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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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At least 631 records · Page 35

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NASA NTRS1995

Reflectometer distance measurement between parallel conductive plates

This report presents an analytic and experimental investigation of the measurement problem in which a reflectometer is used to determine the distance to a target that is a highly conductive surface parallel to the reflectometer antenna ground plane. These parallel surfaces constitute a waveguide (WG) which can contribute parasitic perturbations that seriously degrade the accuracy of the measurements. Two distinct parallel-plate-waveguide (PPWG) phenomena are described, and their effects on both frequency and time-domain reflectometers are considered. The time-domain processing approach was found to be superior to a representative frequency-domain phase-measurement approach because of less susceptibility to perturbations produced by edge reflections and immunity to phase capture. Experimental results are presented which show that a simple radiating system modification can suppress parallel-plate (PP) propagation. The addition of a thin layer of lossy mu-metal 'magnetic absorber' to the antenna ground plane allowed a measurement accuracy of 0.025 cm (0.01 in.) when a vector network analyzer (VNA) is used as a time-domain reflectometer.

Hearn, Chase P.↗

DOE OSTI2025

MSU IETC LSTM Ethernet Decode (AN EDGE)

This research explores the ability of machine learning to perform signal separation of an Ethernet style encoded, full-duplex communication. Typical signal separation currently requires an active tap of the communication line, followed by a recombination and retransmission of the data. The purpose of this research is to study a passive approach to data acquisition from a full-duplex signal. The machine learning model used in this research is a long-short-term memory recurrent neural network (LSTM-RNN). The results show that the LSTM was largely successful in recreating the transmission signal from the measured data points, though the separated signals have not yet been tested using a decoding method.

Full Duplex Signals↗

DOE OSTI2023

Young but fading radio sources: searching for remnants among compact steep-spectrum radio sources

The incidence of young but fading radio sources provides important information on the life cycle of radio emission in radio-loud active galactic nuclei. Despite its importance for constraining the models of radio source evolution, there are no systematic studies of remnants in complete samples of young radio sources. We report results of the study of 18 compact steep-spectrum (CSS) radio sources, selected from the statistically complete B3-VLA (Very Large Array) CSS sample, characterized by a steep optically thin spectrum (α ≥ 1.0) and no core detection in earlier studies. Our deep multifrequency VLA, pc-scale Very Long Baseline Array, and enhanced Multi Element Remotely Linked Interferometer Network (e-MERLIN) observations allowed us to locate the core component in 10 objects. In three CSS sources, there is no clear evidence of present-time active regions, suggesting that they are likely in a remnant phase. Among sources with core detection, we find three objects that have no clear active regions (hotspots) at the edges of the radio structure, suggesting that the radio emission may have just restarted. Our results support a power-law distribution of the source ages, although the poor statistics prevents us from setting solid constraints on the percentage of remnants and restarted sources in subpopulations of radio sources.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Optimizing Carbon Capture, Transport, and Storage: Overcoming Challenges with Machine Learning and Cost-Benefit Analysis

Carbon Capture, Utilization, and Storage (CCUS) is a critical strategy for reducing CO₂ emissions and mitigating climate change. However, its widespread deployment faces numerous challenges across the capture, transport, and storage phases. These challenges include the technical complexity of predicting subsurface behaviors during CO₂ injection, ensuring long-term storage integrity, optimizing transportation networks, and balancing the economic and environmental trade-offs. Addressing these issues requires an integrated approach combining advanced subsurface modeling with system-level analyses to assess costs, risks, and benefits. This presentation provides an overview of studies conducted by the National Energy Technology Laboratory (NETL) to tackle these challenges. NETL’s efforts encompass cutting-edge research in subsurface fluid behavior machine learning predictions, alongside the development of innovative tools for system optimization and economic evaluation. By bridging technical expertise and strategic analysis, NETL aims to advance the deployment of CCUS technologies to support global decarbonization efforts. Presented at the Carnegie Mellon University CEE IESS Student Seminar October 4, 2024.

