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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Lunar Soil Enrichment for Plant Production: WILD (Waste Improved Lunar Dirt)

To identify a process to generate a fertile soil for plant growth using lunar regolith and waste compost, several qualitative and quantitative investigations were performed. The primary focus of this project was to demonstrate the feasibility of microbe bioleaching to extract inorganic plant nutrients (P and K) from lunar regolith simulant. This was achieved by developing a screening test method to identify microbial candidates that would effectively bioleach P and K from JSC-1A. Quantitative bioleaching test using the downselected microbes (Pantoea Agglomerans (P. agglo) and a plant-relevant consortium) were then performed. The second focus of the project was to validate the approach of waste compost utilization to improve water retention and fertility of lunar regolith for food production. This was achieved by measuring the water retention property of the mixture of compost and regolith at different ratio and conducting microgreen growth experiments with compost/regolith mixtures. The team also discovered from this study that some native microbes associated with JSC-1A can form biofilm containing JSC-1A particles (a type of soil crust), which showed potential as an ISRU geomicrobiological dust mitigation method for Lunar or Martian applications.

Ray Pitts↗
NASA NTRS2011

NASA Tech Briefs, March 2011

Topics covered include: Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation; Airborne Radar Interferometric Repeat-Pass Processing; Plug-and-Play Environmental Monitoring Spacecraft Subsystem; Power-Combined GaN Amplifier with 2.28-W Output Power at 87 GHz; Wallops Ship Surveillance System; Source Lines Counter (SLiC) Version 4.0; Guidance, Navigation, and Control Program; Single-Frame Terrain Mapping Software for Robotic Vehicles; Auto Draw from Excel Input Files; Observation Scheduling System; CFDP for Interplanetary Overlay Network; X-Windows Widget for Image Display; Binary-Signal Recovery; Volumetric 3D Display System with Static Screen; MMIC Replacement for Gunn Diode Oscillators; Feature Acquisition with Imbalanced Training Data; Mount Protects Thin-Walled Glass or Ceramic Tubes from Large Thermal and Vibration Loads; Carbon Nanotube-Based Structural Health Monitoring Sensors; Wireless Inductive Power Device Suppresses Blade Vibrations; Safe, Advanced, Adaptable Isolation System Eliminates the Need for Critical Lifts; Anti-Rotation Device Releasable by Insertion of a Tool; A Magnetically Coupled Cryogenic Pump; Single Piezo-Actuator Rotary-Hammering Drill; Fire-Retardant Polymeric Additives; Catalytic Generation of Lift Gases for Balloons; Ionic Liquids to Replace Hydrazine; Variable Emittance Electrochromics Using Ionic Electrolytes and Low Solar Absorptance Coatings; Spacecraft Radiator Freeze Protection Using a Regenerative Heat Exchanger; Multi-Mission Power Analysis Tool; Correction for Self-Heating When Using Thermometers as Heaters in Precision Control Applications; Gravitational Wave Detection with Single-Laser Atom Interferometers; Titanium Alloy Strong Back for IXO Mirror Segments; Improved Ambient Pressure Pyroelectric Ion Source; Multi-Modal Image Registration and Matching for Localization of a Balloon on Titan; Entanglement in Quantum-Classical Hybrid; Algorithm for Autonomous Landing; Quantum-Classical Hybrid for Information Processing; Small-Scale Dissipation in Binary-Species Transitional Mixing Layers; Superpixel-Augmented Endmember Detection for Hyperspectral Images; Coding for Parallel Links to Maximize the Expected Value of Decodable Messages; and Microwave Tissue Soldering for Immediate Wound Closure.

