confinement fusion devices is desirable to mitigate plasma instabilities and enable robust operation. Optical high-speed cameras provide a powerful, non-invasive diagnostic and can be suitable for these applications. Here, in this study, we process high-speed camera data, at rates exceeding 100 kfps, on in situ field-programmable gate array (FPGA) hardware to track magnetohydrodynamic (MHD) mode evolution and generate control signals in real time. Our system utilizes a convolutional neural network (CNN) model, which predicts the n = 1 MHD mode amplitude and phase using camera images with better accuracy than other tested non-deep-learning-based methods. By implementing this model directly within the standard FPGA readout hardware of the high-speed camera diagnostic, our mode tracking system achieves a total trigger-to-output latency of 17.6 μs and a throughput of up to 120 kfps. This study at the High Beta Tokamak-Extended Pulse (HBT-EP) experiment demonstrates an FPGA-based high-speed camera data acquisition and processing system, enabling application in real-time machine-learning-based tokamak diagnostic and control as well as potential applications in other scientific domains.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Metabolic profiling of epidermal and mesophyll tissues under water-deficit stress in Opuntia ficus-indica reveals stress-adaptive metabolic responses

Cactus pear (Opuntia ficus-indica) is a high productivity species within the Cactaceae grown in many semiarid parts of the world for food, fodder, forage, and biofuels. O. ficus-indica utilises obligate crassulacean acid metabolism (CAM), an adaptation that greatly improves water-use efficiency (WUE) and reduces crop water usage. To better understand CAM-related metabolites and water-deficit stress responses of O. ficus-indica, comparative metabolic profiling was performed on mesophyll and epidermal tissues collected from well-watered and water-deficit stressed cladodes at 50% relative water content (RWC). Tissues were collected over a 24-h period to identify metabolite levels throughout the diel cycle and analysed using a combination of acidic/basic ultra-high-performance liquid chromatography/tandem mass spectrometry (UHPLC/MS/MS) and gas chromatography/mass spectrometry (GC/MS) platforms. A total of 382 metabolites, including 210 (55%) named and 172 (45%) unnamed compounds, were characterised across both tissues. Most tricarboxylic acid (TCA) cycle and glycolysis intermediates were depleted in plants undergoing water-deficit stress indicative of CAM idling or post-idling, while the raffinose family oligosaccharides (RFO) accumulated in both mesophyll and epidermal tissues as osmoprotectants. Levels of reduced glutathione and other metabolites of the ascorbate cycle as well as oxylipins, stress hormones such as traumatic acid, and nucleotide degradation products were increased under water-deficit stress conditions. Notably, tryptophan accumulation, an atypical response, was significantly (24-fold) higher during all time points in water-deficit stressed mesophyll tissue compared with well-watered controls. Many of the metabolite increases were indicative of a highly oxidising environment under water-deficit stress. A total of 34 unnamed metabolites also accumulated in response to water-deficit stress indicating that such compounds might play important roles in water-deficit stress tolerance.

Plant Sciences↗
DOE OSTI2022

Eddy current flow meter model validation with a moving solid rod*

We report that the eddy current flow meter (ECFM) has been used to measure velocities and temperatures of conductive flows, such as liquid metal flows in a nuclear fission reactor. The goal of this paper is to develop a finite element electromagnetic model that can characterize the ECFM sensor performance and validate this finite element model with detailed velocity measurements of a controlled, well-characterized moving conductive solid rod. Both measurements and modeling were performed for various parameters that are important for ECFM performance such as rod velocity, rod material, ECFM sensor coil length, number of sensor coils, applied alternating current (AC) current amplitude, and applied ECFM AC frequency. For all parametric scans, the measurement and modeling agree well in both magnitude and trend. The normalized root-mean-square error between measurement and modeling is less than 10% for all cases. These results suggest that electromagnetic modeling could eventually be used to cost-effectively design future ECFM sensors in arbitrary geometry for more challenging applications such as liquid metal nuclear fission reactors.

47 OTHER INSTRUMENTATION↗