Shih, Chung Yan↗

NASA NTRS2012

Low-Gain Circularly Polarized Antenna with Torus-Shaped Pattern

The Juno mission to Jupiter requires an antenna with a torus-shaped antenna pattern with approximately 6 dBic gain and circular polarization over the Deep Space Network (DSN) 7-GHz transmit frequency and the 8-GHz receive frequency. Given the large distances that accumulate en-route to Jupiter and the limited power afforded by the solar-powered vehicle, this toroidal low-gain antenna requires as much gain as possible while maintaining a beam width that could facilitate a +/-10deg edge of coverage. The natural antenna that produces a toroidal antenna pattern is the dipole, but the limited approx. = 2.2 dB peak gain would be insufficient. Here a shaped variation of the standard bicone antenna is proposed that could achieve the required gains and bandwidths while maintaining a size that was not excessive. The final geometry that was settled on consisted of a corrugated, shaped bicone, which is fed by a WR112 waveguide-to-coaxial- waveguide transition. This toroidal low-gain antenna (TLGA) geometry produced the requisite gain, moderate sidelobes, and the torus-shaped antenna pattern while maintaining a very good match over the entire required frequency range. Its "horn" geometry is also low-loss and capable of handling higher powers with large margins against multipactor breakdown. The final requirement for the antenna was to link with the DSN with circular polarization. A four-layer meander-line array polarizer was implemented; an approach that was fairly well suited to the TLGA geometry. The principal development of this work was to adapt the standard linear bicone such that its aperture could be increased in order to increase the available gain of the antenna. As one increases the aperture of a standard bicone, the phase variation across the aperture begins to increase, so the larger the aperture becomes, the greater the phase variation. In order to maximize the gain from any aperture antenna, the phase should be kept as uniform as possible. Thus, as the standard bicone fs aperture increases, the gain increase becomes less until one reaches a point of diminishing returns. In order to overcome this problem, a shaped aperture is used. Rather than the standard linear bicone, a parabolic bicone was found to reduce the amount of phase variation as the aperture increases. In fact, the phase variation is half of the standard linear bicone, which leads to higher gain with smaller aperture sizes. The antenna pattern radiated from this parabolic-shaped bicone antenna has fairly high side lobes. The Juno project requested that these sidelobes be minimized. This was accomplished by adding corrugations to the parabolic shape. This corrugated-shaped bicone antenna had reasonably low sidelobes, and the appropriate gain and beamwidth to meet project requirements.

Amaro, Luis R.↗

DOE OSTI2019

Phase Segmentation in Atom-Probe Tomography Using Deep Learning-Based Edge Detection

Abstract Atom-probe tomography (APT) facilitates nano- and atomic-scale characterization and analysis of microstructural features. Specifically, APT is well suited to study the interfacial properties of granular or heterophase systems. Traditionally, the identification of the interface between, for precipitate and matrix phases, in APT data has been obtained either by extracting iso-concentration surfaces based on a user-supplied concentration value or by manually perturbing the concentration value until the iso-concentration surface qualitatively matches the interface. These approaches are subjective, not scalable, and may lead to inconsistencies due to local composition inhomogeneities. We introduce a digital image segmentation approach based on deep neural networks that transfer learned knowledge from natural images to automatically segment the data obtained from APT into different phases. This approach not only provides an efficient way to segment the data and extract interfacial properties but does so without the need for expensive interface labeling for training the segmentation model. We consider here a system with a precipitate phase in a matrix and with three different interface modalities—layered, isolated, and interconnected—that are obtained for different relative geometries of the precipitate phase. We demonstrate the accuracy of our segmentation approach through qualitative visualization of the interfaces, as well as through quantitative comparisons with proximity histograms obtained by using more traditional approaches.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Structural Evidence of Interanionic Hydrogen Bonding in Phosphoric Acid Solutions

Interanionic hydrogen bonding (IAHB) is a noncovalent interaction between like-charged ions that challenges conventional electrostatic understanding. This study provides direct structural evidence of IAHB in concentrated aqueous phosphoric acid (PA) solutions, which exhibit >60% dissociation under these conditions. Oxygen K-edge X-ray absorption fine structure spectroscopy, combined with electron affinity time-dependent density functional theory calculations, reveals the formation of stable, cyclic phosphate-phosphate IAHB dimers at PA concentrations ≥7 M. Extended X-ray absorption fine structure data show distinct long-range ordering consistent with these dimers, and near-edge X-ray absorption fine structure spectra confirm a concentration-dependent transition from monomeric to dimeric species. Energy decomposition analysis through density functional theory shows that the formation of solution-phase IAHB is energetically favored and is attributed to polarization of and the charge transfer between the two fragments driven by the surrounding solvent molecules, in addition to the permanent electrostatics. These findings offers crucial structural insights into the H-bonded networks in concentrated PA, highlighting the critical role of solvent in facilitating anion–anion association.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Quantitative relationships between film morphology, charge carrier dynamics, and photovoltaic performance in bulk-heterojunction binary vs. ternary acceptor blends

