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NASA NTRS2022

S-band Network Analysis and Strategies for LEO Multi-CubeSat Science Missions

This paper presents the network architecture utilized at NASA’s Goddard Space Flight Center (GSFC) to support a mission set of five 6U CubeSats. These five CubeSats employ a multi-waveform Software Defined Radio (SDR) platform developed by Vulcan Wireless for use with NASA’s Space Relay (SR) and Direct to Earth (DTE) networks. The performance testing of the SDR is discussed via a comprehensive S-band and communication link analysis. The tested capabilities of the SDR and antenna components are reviewed in terms of the mission requirements for each CubeSat. Size Weight and Power (SWaP), required availability, and access times are discussed. The measured data from experimental compatibility testing is incorporated into detailed simulations of the CubeSat mission set to verify desired performance over the mission lifetime. The model is also used to investigate the impact of potential adverse effects on the communication links such as interference and weather conditions. This paper also reviews potential improvements from future technological advances and commercial partnerships. A collaborative investigation between GSFC and Oklahoma State University is presented in which a qualitative analysis of Hybrid RF/Optical communication strategies is performed. The data rate improvements of optical communication techniques are weighed against attitude control and science mission requirements for CubeSats, and network architectures/switching strategies are discussed. A separate analysis reviews the potential benefits of ground station partnerships, which aligns with NASA’s future goal to include commercial partners in its Earth and space network architectures, e.g. LunaNet.

Space networks↗

DOE OSTI2026

Constructing a High‐Resolution Aftershock Catalog for the 2017 Mw 8.2 Tehuantepec Earthquake Sequence Using a Machine Learning–Based Workflow

The 8 September 2017 Mw 8.2 Tehuantepec earthquake was the largest instrumentally recorded normal‐faulting earthquake in Mexico. The mainshock occurred offshore within the Tehuantepec seismic gap, generating >30,000 aftershocks in the following year. We applied an open‐source, machine learning (ML)–assisted workflow to construct a high‐resolution aftershock catalog using data from temporary and permanent seismic networks in southern Mexico. The workflow integrates PhaseNet for phase detection; GaMMA for phase association; and VELEST, HypoInverse, and HypoDD for velocity modeling and relocation. We processed seven months of continuous waveform data from 29 broadband stations, including a temporary rapid‐response deployment that improved station coverage of the offshore rupture zone. To evaluate performance, we compared our results against analyst‐reviewed picks and event locations from the Servicio Sismológico Nacional catalog. The resulting catalog contains 11,374 relocated earthquakes and represents the most comprehensive published dataset for this sequence, incorporating the first full use of the temporary network. Relocated hypocenters show improved depth control and align well with the Slab2.0 subduction geometry, revealing clearer separation between offshore slab events and onshore crustal seismicity. This study demonstrates that combining ML‐based detection with established methods provides a scalable and reproducible approach for constructing high‐quality earthquake catalogs in tectonically complex environments and offers practical guidance for adapting similar workflows to other earthquake sequences.

Garcia, Marc [The University of Texas at El Paso, ↗

DOE OSTI2024

Critical Minerals and Materials Matchmaker-CM3

This is the Critical Minerals and Materials Matchmaker (CM3) survey form. CM3 is an online information resource created to help connect users across the critical minerals and materials supply chain. The survey is designed to allow organizations to self-identify their critical minerals and materials-aligned activities and interests, and an interactive map that displays those on-going activities in a dynamic way. To include your critical minerals management activity or activities in CM3, please open and fill out the Critical Minerals and Materials Survey. If your organization has many ongoing or planned activities that would be onerous to enter in the form, or if your activities are difficult to geolocate (such as a transport network), please email the team at edxspatial@netl.doe.gov. This initiative is aligned with the approach of DOE’s H2 Matchmaker and Carbon Matchmaker. Read more information on H2 Matchmaker and Carbon Matchmaker. Below are some questions to help understand if you should fill out the CM3 survey: Does your company work with elements such as lithium, cobalt, copper, graphite, nickel, rare earth minerals, or platinum group metals? Does your organization have research and development activities related to critical materials or their supply chains? Does your company currently work in the critical minerals or materials supply chain? Do you have prospective work in critical minerals or materials in the next 5 years? Does your company mine, process, refine or distribute critical minerals or materials? Do you want to network with other facilities or organizations working in the same areas? Are you curious about the critical mineral and material activity in your surrounding area? Are you interested in aligning your potential needs across the supply chain to different geographic areas within the U.S? For more information, please see the CM3 website (https://www.energy.gov/fecm/articles/critical-minerals-materials-matchmaker-cm3) or email our team at edxspatial@netl.doe.gov.

