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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 739 records · Page 41

Traveling wakefield tube: THz source powered by nonrelativistic electron beam

High peak power, tunable, narrowband terahertz emitters are becoming sought after given their portability, efficiency, and ability to be deployed in the field for industrial, medical, and military applications. The use of accelerator systems producing THz frequencies via Cherenkov radiation, generated by passing an electron beam through a slow-wave wakefield structure, is a promising method to meet future THz requirements. To date, efforts have been dedicated to analysis and design of sources utilizing laser seeded bunched electron beam drivers with relativistic energies beyond 5 MeV. Presented here is a wakefield THz generation scheme based on passing a long quasi-dc nonrelativistic beam (200 keV) through a dielectric loaded travelling wave structure. Reduced energy allows for compactness and portability of the accelerator as the size and weight of the dielectric slow wave structure is vanishingly small compared to the accelerator unit. The presented scheme can serve as a tunable high peak power THz source operated between 0.4-1.6 THz and produces power gain by a factor of five with an average efficiency of 6.8%

43 PARTICLE ACCELERATORS↗

Recent research on magnetospheric wave-particle interactions

Highlights of recent Stanford University VLF research in the Antarctic include new observations of wave-induced particle precipitation and controlled experiments on nonlinear wave growth phenomena. Higher-than-expected levels of burst precipitation have been discovered inside the plasmasphere, near L = 2, using subionospheric signal perturbations called 'Trimpi events'. Studies of burst precipitation have been extended to the region poleward of the plasmapause using the Siple transmitter signal as a waveguide probe. Experiments on the 'coherent wave instability', using the amplitude and frequency modulation capability of the new Siple transmitter, have produced exciting new results. Examples are: (1) better definition of the power threshold for the stimulation of temporal wave growth, (2) generation of strong sidebands by unamplified 'beat' waves and (3) generation of chorus-like elements within a band of simulated hiss. Using a new digital processing technique developed at Stanford, new features of the phase behavior of growing waves have been found. Opportunities for extending these experiments are discussed.

Helliwell, R. A.↗

Software to Control and Monitor Gas Streams

This software package interfaces with various gas stream devices such as pressure transducers, flow meters, flow controllers, valves, and analyzers such as a mass spectrometer. The software provides excellent user interfacing with various windows that provide time-domain graphs, valve state buttons, priority- colored messages, and warning icons. The user can configure the software to save as much or as little data as needed to a comma-delimited file. The software also includes an intuitive scripting language for automated processing. The configuration allows for the assignment of measured values or calibration so that raw signals can be viewed as usable pressures, flows, or concentrations in real time. The software is based on those used in two safety systems for shuttle processing and one volcanic gas analysis system. Mass analyzers typically have very unique applications and vary from job to job. As such, software available on the market is usually inadequate or targeted on a specific application (such as EPA methods). The goal was to develop powerful software that could be used with prototype systems. The key problem was to generalize the software to be easily and quickly reconfigurable. At Kennedy Space Center (KSC), the prior art consists of two primary methods. The first method was to utilize Lab- VIEW and a commercial data acquisition system. This method required rewriting code for each different application and only provided raw data. To obtain data in engineering units, manual calculations were required. The second method was to utilize one of the embedded computer systems developed for another system. This second method had the benefit of providing data in engineering units, but was limited in the number of control parameters.