Source record↗
DOE OSTI2024

Prediction of O and OH Adsorption on Transition Metal Oxide Surfaces from Bulk Descriptors

In the search for stable and active catalysts, density functional theory and machine learning (ML) based models can accelerate the screening of materials. While stability is conveniently addressed on the bulk level of computation, the modelling of catalytic activity requires expensive surface simulations. Here, in this work, we develop models for the surface adsorption energy of O and OH intermediates across a consistent and extensive dataset of pure transition metal oxide surfaces. We show that adsorption energies across metal oxidation states of +2 to +6 are well captured from the metal-oxygen bond strength extracted from the bulk level calculation. Specifically, we calculate the integrated crystal orbital Hamiltonian population (ICOHP) of the metal-oxygen bond in the bulk oxide and employ a simple normalization scheme to obtain a strong correlation with adsorption energetics. By combining our ICOHP descriptor with non DFT features in a Gaussian Process regression (GPR) model, we achieve high model accuracy with mean absolute errors of 0.166 and 0.219 eV for OH and O adsorption, respectively. By targeting the O-OH adsorption energy difference with our GPR model, we predict the the oxygen evolution reaction (OER) activity from bulk descriptors only. Furthermore, we utilize the strong correlation between the COHP and metal oxygen bond lengths to rapidly predict adsorption energetics and catalytic activity from the optimized bulk geometry. Our approach can enable an efficient search for active catalysts by eliminating the need for surface calculations in the initial screening phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Two-dimensional forms of robust CO 2 reduction photocatalysts

Photoelectrocatalysts that use sunlight to power the CO 2 reduction reaction will be crucial for carbon-neutral power and energy-efficient industrial processes. Scalable photoelectrocatalysts must satisfy a stringent set of criteria, such as stability under operating conditions, product selectivity, and efficient light absorption. Two-dimensional materials can offer high specific surface area, tunability, and potential for heterostructuring, providing a fresh landscape of candidate catalysts. From a set of promising bulk CO 2 reduction photoelectrocatalysts, we screen for candidate monolayers of these materials, then study their catalytic feasibility and suitability. For stable monolayer candidates, we verify the presence of visible-light band gaps, check that band edges can support CO 2 reduction, determine exciton binding energies, and compute surface reactivity. We find visible light absorption for SiAs, ZnTe, and ZnSe monolayers, and that due to a lack of binding, CO selectivity is possible. We thus identify SiAs, ZnTe, and ZnSe monolayers as targets for further investigation, expanding the chemical space for CO 2 photoreduction candidates.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Characterization of the image plate multi-scan response to mono-energetic x-rays

Image plates (IPs), or phosphor storage screens, are a technology employed frequently in inertial confinement fusion (ICF) and high energy density plasma (HEDP) diagnostics because of their sensitivity to many types of radiation, including, x rays, protons, alphas, beta particles, and neutrons. Prior studies characterizing IPs are predicated on the signal level remaining below the scanner saturation threshold. Since the scanning process removes some signal from the IP via photostimulated luminescence, repeatedly scanning an IP can bring the signal level below the scanner saturation threshold. This process, in turn, raises concerns about the signal response of IPs after an arbitrary number of scans and whether such a process yields, for example, a constant ratio of signal between the nth and n + 1st scan. Here, the sensitivity of IPs is investigated when scanned multiple times. It is demonstrated that the ratio of signal decay is not a constant with the number of scans and that the signal decay depends on the x-ray energy. As such, repeatedly scanning an IP with a mixture of signal types (e.g., x ray, neutron, and protons) enables ICF and HEDP diagnostics employing IPs to better isolate a particular signal type.

Instruments & Instrumentation↗
DOE OSTI2020

Harnessing the power of ab initio calculations, distributed computing and machine learning to efficiently locate extreme molecules for use in carbon-based solar cells (Final Technical Report)

The use of high-throughput virtual screening (HTVS) tools is a powerful tool to expedite the materials discovery of commercially relevant materials. In previous years, our group has developed a molecular discovery platform to generate libraries in order to obtain suitable candidates for different applications, starting from the Harvard Clean Energy Project. This platform is suitable to test in-silico on traditional supercomputing clusters and shared resources, for example, in the IBM World Community Grid. In this project, we used the molecular discovery platform to create and screen a library of candidates of organic photovoltaic (OPVs) molecules. Based on a set of candidates created with combinations of molecular moieties, we were able to filter, by conformation stability, the energy of electronic orbitals and approximated power conversion efficiencies (PCE). To improve the predictions of orbital energies calculated and the PCEs, we used Gaussian Process regression and two sets of molecules. These sets correspond to electronic structure calculations of a higher level of theory and experimental PCE values, respectively. Finally, we selected a subset of the best candidates (molecules with a PCE higher than 10%) to understand its absorbance properties with TD-DFT. This project has demonstrated the capabilities of our molecular discovery platform for HTVS. Finally, machine learning can help us to introduce more complex effects included in bulk conditions and computational intensive calculations on models.