CM3↗

NASA NTRS2003

Applications of High Etendue Line-Profile Spectro-Polarimetry to the Study of the Atmospheric and Magnetospheric Environments of the Jovian Icy Moons

Electrodynamic effects play a significant, global role in the state and energization of the Earth's ionosphere/magnetosphere, but even more so on Jupiter, where the auroral energy input is four orders of magnitude greater than on Earth. The Jovian magnetosphere is distinguished from Earth's by its rapid rotation rate and contributions from satellite atmospheres and internal plasma sources. The electrodynamic effects of these factors have a key role in the state and energization of the ionosphere-corona- plasmasphere system of the planet and its interaction with Io and the icy satellites. Several large scale interacting processes determine conditions near the icy moons beginning with their tenuous atmospheres produced from sputtering, evaporative, and tectonic/volcanic sources, extending out to exospheres that merge with ions and neutrals in the Jovian magnetosphere. This dynamic environment is dependent on a complex network of magnetospheric currents that act on global scales. Field aligned currents connect the satellites and the middle and tail magnetospheric regions to the Jupiter's poles via flux tubes that produce as bright auroral and satellite footprint emissions in the upper atmosphere. This large scale transfer of mass, momentum, and energy (e.g. waves, currents) means that a combination of complementary diagnostics of the plasma, neutral, and and field network must be obtained near simultaneously to correctly interpret the results. This presentation discusses the applicability of UV spatial heterodyne spectroscopy (SHS) to the broad study of this system on scales from satellite surfaces to Jupiter's aurora and corona.

Harris, Walter M.↗

NASA NTRS2011

Ice Shape Characterization Using Self-Organizing Maps

A method for characterizing ice shapes using a self-organizing map (SOM) technique is presented. Self-organizing maps are neural-network techniques for representing noisy, multi-dimensional data aligned along a lower-dimensional and possibly nonlinear manifold. For a large set of noisy data, each element of a finite set of codebook vectors is iteratively moved in the direction of the data closest to the winner codebook vector. Through successive iterations, the codebook vectors begin to align with the trends of the higher-dimensional data. In information processing, the intent of SOM methods is to transmit the codebook vectors, which contains far fewer elements and requires much less memory or bandwidth, than the original noisy data set. When applied to airfoil ice accretion shapes, the properties of the codebook vectors and the statistical nature of the SOM methods allows for a quantitative comparison of experimentally measured mean or average ice shapes to ice shapes predicted using computer codes such as LEWICE. The nature of the codebook vectors also enables grid generation and surface roughness descriptions for use with the discrete-element roughness approach. In the present study, SOM characterizations are applied to a rime ice shape, a glaze ice shape at an angle of attack, a bi-modal glaze ice shape, and a multi-horn glaze ice shape. Improvements and future explorations will be discussed.

McClain, Stephen T.↗

NASA NTRS1990

An Optimal Design For Steerable Dish Antenna With BWG

New design proposed for highly-efficient 34-m-diameter millimeter-wavelength antennas of NASA's Deep Space Network. Incorporates axial beam waveguide, BWG, and improved structure to maintain shape and alignment of reflecting surfaces. General approach to conceptual construction of structure to modularize overall system so critical constraint conditions pertaining to microwave optics and structural performance satisfied. Design retrofitted to existing NASA Deep Space Network 34-m antennas, or used as basis to build large ground-based steerable antennas. Engineering concepts involved in design adapted to design of other large, steerable antennas for telecommunications, radio astronomy, and military uses.

Chuang, K. L.↗

DOE OSTI2024

Stiffness anisotropy coordinates supracellular contractility driving long-range myotube-ECM alignment

The ability of cells to organize into tissues with proper structure and function requires the effective coordination of proliferation, migration, polarization, and differentiation across length scales. Skeletal muscle is innately anisotropic; however, few biomaterials can emulate mechanical anisotropy to determine its influence on tissue patterning without introducing confounding topography. Here, we demonstrate that substrate stiffness anisotropy coordinates contractility-driven collective cellular dynamics resulting in C2C12 myotube alignment over millimeter-scale distances. When cultured on mechanically anisotropic liquid crystalline polymer networks (LCNs) lacking topography, C2C12 myoblasts collectively polarize in the stiffest direction. Cellular coordination is amplified through reciprocal cell-ECM dynamics that emerge during fusion, driving global myotube-ECM ordering. Conversely, myotube alignment was restricted to small local domains with no directional preference on mechanically isotropic LCNs of the same chemical formulation. These findings provide valuable insights for designing biomaterials that mimic anisotropic microenvironments and underscore the importance of stiffness anisotropy in orchestrating tissue morphogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1989