Addressing pertinent and perplexing questions regarding why nonfullerene acceptors (NFAs) promote higher power conversion efficiencies (PCEs) than traditional fullerenes and how photoactive bulk heterojunction (BHJ) film morphology, charge photogeneration, and recombination dynamics dictate solar cell performance have stimulated many studies of polymer solar cells (PSCs), yet quantitative relationships remain limited. Better understanding in these areas offers the potential to advance materials design and device engineering, afford higher PCEs, and ultimate commercialization. Here we probe quantitative relationships between BHJ film morphology, charge carrier dynamics, and photovoltaic performance in model binary and ternary blend systems having a wide bandgap donor polymer, a fullerene, and a promising NFA. We show that optimal PC 71 BM incorporation in a PBDB-TF:ITIC-Th binary system matrix retains the original π-face-on orientation, ITIC-Th crystallinity and BHJ film crystallite dimensions, and reduces film upper surface ITIC-Th segregation. Such morphology changes together simultaneously increase hole (μ h ) and electron (μ e ) mobilities, facilitate light-activated ITIC-Th to PC 71 BM domain electron delocalization, reduce free charge carrier (FC) bimolecular recombination (BR) within PBDB-TF:ITIC-Th mixed regions, and increase FC extraction pathways viaPBDB-TF:PC 71 BM pairs. The interplay of these effects yields significantly enhanced inverted cell short-circuit current density (J SC ), fill factor (FF), and PCE. Unexpectedly, we also find that excessive PC 71 BM in the PBDB-TF:ITIC-Th binary system alters the PBDB-TF orientation to π-edge-on, increases large scale PC 71 BM-rich aggregations and BHJ upper surface PC 71 BM composition. Further, these morphology changes increase parasitic decay processes such as intersystem crossing from photoexcited PC 71 BM, compromising the J SC , FF, and PCE metrics. ITIC-Th X-ray diffraction reveals a unique sidechain-dominated molecular network with previously unknown sidechain-end group stacking, rationalizing the STEM and GIWAXS results, photophysics, and the high μ e . DFT computation reveals charge transfer networks within ITIC-Th crystallites, supporting excited-state electron delocalization from ITIC-Th to PC 71 BM. This structure–property understanding leads to a newly reported NFA blend with PCE near 17%.

14 SOLAR ENERGY↗

DOE OSTI2022

Passenger Boarding Station and Curbfront Configuration Concepts for On-Demand Services with Small Automated Vehicles

This paper explores the various configurations of off-line stations and vehicle berthing that have been found to be fundamentally important parameters in the analysis of system performance, operations, and capacity. The proposed automated transit network system concept, which provides a direct ride between a passenger's origin and destination station, is applicable to both fixed guideway automated transit and to systems with self-driving vehicles. Addressed at a conceptual level is the vehicle/station interface in terms of Americans with Disability Act compliance and station capacity concerns. The concept of open-edge platforms monitored by advanced sensing technology combined with artificial intelligence-powered perception for the purpose of protecting passengers from entering the active vehicle lanes is also discussed. Finally, the paper draws initial conclusions on how these station configurations, operational complexities, and associated costs can be better understood through appropriate research and development.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

A Multifidelity and Multimodal Machine Learning Approach for Extracting Bonding Environments of Impurities and Dopants from X-ray Spectroscopies