14 SOLAR ENERGY↗
DOE OSTI2024

Automated AI-driven Molecular Design for Therapeutic Discovery

In recent years, artificial intelligence and machine learning (AI/ML) approaches have revolutionized the process of designing new therapeutics, enabling scientists to rapidly respond to emerging threats from various pathogens. A prime example is the SARS-CoV-2 main protease, a key target for the development of antiviral inhibitors. In this study, we employed a novel, integrated approach that combines AI-driven iterative design of inhibitor candidates, screening based on physio-chemical properties and toxicity, physics-based computational modeling of protein-inhibitor interactions, and AI-assisted analysis of Native MS biophysical assay and characterization of designed candidates. Our deep learning 3D-scaffold model, which uses an input scaffold as a starting point, generated tens of thousands of compounds while preserving the key scaffold. To optimize these candidates, we calculated a comprehensive set of 136 descriptors, including both 2D and 3D molecular features, for compounds targeting the SARS-CoV-2 Main protease (Mpro) and a neurodegenerative disease-associated protein, cyclophilin (Cyp). The generated compounds were initially filtered based on their properties and then ranked according to their predicted binding affinity using our automated modeling and ML methods. Experimental validation of the Mpro candidates showing inhibitory activity demonstrates that our workflow can expedite the therapeutic discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1974

Holography and the control of self-propelled vehicles

The possibility of applying the principles of holography and optical data processing in the control of self-propelled space vehicles is considered. Various methods of controlling space vehicles are described: (1) by the results of comparing the image with the standard hologram; (2) by holographic images transmitted over moon earth communications channels; and (3) on the basis of using autotelevision cameras with a three dimensional screen. Procedures are presented for obtaining the standard holograms. The structural organization of the microprogrammed automaton controlling the movement of the space vehicle is also presented.

Yeroshin, V. I.↗
DOE OSTI2020

Energy Master Planning: Identifying Framing Constraints that Scope Your Technology Options

This paper addresses the framing constraints for building and community energy projects that must be considered when energy master planning (EMP) is conducted. The constraints cover emissions, sustainability, resilience, regulations and directives, and regional and local limitations such as available energy types, local conditions, and project requirements. The paper reflects development results from participants in an International Energy Agency project on energy master planning and in a U.S. Department of Defense project on technology integration to achieve resilient, low-energy use military installations. It identifies a comprehensive list of framing constraints categorized into locational threats, locational resources, energy and water distribution and storage systems, building and facility, indoor environmental, and equipment in buildings and district systems constraints. In addition, it identifies limits for these constraints that exist in seven participating countries. Some framing constraints can profoundly impact technology selection while others impact the installation of technologies (as in hardening) and have little to no impact on technology selection. Furthermore, framing constraints can be assessed in different ways and there are resources available to help EMP stakeholders evaluate them. Finally, a case is made that identifying and applying framing constraints early in EMP can bring efficiencies and better focus to the EMP process. We come to the conclusion that (1) for holistic energy planning, it is essential to identify and assess the framing constraints that bound an optimized EMP solution, (2) framing constraints limits should be evaluated as either hard or soft or promising technologies may fall out of an EMP analysis, (3) to maintain consistent quality in the EMP process, the identification of framing constraints and their limits, and perhaps their evaluation, should be standardized, (4) a standardized approach could establish a baseline that can be used, built upon, and improved, (5) as automated EMP tools are improved or developed, the resources in this paper could possibly contribute to their interworkings relative to technology screening, and (6) continued climate change and resulting aggressive goal setting will likely drive a continued and strong emphasis on EMP.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Small- and Wide-Angle X-ray Scattering Studies of Liquid–Liquid Phase Separation in Silicate Melts