A mesoscale analysis of the pre-storm environment on the 17 June 1986 COHMEX day

The study presented utilized special mesoscale Cooperative Huntsville Meteorological Experiment (COHMEX) data to understand the evolution of the preconvective environment on June 17, 1986. Using the special mesoscale COHMEX data, several mechanisms for triggering the convection are investigated. Afternoon heating probably was a major factor as observed noontime temperatures were near the sounding-derived convection temperatures. The special surface network revealed a quasi-stationary area of convergence not aligned with the front that may be associated with the orography of the area. This study demonstrates that rapid, small scale atmospheric variations preceded convective development on June 17, 1986.

Fuelberg, Henry E.↗

DOE OSTI2025

Hydrologic Model Data for the East Fork Poplar Creek Watershed Simulated with the Advanced Terrestrial Simulator (ATS): Streamflow and Network Expansion–Contraction Dynamics

This dataset supports hydrologic modeling and stream network expansion–contraction analysis for the East Fork Poplar Creek (EFPC) Watershed in Tennessee. It includes a Jupyter notebook for model setup, model configuration files, simulation outputs, and derived products used to evaluate model performance and investigate stream dynamics under varying hydrologic conditions. The dataset was generated using the Watershed Workflow Python package and the Advanced Terrestrial Simulator (ATS), enabling integrated surface–subsurface hydrologic simulations using a stream-aligned mesh. Outputs include high-resolution time series of streamflow, active network length, water table depth, and related hydrologic variables. Also included are spatially explicit stream persistency indices and classifications of reaches as perennial or non-perennial. These data facilitate reproducibility and support further research on stream intermittency and variability in network extent.The model data archive is organized in following directories:1) model_setup_inputsContains the Watershed Workflow Jupyter notebooks (accessed through any open source code editor), selected input datasets, and resulting ATS input files, including XML files (access through any open source code editor), computational mesh (.exo files can be viewed using Paraview), and meteorological forcing files (.h5 files can be accessed through h5py python package and HDFView open source software). 2) model_outputsIncludes ATS simulation outputs relevant to this study. Time series of spatially integrated or averaged variables (e.g., streamflow, water table depth) are provided as CSV files. Select spatial fields (e.g., ponded depth and water table depth) are saved as pickled Python objects to reduce file size, and can be accessed through pickle package in Python. Key geometry objects from Watershed Workflow—such as the surface mesh and river tree—are also included to support analysis of streamflow persistency and expansion–contraction dynamics. These files can also be accessed through Watershed Workflow Python package.3) model_evaluationProvides observed streamflow time series and field survey-based flow regime classifications used to evaluate model performance. Jupyter notebooks for processing ATS outputs and comparing model predictions with observations to build confidence in the model prior to scientific analysis are also included.4) Q_L_relationshipsContains workflows for generating time series of discharge, active network length, and related hydrologic variables used in the stream network expansion–contraction analysis. Includes routines for delineating baseflow-dominated periods. For each catchment, notebooks and processed data (as pickled DataFrames accessed through Pandas Python package) are provided. 5) figure_scriptsProvides the Jupyter notebooks used to generate the figures presented in the paper.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2020

Workshop on Space Quantum Communications and Networks

NASA’s Space Communications and Navigation (SCaN) program and the National Institute of Science and Technology (NIST) co-sponsored a two-day workshop in January 2020 on space quantum communications and networks. The workshop was hosted by the Space Sciences Laboratory of the University of California, Berkeley. About 70 invited technical and program leaders from academia, industry, and government agencies defined science goals and technology requirements for a future NASA “quantum mission” that is fully aligned with the National Quantum Initiative (NQI) vision for a space-ground quantum network. This NQI vision is also a strategic milestone in SCaN’s plans for NASA’s space-based quantum communications and networks. The overall technical objectives of the Workshop were to (i) critically evaluate various mission design concepts, (ii) converge on a small subset of quantum communication and networking experiments suitable for space applications, and (iii) identify key technology gaps and promote new and emerging technologies to enable NASA’s “quantum mission” within a 5-year horizon.

quantum communications↗

DOE OSTI2025

Exocortex Network for AI-Augmented Human-Led Scientific Expedition

AI advances in science can be viewed along two main directions with a fluid boundary: enhancing efficiency through automation and smart tools to accelerate tasks that humans can already perform; and enabling exploration into uncharted territories and potentially toward AGI. These advances manifest in the AI cognitive core through the development and explainability of foundation models; in the physical embodiment of instruments and facilities; and in the integrated agency of AI workflows exemplified by the science exocortex. To address the role of humans in this evolving landscape, in this Perspective, we suggest a third direction: the development of personalized agents that form human-centered networks, supporting both efficiency and exploration while ensuring that AI remains aligned with human vision.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Dynamic Validation of CNN-Based Surrogate Models for Inverter-Based Resources in Open-Source Solvers