Arkin, C.↗

Analysis of At-Altitude LTE Power Spectra for C2 Communications for UAS Traffic Management

The National Aeronautics and Space Administration’s (NASA) Unmanned Aircraft Systems Traffic Management (UTM) project works to develop tools and technologies essential for safely enabling civilian low-altitude small Unmanned Aerial Systems (sUAS, also known as drones) operations. This paper presents results of work completed in the paper [1] presented at the 2018 ICNS conference where proposed approaches were explored for evaluating and analyzing sUAS Command and Control (C2) links based on commercial cellular networks. This paper focuses on the UTM Project’s Technology Capability Level 3 (TCL-3) test results which address the communications portion identified within the same paper. A software defined radio (SDR) was flown as a sUAS payload to capture received signal spectrum in Long Term Evolution (LTE) frequency bands of interest. The purpose was to measure the RF environment at UTM altitudes to characterize the interference potential. The SDR payload was flown at various stationary altitudes where the LTE over-the-air complex (I/Q) samples were captured by the SDR and later post-processed. The SDR received inputs through an omnidirectional antenna. The complex samples captured were an aggregate of transmissions received from all line-of-sight (LOS) towers within the geographic area for the specific radio frequency bandwidth the SDR is programmed to capture. Using this approach, the complex samples captured do not distinguish between the various eNodeB's (Long Term Evolution (LTE) transmitting towers). The complex samples were post processed via a Discrete Fourier Transform (DFT) algorithm to view the captured spectrum along with the power levels across the captured LTE bandwidth. This SDR payload process of capturing complex samples was done at two different regions within the US: 1) NASA's Ames Research Center (ARC) in Moffett Field, CA, and 2) Griffiss Airfield in Rome, NY. The data capture at the ARC site was done at two physical locations within the Ames campus where many stationary altitude captures where done as high as 800 ft. above ground level (AGL). The data captured at the Griffiss Airport (also known as the NY Corridor Site) were acquired at one location with three specific stationary altitude levels – {Ground Level (GL), 300 ft., and 400 ft.}. The LTE spectrum power levels were captured for two LTE carriers, AT&T and Verizon, at both sites where their respective spectra and power levels were measured and compared at various altitudes. The overall results show that there is an increase in LTE spectrum power levels at higher altitudes for drones. A detailed analysis of this data and conclusions drawn from the results are presented in this paper.

Kerczewski, Robert J.↗

An assessment of controlled source EM for monitoring subsurface CO 2 injection at the wyoming carbonSAFE geologic carbon storage site

Here we evaluate if electromagnetic (EM) geophysical methods for monitoring geologic carbon storage (GCS) efforts at the Wyoming CarbonSAFE project adjacent to the Dry Fork Station power plant near Gillette, Wyoming. This first involved acquiring both electric and magnetic fields at eleven different locations ranging in distance from immediately adjacent to 4 km from the plant. Passive EM measurements were made to provide spectral EM noise measurements generated by electricity production at the plant and to determine if useful magnetotelluric (MT) data can be successfully collected in the region. The processed data indicate that useful MT data can be collected as long as the site is located more than 2km away from the power plant as well as active roads and rail lines. Controlled source EM data were collected using three different source configurations, two of which connected to steel casings used to complete the injection wells. Comparing the EM noise measurements to the CSEM data show measurable electric and magnetic field signals at all sites. Next a series of three-dimensional (3D) numerical models were built that simulate resistivity changes caused by the proposed CO2 injection at depths ranging from 2.4 to 3.0km. These models were used to simulate various EM measurement configurations. The modeling shows that casing-source CSEM monitoring can provide sensitivity to the injected CO 2 if source electrodes are connected to the bottom of one or both of the injection wells.

58 GEOSCIENCES↗

Spatial Mapping of Valence Excited-State Landscapes Using Time-Resolved Shake-Down Spectroscopy

Time-resolved X-ray photoelectron spectroscopy (XPS) is used to track the photodissociation dynamics of 2-iodothiophene following 262 nm excitation. The transient XPS features include both direct ionization of the initially populated excited states and pronounced satellite peaks arising from shake-down processes. While the direct ionization signals exhibit only minimal energy shifts during C−I bond cleavage, the shake-down transitions undergo a substantial, 5 eV, shift over the reaction coordinate. By correlating these shifts with simulated C−I bond lengths, a direct structural mapping is established that reveals the exceptional sensitivity of shake-down channels to molecular geometry. These results demonstrate that shake-down transitions provide a new and powerful probe of ultrafast structural dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Sparse Tensor Benchmark Suite for CPUs and GPUs