Incongruent liquid-liquid phase separation is a common phenomenon in molten oxides, but there are few structural studies due to the high temperatures involved ca. >1600oC. In this work, we present a high-energy x-ray combined small/wide angle scattering (SAXS/WAXS) method that can directly probe non-equilibrium phase diagrams. The Porod exponent in the SAXS signal is extracted, which measures the roughness of the interface formed between different phases. Problematic volatilization of silica in Al 2 O 3 -, CaO-, and MgO-bearing silica-rich liquids were minimized using levitation, laser heating and rapid time-resolved measurements (lasting tens of seconds), to probe the kinetics of the phase separation process. The WAXS measurement simultaneously probes the local atomic structure of the liquid state and shows that the primary structural changes are associated with the SiO 2 network. Cation coordination numbers extracted from pair distribution functions support the model that the origin of phase separation in binary silicate systems is due to Coulombic repulsions between poorly screened cations. For CaO-SiO 2 , the liquid-liquid phase separation is found to correlate with a pause in the temperature dependent atomic disorder associated with SiO4 tetrahedra.

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

Radiological Safety Analysis Computer (RSAC) Program Version 7.4 Users’ Manual

The Radiological Safety Analysis Computer (RSAC) Program Version 7.4 (RSAC-7) is the newest version of the RSAC legacy code. RSAC-7 calculates the consequences of a release of radionuclides to the atmosphere. Users generates a fission product inventory from either reactor operating history or a nuclear criticality event. RSAC-7 models the effects of high-efficiency particulate air filters or other cleanup systems and calculates the decay and ingrowth during transport through processes, facilities, and the environment. Doses are calculated for inhalation, air immersion, ground surface, ingestion, and cloud gamma pathways. RSAC-7 is used as a tool to evaluate accident conditions in emergency response scenarios, radiological sabotage events, and safety basis accident consequences. This users’ manual contains the mathematical models and operating instructions for RSAC-7. Instructions, screens, and examples are provided to guide the user through the functions provided by RSAC-7. This program is designed for users who are familiar with radiological dose assessment methods.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2020

Space Flight LiDARs, Navigation & Science Instrument Implementations: Lasers, Optoelectronics, Integrated Photonics, Fiber Optic Subsystems and Components

For the past 25 years, the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center's Photonics Group in the Engineering Directorate has been substantially contributing to the flight design, development, production, testing and integration of many science and navigational instruments. The Moon to Mars initiative will rely heavily upon utilizing commercial technologies for instrumentation with aggressive schedule deadlines. The group has an extensive background in screening, qualifying, development and integration of commercial components for spaceflight applications. By remaining adaptable and employing a rigorous approach to component and instrument development, they have forged and fostered relationships with industry partners. They have been willing to communicate lessons learned in packaging, part construction, materials selection, testing, and other facets of the design and production process critical to implementation for high-reliability systems. As a result, this successful collaboration with industry vendors and component suppliers has enabled a history of mission success from the Moon to Mars (and beyond) while balancing cost, schedule, and risk postures. In cases where no commercial components exist, the group works closely with other teams at Goddard Space Flight Center and other NASA field centers to fabricate and produce flight hardware for science, remote sensing, and navigation applications. Summarized here is the last ten years of instrumentation development lessons learned and data collected from the subsystems down to the optoelectronic component level.