Traditionally, distribution system planning has focused on steady-state analyses, with limited consideration of dynamic behavior. However, as large or medium-scale inverter-based resources (IBRs), particularly grid-following (GFL) inverters in commercial or industry buildings, become more prevalent, understanding their dynamic impact is essential for grid planning and operation. This article presents an innovative deep-learning (DL)-approach using convolutional neural networks technique to model the GFL inverters. Developed from real grid-tied commercial IBR transient data, these dynamic DL models overcome proprietary constraints by requiring minimal knowledge of internal converter physics while maintaining high accuracy and flexibility. To demonstrate their applicability, the models were incorporated into GridLAB-D, an open-source, three-phase distribution analysis tool. This integration enables dynamic simulations of large-scale distribution networks with high IBR penetration stability analysis. Rigorous testing and validation, aligned with industry standards, confirmed the reliability and efficiency of this approach, paving the way for enhanced planning and operational assessments of modern power systems.

Deep-learning↗

DOE OSTI2026

Wyoming Carbon Blueprint A Roadmap for Statewide Carbon Capture and Storage

Wyoming stands at a pivotal point in defining its energy future, and the Wyoming Carbon Blueprint positions the state to lead the nation in carbon management through a coordinated buildout of carbon capture, transportation, utilization, and geologic storage. Building on Wyoming’s long history as a major producer of coal, oil, and natural gas, and supported by favorable policies, skilled labor, and robust subsurface resources, the Blueprint outlines a pathway to develop one of the world’s first open-access carbon hubs capable of capturing between 10 and 25 million tonnes of CO₂ per year within five years, and up to 45 million tonnes within a decade. In doing so, it advances the concept of “No Carbon Left Behind”: a statewide strategy that prevents stranded CO₂ by aligning capture, transport, and storage systems into a single coherent infrastructure network.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Insights from Femtosecond Transient Absorption Spectroscopy into the Structure–Function Relationship of Glyceline Deep Eutectic Solvents

This study aimed to determine the structure–function relationship (SFR) for ChCl–glycerol mixtures, a deep eutectic solvent (DES), by investigating their microscopic solvation dynamics and how it relates to their macroscopic properties across varying concentrations of ChCl. Femtosecond transient absorption (fs-TA) spectroscopy revealed two distinct solvation dynamics time constants: τ 1 , governed by glycerol–glycerol interactions, and τ 2 , dominated by the choline response. The τ 2 minimum at 25–30 mol % ChCl closely aligned with the eutectic composition (~33.33 mol % ChCl), where the glycerol network was the most organized and the choline ions exhibited the fastest relaxation. The viscosity decreased sharply up to ~25 mol % ChCl and then plateaued, while the conductivity increased monotonically with ChCl concentration, reflecting enhanced ionic mobility. The density decreased with both increasing ChCl concentration and temperature, indicating disrupted hydrogen bonding and reduced molecular packing. The polarity, measured using betaine-30 (B30) and the E T (30) polarity scale, increased steeply up to approximately 25 mol % ChCl before reaching a plateau. These findings identified the eutectic composition as the optimal concentration range for balancing stability, fluidity, conductivity, and enhanced dynamics within the glycerol system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1998

Turbulent Compressible Convection with Rotation: Mean Flows and Differential Rotation - 2