Tensor computations present significant performance chal- lenges that impact a wide spectrum of applications ranging from machine learning, healthcare analytics, social network analysis, data mining to quantum chemistry and signal processing. Efforts to improve the perfor- mance of tensor computations include exploring data layout, execution scheduling, and parallelism in common tensor kernels. This work presents a benchmark suite for arbitrary-order sparse tensor kernels using state- of-the-art tensor formats: coordinate (COO) and hierarchical coordinate (HiCOO) on CPUs and GPUs. It presents a set of reference tensor kernel implementations that are compatible with real-world tensors and power law tensors extended from synthetic graph generation techniques. We also propose Roofline performance models for these kernels to provide insights of computer platforms from sparse tensor view. This benchmark suite along with the synthetic tensor generator is publicly available.

Li, Jiajia↗

Traveling Wave Tube (TVT) RF Power Combining Demonstration for use in the Jupiter Icy Moons Orbiter (JIMO)

The Jupiter Icy Moons Orbiter (JIMO) is set to launch between the years 2012 and 2015. It will possibly utilize a nuclear reactor power source and ion engines as it travels to the moons of Jupiter. The nuclear reactor will produce hundreds of kilowatts of power for propulsion, communication and various scientific instruments. Hence, the RF amplification devices aboard will be able to operate at a higher power level and data rate. The initial plan for the communications system is for an output of 1000 watts of RF power, a data rate of at least 10 megabits a second, and a frequency of 32 GHz. A higher data rate would be ideal to fully utilize the instruments aboard JIMO. At NASA Glenn, one of our roles in the JIMO project is to demonstrate RF power combining using multiple traveling wave tubes (TWT). In order for the power of separate TWT s to be combined, the RF output waves from each must be in-phase and have the same amplitude. Since different tubes act differently, we had to characterize each tube using a Network Analyzer. We took frequency sweeps and power sweeps to characterize each tube to ensure that they will behave similarly under the same conditions. The 200 watt Dornier tubes had been optimized to run at a lower power level (120 watts) for their extensive use in the ACTS program, so we also had to experiment with adjusting the voltage settings on several internal components (helix, anode, collector) of the tubes to reach the full 200 watt potential. from the ACTS program. Phase shifters and power attenuators were placed in the waveguide circuit at the inputs to the tubes so that adjustments could be made individually to match them exactly. A magic tee was used to route and combine the amplified electromagnetic RF waves on the tube output side. The demonstration of 200 watts of combined power was successful with efficiencies greater than 90% over a 500 MHz bandwidth. The next step will be to demonstrate the use of three amplifiers using two magic tees by adding a 200 watt Dornier tube to the Varian and Logimetrics combined setup for a total of 400 watts. After that we will use two 200 watt Dorniers for 400 watts and eventually four 200 watt Dornier tubes to demonstrate 800 watts. After demonstrating the success of power combining, we will need to verify the integrity of a modulated signal sent through the combined tubes. The purpose will be to see what effects separating and recombining will have on the modulated signal and also what effect it will have on combining efficiency. A Bit Error Rate (BER) will be determined by a Bit Error Rate Tester (BERT) by comparing the random information it transmits to what it receives back. The process began with two 100 watt tubes, a Varian and a Logimetrics, salvaged

Downey, Joseph A.↗

MoRE-Brain: Routed Mixture of Experts for Interpretable and Generalizable Cross-Subject fMRI Visual Decoding