Detectors↗
NASA NTRSDate not supplied

NASA GPM Status and Future Activities

The joint U.S.-Japan Global Precipitation Measurement (GPM) mission is approaching a decade of operations, and continues to pursue research, dataset production, and outreach related to precipitation. Key activities over the last year were the release of an improved “Version 07” of all GPM precipitation and latent heating products, boosting the orbit of the GPM Core Observatory (GPM CO) to 435 km, and improving quality control on precipitation retrievals from the GPM constellation of passive microwave satellites. This presentation summarizes key improvements to the GPM products and provides some examples of the changes between Versions 06 and 07 in algorithm performance. One important operational change that affected Version 07 is that the scanning strategy for the Ka-band radar channel changed in May 2018; all products that depend on Ka were revised to accommodate this change. For example, in Version 07 the Goddard Profiling (GPROF) algorithm has implemented improvements in regions where orographic enhancement and suppression take place and where the surface is snowy/icy, and again covers radiometers reaching back to 1987. The Combined Radar Radiometer Algorithm (CORRA) now incorporates modified drop-size distribution constraints that substantially reduce bias. Revisions to the Convective-Stratiform Heating (CSH) algorithm employ new radiative transfer retrievals as well as accounting for terrain in the vertical coordinates. Each algorithm was adjusted to ensure continuity for each product across the boundary in 2014 between the predecessor Tropical Rainfall Measuring Mission (TRMM) and the GPM CO. The U.S. Science Team’s Integrated Multi-satellitE Retrievals for GPM (IMERG) was upgraded to account for distortions in the probability density function of regional precipitation rates due to weighted averaging in the Kalman filter used for “morphing” the passive microwave data. Maintaining the GPM CO orbital altitude in the the current very active solar cycle has been forcing the use of more fuel than planned and consequently shortening the forecasted life of the mission from the early 2030's to the late 2020's. It was considered vital to regain some of this lifetime to ensure overlap with the upcoming Atmosphere Observing System mission to provide crosscalibration of instruments. To accomplish this, the orbital altitude was raised from 400 to 435 km on 7-8 November 2023. Thereafter, the primary GPM CO algorithms had to be revised to account for the change in observing parameters. By meeting time this action should be complete. Recently, a screening algorithm based on auto-encoding was developed that uncovered 162 orbits (out of the many thousands of orbits across all years and all satellites) of passive microwave retrievals that had highly anomalous values. Removing these defective retrievals has improved the integrity of both the GPROF and IMERG records. However, the nature of the IMERG processing interacted sufficiently badly with the now-discovered anomalous orbits that it was necessary to completely reprocess the IMERG Final Run record, now labeled Version 07B. The presentation also considers major issues that require continued attention, including the use of machine learning algorithms and the operational challenge of swarms of “small”, perhaps short-lived satellites.

GPM↗
DOE OSTI2025

Sustainable Triacetic Acid Lactone Production from Sugarcane by Fermentation and Crystallization

Triacetic acid lactone (TAL) has the potential to serve as a bioderived platform chemical for commercial products including sorbic acid and recyclable polydiketoenamine plastics. In this study, we leveraged BioSTEAM to design, simulate, and evaluate (via techno-economic analysis, TEA, and life cycle assessment, LCA) TAL production from sugarcane. We experimentally characterized TAL solubility, calibrated solubility models, and designed a process to separate TAL from fermentation broths by crystallization. The biorefinery could produce TAL at a minimum product selling price (MPSP) of $\$3.73$–5.86·kg –1 (5th–95th percentiles; baseline at $\$4.60$·kg –1 ) and a carbon intensity (CI) of 5.31 [2.60–8.71] kg CO 2 -eq·kg –1 , which could enable financially viable, low-CI production of sorbic acid and polydiketoenamines. To drive down costs and CI, we explored the theoretical fermentation space (titer, yield, productivity combinations), operation scheduling and capacity expansion strategies (e.g., integrated sorghum processing), and potential separation improvements (mitigating TAL loss through pH control). Advancements in key design and technological parameters could further reduce MPSP by 51% to $\$2.26$·kg –1 [$\$1.97$–2.80·kg –1 ] and CI by 43% to 3.05 [1.91–4.15] kg CO 2 -eq·kg –1 . This research highlights the ability of agile TEA-LCA to screen promising designs, navigate sustainability trade-offs, prioritize research needs, and chart quantitative roadmaps to advance bioproducts and biofuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Core hole processes in x-ray absorption and photoemission by resonant Auger-electron spectroscopy and first-principles theory

Electron–core hole interactions are critical for proper interpretation of core-level spectroscopies commonly used as analytical tools in materials science. Here we utilize resonant Auger-electron spectroscopy to uniquely identify exciton, shake, and charge-transfer processes that result from the sudden creation of the core hole in both x-ray-absorption and photoemission spectra. These effects are captured for the transition-metal compounds SrTiO 3 and MoS 2 by fully ab initio, combined real-time cumulant, and Bethe-Salpeter equation approaches to account for core hole dynamics and screening. Atomic charges and excited-state electron-density fluctuations reflect materials’ solid-state electronic structure, loss of translational symmetry around the core hole, and breakdown of the sudden approximation. They also demonstrate competition between long- and short-range screening in a solid.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2005