The effects of rotation on turbulent, compressible convection within stellar envelopes are studied through three-dimensional numerical simulations conducted within a local f-plane model. This work seeks to understand the types of differential rotation that can be established in convective envelopes of stars like the Sun, for which recent helioseismic observations suggest an angular velocity profile with depth and latitude at variance with many theoretical predictions. This paper analyzes the mechanisms that are responsible for the mean (horizontally averaged) zonal and meridional flows that are produced by convection influenced by Coriolis forces. The compressible convection is considered for a range of Rayleigh, Taylor, and Prandtl (and thus Rossby) numbers encompassing both laminar and turbulent flow conditions under weak and strong rotational constraints. When the nonlinearities are moderate, the effects of rotation on the resulting laminar cellular convection leads to distinctive tilts of the cell boundaries away from the vertical. These yield correlations between vertical and horizontal motions that generate Reynolds stresses that can drive mean flows, interpretable as differential rotation and meridional circulations. Under more vigorous forcing, the resulting turbulent convection involves complicated and contorted fluid particle trajectories, with few clear correlations between vertical and horizontal motions, punctuated by an evolving and intricate downflow network that can extend over much of the depth of the layer. Within such networks are some coherent structures of vortical downflow that tend to align with the rotation axis. These yield a novel turbulent alignment mechanism, distinct from the laminar tilting of cellular boundaries, that can provide the principal correlated motions and thus Reynolds stresses and subsequently mean flows. The emergence of such coherent structures that can persist amidst more random motions is a characteristic of turbulence with symmetries broken by rotation and stratification. Such structure is here found to play a crucial role in defining the mean zonal and meridional flows that coexist with the convection. Though they are subject to strong inertial oscillations, the strength and type of the mean flows are determined by a combination of the laminar tilting and the turbulent alignment mechanisms. Varying the parameters produces a wide range of mean motions. Among these, some turbulent solutions exhibit a mean zonal velocity profile that is nearly constant with depth, much as deduced by helioseismology at midlatitudes within the Sun. The solutions exhibit a definite handedness, with the direction of the persistent mean flows often prescribing a spiral with depth near the boundaries, also in accord with helioseismic deductions. The mean helicity has a profile that is positive in the upper portion of the domain and negative in the lower portion, a property bearing on magnetic dynamo processes that may be realized within such rotating layers of turbulent convection.

Brummell, Nicholas H.↗

DOE OSTI2025

Leveraging FPGA Advantages for Quicker Data Processing for LBNF

The Long Baseline Neutrino Facility (LBNF) will deliver a 2.4 MW muon neutrino beam from Fermilab to the Deep Underground Neutrino Experiment (DUNE), requiring unprecedented precision in beamline alignment to achieve DUNE's neutrino oscillation measurement goals. Vertical misalignments of beamline components as small as 0.5 mm can contribute 6-7\% uncertainty in predicted neutrino flux, necessitating sub-0.1 mm alignment monitoring capabilities. The Horn Location Sensor (HLS) system employs frequency sweep interferometry (FSI) in a distributed hydrostatic leveling network to achieve the required precision under harsh radiation conditions up to 5000 kRad/year. Traditional FSI implementations suffer from laser sweep nonlinearities that degrade resolution and require computationally intensive post-processing corrections using gas reference cells. This work presents a real-time FPGA-based implementation of the HLS data acquisition and processing system using a sweep tracker interferometer for dynamic sweep linearization. The system utilizes a PYNQ-Z2 FPGA with programmable logic implementing parallel 16k-point FFT processing across four channels, synchronized by the sweep tracker signal to eliminate post-processing requirements. Spectral performance testing demonstrates significant improvements in peak sharpness compared to traditional fixed-frequency digitization. The FPGA implementation enables real-time displacement monitoring with processing speeds orders of magnitude faster than software-based approaches, essential for the operational requirements of LBNF's eventual distributed sensor network. This advancement in real-time FSI processing directly supports DUNE's precision neutrino physics program by providing the rapid feedback necessary for maintaining stringent beamline alignment tolerances during high-power beam operations.

Rossel, Jacob↗

DOE OSTI2025

Real-Time FPGA Implementation For Frequency Sweep Interferometry In The LBNF Complex

Rossel, A. Jacob [Fermilab; Unlisted]↗

DOE OSTI2026

Self-aligned heterogeneous quantum photonic integration

Integrated quantum photonics holds significant promise for scalable photonic quantum information processing, quantum repeaters, and quantum networks, but its development is hindered by the mismatch between materials hosting high-quality quantum emitters and those compatible with mature photonic technologies. Heterogeneous integration offers a potential solution to this challenge, yet practical implementations have been limited by inevitable insertion losses at material interfaces. Here, we present a self-aligned heterogeneous quantum photonic integration approach that enables near-unity coupling efficiency at the interface. To showcase our approach, we demonstrate Purcell enhancement of a silicon vacancy (SiV) center in diamond induced by a heterogeneous photonic crystal cavity defined by titanium dioxide (TiO 2 ), as well as optical spin control and readout via a TiO 2 photonic circuit. We further show that, when combined with inverse photonic design, our approach enables efficient and broadband collection of single photons from a color center into a heterogeneous waveguide. Our approach is not restricted to SiV centers or TiO 2 ; it has the potential to be broadly applied to integrate diverse solid-state quantum emitters with thin-film photonic devices where conformal deposition is possible. Together, these results establish a practical route to scalable quantum photonic integrated circuits that combine high-quality quantum emitters with technologically mature photonic platforms.

36 MATERIALS SCIENCE↗