Decoding visual experiences from fMRI offers a powerful avenue to understand human perception and develop advanced brain-computer interfaces. However, current progress often prioritizes maximizing reconstruction fidelity while overlooking interpretability, an essential aspect for deriving neuroscientific insight. To address this gap, we propose MoRE-Brain, a neuro-inspired framework designed for high-fidelity, adaptable, and interpretable visual reconstruction. MoRE-Brain uniquely employs a hierarchical Mixture-of-Experts architecture where distinct experts process fMRI signals from functionally related voxel groups, mimicking specialized brain networks. The experts are first trained to encode fMRI into the frozen CLIP space. A finetuned diffusion model then synthesizes images, guided by expert outputs through a novel dual-stage routing mechanism that dynamically weighs expert contributions across the diffusion process. MoRE-Brain offers three main advancements: First, it introduces a novel Mixture-of-Experts architecture grounded in brain network principles for neuro-decoding. Second, it achieves efficient cross-subject generalization by sharing core expert networks while adapting only subject-specific routers. Third, it provides enhanced mechanistic insight, as the explicit routing reveals precisely how different modeled brain regions shape the semantic and spatial attributes of the reconstructed image. Extensive experiments validate MoRE-Brain’s high reconstruction fidelity, with bottleneck analyses further demonstrating its effective utilization of fMRI signals, distinguishing genuine neural decoding from over-reliance on generative priors. Consequently, MoRE-Brain marks a substantial advance towards more generalizable and interpretable fMRI-based visual decoding.

Wei, Yuxiang [Georgia Institute of Technology]↗

Machine Learning Predicts the Timing and Shear Stress Evolution of Lab Earthquakes Using Active Seismic Monitoring of Fault Zone Processes

Abstract Machine learning (ML) techniques have become increasingly important in seismology and earthquake science. Lab‐based studies have used acoustic emission data to predict time‐to‐failure and stress state, and in a few cases, the same approach has been used for field data. However, the underlying physical mechanisms that allow lab earthquake prediction and seismic forecasting remain poorly resolved. Here, we address this knowledge gap by coupling active‐source seismic data, which probe asperity‐scale processes, with ML methods. We show that elastic waves passing through the lab fault zone contain information that can predict the full spectrum of labquakes from slow slip instabilities to highly aperiodic events. The ML methods utilize systematic changes in P‐wave amplitude and velocity to accurately predict the timing and shear stress during labquakes. The ML predictions improve in accuracy closer to fault failure, demonstrating that the predictive power of the ultrasonic signals improves as the fault approaches failure. Our results demonstrate that the relationship between the ultrasonic parameters and fault slip rate, and in turn, the systematically evolving real area of contact and asperity stiffness allow the gradient boosting algorithm to “learn” about the state of the fault and its proximity to failure. Broadly, our results demonstrate the utility of physics‐informed ML in forecasting the imminence of fault slip at the laboratory scale, which may have important implications for earthquake mechanics in nature.

58 GEOSCIENCES↗

Optical coherence and energy-level properties of a Tm 3+ -doped LiNbO 3 waveguide at subKelvin temperatures

We characterize the optical coherence and energy-level properties of the 795-nm 3 H 6 to 3 H 4 transition of Tm 3+ in a Ti 4+ :LiNbO 3 waveguide at temperatures as low as 0.65 K. Coherence properties are measured with varied temperature, magnetic field, optical excitation power and wavelength, and measurement timescale. We also investigate nuclear spin-induced hyperfine structure and population dynamics with varying magnetic field and laser excitation power. Except for accountable differences due to different Ti 4+ - and Tm 3+ -doping concentrations, we find that the properties of Tm 3+ :Ti 4+ :LiNbO 3 produced by indiffusion doping are consistent with those of a bulk-doped Tm 3+ :LiNbO 3 crystal measured under similar conditions. Furthermore, our results, which complement previous work in a narrower parameter space, support using rare-earth ions for integrated optical and quantum signal processing.

74 ATOMIC AND MOLECULAR PHYSICS↗

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the noise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.