Tool for Ranking Research Options

Tool for Research Enhancement Decision Support (TREDS) is a computer program developed to assist managers in ranking options for research aboard the International Space Station (ISS). It could likely also be adapted to perform similar decision-support functions in industrial and academic settings. TREDS provides a ranking of the options, based on a quantifiable assessment of all the relevant programmatic decision factors of benefit, cost, and risk. The computation of the benefit for each option is based on a figure of merit (FOM) for ISS research capacity that incorporates both quantitative and qualitative inputs. Qualitative inputs are gathered and partly quantified by use of the time-tested analytical hierarchical process and used to set weighting factors in the FOM corresponding to priorities determined by the cognizant decision maker(s). Then by use of algorithms developed specifically for this application, TREDS adjusts the projected benefit for each option on the basis of levels of technical implementation, cost, and schedule risk. Based partly on Excel spreadsheets, TREDS provides screens for entering cost, benefit, and risk information. Drop-down boxes are provided for entry of qualitative information. TREDS produces graphical output in multiple formats that can be tailored by users.

Ortiz, James N.↗
NASA NTRS2017

Identification of Novel Desiccation-Tolerant S. cerevisiae Strains for Deep Space Biosensors

NASA's BioSentinel mission, a secondary payload that will fly on the Space Launch Systems first Exploration Mission (EM-1), utilizes the budding yeast S. cerevisiae to study the biological response to the deep space radiation environment. Yeast samples are desiccated prior to launch to suspend growth and metabolism while the spacecraft travels to its target heliocentric orbit beyond Low Earth Orbit. Each sample is then rehydrated at the desired time points to reactivate the cells. A major risk in this mission is the loss of cell viability that occurs in the recovery period following the desiccation and rehydration process. Cell survival is essential for the detection of the biological response to features in the deep space environment, including ionizing radiation.The aim of this study is to mitigate viable cell loss in future biosensors by identifying mutations and genes that confer tolerance to desiccation stress in rad51, a radiation-sensitive yeast strain. We initiated a screen for desiccation-tolerance after rehydrating cells that were desiccated for three years, and selected various clones exhibiting robust growth. To verify retention of radiation sensitivity in the isolated clonesa crucial feature for a successful biosensorwe exposed them to ionizing radiation. Finally, to elucidate the genetic and molecular bases for observed desiccation-tolerance, we will perform whole-genome sequencing of those rad51 clones that exhibit both robust growth and radiation sensitivity following desiccation. The identification and characterization of desiccation-tolerant strains will allow us to engineer a biological model that will be resilient in face of the challenges of the deep space environment, and will thus ensure the experimental success of future biosensor missions.

S. cerevisiae↗
DOE OSTI2025

xGFabric: Coupling Sensor Networks and HPC Facilities with Private 5G Wireless Networks for Real-Time Digital Agriculture

Advanced scientific applications require coupling distributed sensor networks with centralized high-performance computing facilities. Citrus Under Protective Screening (CUPS) exemplifies this need in digital agriculture, where citrus research facilities are instrumented with numerous sensors monitoring environmental conditions and detecting protective screening damage. CUPS demands access to computational fluid dynamics codes for modeling environmental conditions and guiding real-time interventions like water application or robotic repairs. These computing domains have contrasting properties: sensor networks provide low-performance, limited-capacity, unreliable data access, while high-performance facilities offer enormous computing power through high-latency batch processing. Private 5G networks present novel capabilities addressing this challenge by providing low latency, high throughput, and reliability necessary for near-real-time coupling of edge sensor networks with HPC simulations. This work presents xGFabric, an end-to-end system coupling sensor networks with HPC facilities through Private 5G networks. The prototype connects remote sensors via 5G network slicing to HPC systems, enabling real-time digital agriculture simulation.

Digital Agriculture↗