Extended X-ray absorption fine structure (EXAFS) spectroscopy is crucial for determining the coordination environment of impurities and dopants; however, it requires difficult measurements. X-ray absorption near edge structure (XANES) spectroscopy and X-ray emission spectroscopy (XES) can be obtained easily but cannot be converted to determine structures. In this work we develop tools to map measured XANES to the EXAFS signal through machine learning, thereby facilitating the use of EXAFS structural-determination analyses on XANES data. Through the use of Deep Operator Networks (DeepONets), we are able to accurately predict the EXAFS spectrum between 6 and 14 Å -1 from the first 6 Å -1 (~100 eV) of the absorption spectrum of Cu 2+ substitutional defects in the Fe 3+ mineral hematite (a-Fe 2 O 3 ). This surprising finding implies that theoretical analyses of X-ray absorption spectra could be implemented that extract the same conclusions as high-quality EXAFS studies from spectra collected over a much smaller range of photon energies. To encourage similar efforts, the simulated x-ray spectra, machine learning, and fitting code is made publicly available.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Passenger Boarding Station and Curbfront Configuration Concepts for On-Demand Services with Small Automated Vehicles: Preprint

This paper explores the various configurations of off-line stations and vehicle berthing that have been found to be fundamentally important parameters in the analysis of system performance, operations, and capacity. The proposed Automated Transit Network system concept, which provides a direct ride between a passenger's origin and destination station, is applicable to both fixed guideway automated transit and to systems with self-driving vehicles. Addressed at a conceptual level are the vehicle/station interface in terms of Americans with Disability Act compliance and station capacity concerns. The concept of open-edge platforms monitored by advanced sensing technology combined with artificial intelligence-powered perception for the purpose of protecting passengers from entering the active vehicle lanes is also discussed. Finally, the paper draws initial conclusions on how these station configurations, operational complexities, and associated costs can be better understood through appropriate research and development.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Topological Defect Engineering and $\mathcal{PT}$ Symmetry in Non-Hermitian Electrical Circuits

In this work, we employ electric circuit networks to study topological states of matter in non-Hermitian systems enriched by parity-time symmetry $\mathcal{PT}$ and chiral symmetry anti-$\mathcal{PT (APT)}$. The topological structure manifests itself in the complex admittance bands which yields excellent measurability and signal to noise ratio. We analyze the impact of $\mathcal{PT}$-symmetric gain and loss on localized edge and defect states in a non-Hermitian Su-Schrieffer-Heeger (SSH) circuit. We realize all three symmetry phases of the system, including the $\mathcal{APT}$-symmetric regime that occurs at large gain and loss. We measure the admittance spectrum and eigenstates for arbitrary boundary conditions, which allows us to resolve not only topological edge states, but also a novel $\mathcal{PT}$-symmetric $\mathbb{Z}_2$ invariant of the bulk. We discover the distinct properties of topological edge states and defect states in the phase diagram. In the regime that is not $\mathcal{PT}$ symmetric, the topological defect state disappears and only reemerges when $\mathcal{APT}$ symmetry is reached, while the topological edge states always prevail and only experience a shift in eigenvalue. Our findings unveil a future route for topological defect engineering and tuning in non-Hermitian systems of arbitrary dimension.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Predictive Integrated Modeling of Heated Tokamak Plasmas (Final Technical Report)

The research carried out by the Lehigh University fusion group during this reporting period: (1) Self-consistent predictive core-pedestal ITER scenario modeling; (2) Microtearing instabilities and electron thermal transport in standard and spherical tokamak discharges; (3) Neural network model of the Multi-Mode anomalous transport module; (4) Anomalous transport in KSTAR, JET, EAST, Alcator C-Mod and DIII-D discharges; (5) Theory for transport in magnetized plasmas; (6) Control-oriented modeling of the q-profile dynamic response in preparation for advanced scenario control in KSTAR and in EAST; (7) Modeling of edge harmonic oscillation in DIII-D QH mode discharges; (8) Elucidating plasma dynamics in Hasegawa-Wakatani turbulence by information geometry; (9) Non-linear Langevin and Fractional Fokker–Planck equations for anomalous diffusion by Levy stable processes; and (10) Investigation of the plasma shaping effects on the H-mode pedestal structure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Residential Vehicle-to-Home Backup Power Capabilities: Key Findings from a ComEd Beneficial Electrification R&D Pilot