Johnson, Hans↗

Image-Based Methods to Score Fungal Pathogen Symptom Progression and Severity in Excised Arabidopsis Leaves

Image-based symptom scoring of plant diseases is a powerful tool for associating disease resistance with plant genotypes. Advancements in technology have enabled new imaging and image processing strategies for statistical analysis of time-course experiments. There are several tools available for analyzing symptoms on leaves and fruits of crop plants, but only a few are available for the model plant Arabidopsis thaliana (Arabidopsis). Arabidopsis and the model fungus Botrytis cinerea (Botrytis) comprise a potent model pathosystem for the identification of signaling pathways conferring immunity against this broad host-range necrotrophic fungus. Here, we present two strategies to assess severity and symptom progression of Botrytis infection over time in Arabidopsis leaves. Thus, a pixel classification strategy using color hue values from red-green-blue (RGB) images and a random forest algorithm was used to establish necrotic, chlorotic, and healthy leaf areas. Secondly, using chlorophyll fluorescence (ChlFl) imaging, the maximum quantum yield of photosystem II (Fv/Fm) was determined to define diseased areas and their proportion per total leaf area. Both RGB and ChlFl imaging strategies were employed to track disease progression over time. This has provided a robust and sensitive method for detecting sensitive or resistant genetic backgrounds. A full methodological workflow, from plant culture to data analysis, is described.

59 BASIC BIOLOGICAL SCIENCES↗

Millimeter Light Curves of Sagittarius A* Observed during the 2017 Event Horizon Telescope Campaign

The Event Horizon Telescope (EHT) observed the compact radio source, Sagittarius A* (Sgr A*), in the Galactic Center on 2017 April 5–11 in the 1.3 mm wavelength band. At the same time, interferometric array data from the Atacama Large Millimeter/submillimeter Array and the Submillimeter Array were collected, providing Sgr A* light curves simultaneous with the EHT observations. These data sets, complementing the EHT very long baseline interferometry, are characterized by a cadence and signal-to-noise ratio previously unattainable for Sgr A* at millimeter wavelengths, and they allow for the investigation of source variability on timescales as short as a minute. While most of the light curves correspond to a low variability state of Sgr A*, the April 11 observations follow an X-ray flare and exhibit strongly enhanced variability. All of the light curves are consistent with a red-noise process, with a power spectral density (PSD) slope measured to be between −2 and −3 on timescales between 1 minute and several hours. Our results indicate a steepening of the PSD slope for timescales shorter than 0.3 hr. The spectral energy distribution is flat at 220 GHz, and there are no time lags between the 213 and 229 GHz frequency bands, suggesting low optical depth for the event horizon scale source. We characterize Sgr A*’s variability, highlighting the different behavior observed just after the X-ray flare, and use Gaussian process modeling to extract a decorrelation timescale and a PSD slope. We also investigate the systematic calibration uncertainties by analyzing data from independent data reduction pipelines.

79 ASTRONOMY AND ASTROPHYSICS↗

Cosmic Infrared Background Fluctuations in Deep Spitzer Infrared Array Camera Images: Data Processing and Analysis

This paper provides a detailed description of the data reduction and analysis procedures that have been employed in our previous studies of spatial fluctuation of the cosmic infrared background (CIB) using deep Spitzer Infrared Array Camera observations. The self-calibration we apply removes a strong instrumental signal from the fluctuations that would otherwise corrupt the results. The procedures and results for masking bright sources and modeling faint sources down to levels set by the instrumental noise are presented. Various tests are performed to demonstrate that the resulting power spectra of these fields are not dominated by instrumental or procedural effects. These tests indicate that the large-scale ([greater, similar]30') fluctuations that remain in the deepest fields are not directly related to the galaxies that are bright enough to be individually detected. We provide the parameterization of these power spectra in terms of separate instrument noise, shot noise, and power-law components. We discuss the relationship between fluctuations measured at different wavelengths and depths, and the relations between constraints on the mean intensity of the CIB and its fluctuation spectrum. Consistent with growing evidence that the [approx]1-5 [mu]m mean intensity of the CIB may not be as far above the integrated emission of resolved galaxies as has been reported in some analyses of DIRBE and IRTS observations, our measurements of spatial fluctuations of the CIB intensity indicate the mean emission from the objects producing the fluctuations is quite low ([greater, similar]1 nW m-2 sr-1 at 3-5 [mu]m), and thus consistent with current [gamma]-ray absorption constraints. The source of the fluctuations may be high-z Population III objects, or a more local component of very low luminosity objects with clustering properties that differ from the resolved galaxies. Finally, we discuss the prospects of the upcoming space-based surveys to directly measure the epochs inhabited by the populations producing these source-subtracted CIB fluctuations, and to isolate the individual fluxes of these populations.

Arendt, Richard↗

Antenna Near-Field Probe Station Scanner

A miniaturized antenna system is characterized non-destructively through the use of a scanner that measures its near-field radiated power performance. When taking measurements, the scanner can be moved linearly along the x, y and z axis, as well as rotationally relative to the antenna. The data obtained from the characterization are processed to determine the far-field properties of the system and to optimize the system. Each antenna is excited using a probe station system while a scanning probe scans the space above the antenna to measure the near field signals. Upon completion of the scan, the near-field patterns are transformed into far-field patterns. Along with taking data, this system also allows for extensive graphing and analysis of both the near-field and far-field data. The details of the probe station as well as the procedures for setting up a test, conducting a test, and analyzing the resulting data are also described.

Zaman, Afroz J.↗

Structure, dynamics, and redox reactivity of an all-purpose flavodoxin

The flavodoxin of Rhodopseudomonas palustris CGA009 (Rp9Fld) supplies highly reducing equivalents to crucial en- zymes such as hydrogenase, especially when the organism is iron-restricted. By acquiring those electrons from photodriven electron flow via the bifurcating electron transfer flavoprotein, Rp9Fld provides solar power to vital metabolic processes. To understand Rp9Fld’s ability to work with diverse partners, we solved its crystal structure. We observed the canonical fla- vodoxin (Fld) fold and features common to other long-chain Flds but not all the surface loops thought to recognize part- ner proteins. Moreover, some of the loops display alternative structures and dynamics. To advance studies of protein– protein associations and conformational consequences, we assigned the 19F NMR signals of all five tyrosines (Tyrs). Our electrochemical measurements show that incorporation of 3- 19 F-Tyr in place of Tyr has only a modest effect on Rp9Fld’s redox properties even though Tyrs flank the flavin on both sides. Meanwhile, the 19 F probes demonstrate the expected paramagnetic effect, with signals from nearby Tyrs becoming broadened beyond detection when the flavin semiquinone is formed. However, the temperature dependencies of chemical shifts and linewidths reveal dynamics affecting loops close to the flavin and regions that bind to partners in a variety of systems. These coincide with patterns of amino acid type conservation but not retention of specific residues, arguing against detailed specificity with respect to partners. We pro- pose that the loops surrounding the flavin adopt altered con- formations upon binding to partners and may even participate actively in electron transfer.

19F NMR↗

Ultrafast disruptive probing: Simultaneously keeping track of tens of reaction pathways

Ultrafast science depends on different implementations of the well-known pump–probe method. Here, we provide a formal description of ultrafast disruptive probing, a method in which the probe pulse disrupts a transient species that may be a metastable ion or a transient state of matter. Disruptive probing has the advantage of allowing for simultaneous tracking of the yield of tens of different processes. Our presentation includes a numerical model and experimental data on multiple products resulting from the strong-field ionization of two different molecules, partially deuterated methanol and norbornene. The correlated enhancement and depletion signals between all the different fragmentation channels offer comprehensive information on photochemical reaction pathways. In combination with ion imaging and/or coincidence momentum imaging or as complementary to atom-specific probing or ultrafast diffraction methods, disruptive probing is a particularly powerful tool for the study of strong-field laser–matter interactions.

47 OTHER INSTRUMENTATION↗