This report summarizes key findings from a collaborative technical study of residential, non-grid-tied vehicle-to-home (V2H) backup power systems in Commonwealth Edison’s (ComEd’s) service territory. The work integrates (1) a feeder-level technoeconomic analysis (TEA) using historical outage-event data and simulated electric-vehicle (EV) driving/charging profiles to estimate potential reliability and customer interruption-cost impacts under V2H and vehicle-to-grid (V2G) adoption scenarios; (2) controlled laboratory performance testing of a representative V2H backup ecosystem to characterize transfer-to-backup behavior, sustained power delivery, efficiency trends, and repeatable reliability limitations; and (3) a cybersecurity assessment aligned with NIST Cybersecurity Framework (CSF) 2.0 and ISO/SAE 21434 to evaluate interface-level risk drivers and identify program-relevant mitigations. Results indicate that V2H can provide measurable resilience value, but outcomes are strongly context dependent on outage patterns and the share of events that are “V2H-applicable.” Typical transfer-to-backup behavior clustered on the order of minutes, but rare long-delay edge cases were observed (including an event approaching 30 minutes) and should be treated as a reliability risk. High-power testing showed that peak-rated output is not necessarily continuously deliverable; stable operation may require operation below nameplate ratings and attention to thermal and installation constraints. The cybersecurity assessment highlights a broad attack surface spanning commissioning, home networks, embedded services, and cloud/OTA pathways, motivating minimum controls for secure onboarding, signed updates, patch cadence, and coordinated vulnerability response for any scaled deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Intrinsic synaptic plasticity of ferroelectric field effect transistors for online learning

Nanoelectronic devices emulating neuro-synaptic functionalities through their intrinsic physics at low operating energies is imperative toward the realization of brain-like neuromorphic computers. In this work, we leverage the non-linear voltage dependent partial polarization switching of a ferroelectric field effect transistor to mimic plasticity characteristics of biological synapses. Here, we provide experimental measurements of the synaptic characteristics for a 28nm high-k metal gate technology based device and develop an experimentally calibrated device model for large-scale system performance prediction. Decoupled read-write paths, ultra-low programming energies and the possibility of arranging such devices in a cross-point architecture demonstrate the synaptic efficacy of the device. Our hardware-algorithm co-design analysis reveals that the intrinsic plasticity of the ferroelectric devices has potential to enable unsupervised local learning in edge devices with limited training data

42 ENGINEERING↗

NASA NTRS1989

Implementation issues in source coding

An edge preserving image coding scheme which can be operated in both a lossy and a lossless manner was developed. The technique is an extension of the lossless encoding algorithm developed for the Mars observer spectral data. It can also be viewed as a modification of the DPCM algorithm. A packet video simulator was also developed from an existing modified packet network simulator. The coding scheme for this system is a modification of the mixture block coding (MBC) scheme described in the last report. Coding algorithms for packet video were also investigated.

Sayood, Khalid↗

DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy's National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real-time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI's Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: Run in real-time on the edge (≥ 12 Hz), Classification: Achieve less than 5% false positive detection, Classification: Achieve ≥ 95% methane plume detection rate, Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time. In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗

DOE OSTI2025

Compositionally Complex Spinel Oxides as Conversion Anodes for Lithium-Ion Batteries

Four different compositionally complex multicomponent M 3 O 4 spinels containing 5–8 distinct metals were prepared by a rapid combustion synthesis method or solvothermal synthesis. High resolution synchrotron X-ray diffraction patterns show that the materials consist primarily of spinel phases with small amounts of rock salt impurities, and, in several samples, a minor amount of contracted spinel phase. Materials were investigated as conversion anodes in lithium half-cells and delivered significantly higher capacities than two-component MgFe 2 O 4 made by combustion synthesis. X-ray absorption near-edge structure (XANES) was used to estimate the oxidation states of the metals in the pristine, lithiated (discharged) and delithiated (charged) materials to better understand the redox processes in half cells that led to the improvement. Co, Ni, and Zn are reduced to low oxidation states during lithiation (cell discharge) but are only partially oxidized. The presence of a conductive metallic network that forms after lithiation is thought to account for the improved electrochemical characteristics. Interestingly, in most of the samples, iron is not fully reduced during initial lithiation unlike what happens with a set of related high entropy spinel ferrites studied previously. Finally, the improved electrochemical properties of these materials illustrates both the advantages of complexity and the difficulties in predicting their behavior.

25 ENERGY STORAGE↗