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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
DOE OSTI2023

Ultra low background Micromegas detectors for BabyIAXO solar axion search

Abstract The International AXion Observatory (IAXO) is a large scale axion helioscope that will look for axions and axion-like particles produced in the Sun with unprecedented sensitivity. BabyIAXO is an intermediate experimental stage that will be hosted at DESY (Germany) and that will test all IAXO subsystems serving as a prototype for IAXO but at the same time as a fully-fledged helioscope with potential for discovery.One of the crucial components of the project is the ultra-low background X-ray detectors that will image the X-ray photons produced by axion conversion in the experiment. The baseline detection technology for this purpose are Micromegas (Microbulk) detectors. We will show the quest and the strategy to attain the very challenging levels of background targeted for BabyIAXO that need a multi-approach strategy coming from ground measurements, screening campaigns of components of the detector, underground measurements, background models, in-situ background measurements as well as powerful rejection algorithms. First results from the commissioning of the BabyIAXO prototype will be shown.

Instruments & Instrumentation↗
DOE OSTI2023

Prescribed fire selects for a pyrophilous soil sub‐community in a northern California mixed conifer forest

Abstract Prescribed fire is a critical strategy for mitigating the effects of catastrophic wildfires. While the above‐ground response to fire has been well‐documented, fewer studies have addressed the effect of prescribed fire on soil microorganisms. To understand how soil microbial communities respond to prescribed fire, we sampled four plots at a high temporal resolution (two burned, two controls), for 17 months, in a mixed conifer forest in northern California, USA. Using amplicon sequencing, we found that prescribed fire significantly altered both fungal and bacterial community structure. We found that most differentially abundant fungal taxa had a positive fold‐change, while differentially abundant bacterial taxa generally had a negative fold‐change. We tested the null hypothesis that these communities assembled due to neutral processes (i.e., drift and/or dispersal), finding that >90% of taxa fit this neutral prediction. However, a dynamic sub‐community composed of burn‐associated indicator taxa that were positively differentially abundant was enriched for non‐neutral amplicon sequence variants, suggesting assembly via deterministic processes. In synthesizing these results, we identified 15 pyrophilous taxa with a significant and positive response to prescribed burns. Together, these results lay the foundation for building a process‐driven understanding of microbial community assembly in the context of the classical disturbance regime of fire.

Microbiology↗
DOE OSTI2024

Design and validation of a cold load for characterization of CMB-S4 detectors

We present the design and validation of a variable temperature cryogenic blackbody source, hereinafter called a cold load, that will be used to characterize detectors to be deployed by CMB-S4, the next-generation ground-based cosmic microwave background (CMB) experiment. Although cold loads have been used for detector characterization by previous CMB experiments, this cold load has three novel design features: (1) the ability to operate from the 1 K stage of a dilution refrigerator (DR), (2) a 3He gas-gap heat switch to reduce cooling time, and (3) the ability to couple small external optical signals to measure detector optical time constants under low optical loading. The efficacy of this design was validated using a 150 GHz detector array previously deployed by the Spider experiment. Here, thermal tests showed that the cold load can be heated to temperatures required for characterizing CMB-S4’s detectors without significantly impacting the temperatures of other cryogenic stages when mounted to the DR’s 1 K stage. Additionally, optical tests demonstrated that external signals can be coupled to a detector array through the cold load without imparting a significant optical load on the detectors, which will enable measurements of the CMB-S4 detectors’ optical time constants.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Lettuce ( Lactuca sativa ) productivity influenced by microbial inocula under nitrogen-limited conditions in aquaponics

The demand for food will outpace productivity of conventional agriculture due to projected growth of the human population, concomitant with shrinkage of arable land, increasing scarcity of freshwater, and a rapidly changing climate. While aquaponics has potential to sustainably supplement food production with minimal environmental impact, there is a need to better characterize the complex interplay between the various components (fish, plant, microbiome) of these systems to optimize scale up and productivity. Here, we investigated how the commonly-implemented practice of continued microbial community transfer from pre-existing systems might promote or impede productivity of aquaponics. Specifically, we monitored plant growth phenotypes, water chemistry, and microbiome composition of rhizospheres, biofilters, and fish feces over 61-days of lettuce (Lactuca sativa var. crispa) growth in nitrogen-limited aquaponic systems inoculated with bacteria that were either commercially sourced or originating from a pre-existing aquaponic system. Lettuce above- and below-ground growth were significantly reduced across replicates treated with a pre-existing aquaponic system inoculum when compared to replicates treated with a commercial inoculum. Reduced productivity was associated with enrichment in specific bacterial genera in plant roots, including Pseudomonas, following inoculum transfer from pre-existing systems. Increased productivity was associated with enrichment of nitrogen-fixing Rahnella in roots of plants treated with the commercial inoculum. Thus, we show that inoculation from a pre-existing system, rather than from a commercial inoculum, is associated with lower yields. Further work will be necessary to test the putative mechanisms involved.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

300_underground robot (final research report)

Recent advancements in mobile robotics have displayed impressive capabilities in traversing and accessing areas that are inaccessible to humans either due to the characteristics of the environment or potential hazards. Furthermore, these advancements within the field of mobile robotics, more specifically uncrewed ground vehicles (UGVs), give the ability to potentially survey, observe, and map these inaccessible areas for humans. However, one of the most challenging areas to implement this technology is underground environments. The main challenge with implementing this technology in underground environments is the dependence on either GPS or RF communication for UGVs to navigate properly. Therefore, in order to properly demonstrate the mapping capabilities of the UGV this challenge must be resolved. The overall goal of this study is to demonstrate the mapping capabilities of a UGV while addressing this challenge and documenting the implementation and testing phase of the robot. The proposed solution to this challenge is to implement a SLAM algorithm onto the main computational device of the UGV utilizing the Robot Operating System (ROS). The algorithm is the open-source software package Slam Toolbox developed by Steve Macenski. Furthermore, the sllidar_ros2 package from Slamtec will be used to gather the lidar data from an A3M1 2D lidar. A separate program will be created to gather odometry information for our UGV robot. All of these software packages will run together in a Docker environment. Through working on this project I have developed a better understanding of the world of robotics/autonomous systems, especially with applications such as navigation and mapping. Furthermore, through this project, I have been given exposure to how research is conducted within a DOE lab setting. As robotics/autonomous systems become more advanced it's important to pursue more avenues of research such as this project as it will ensure the development of our capabilities.

42 ENGINEERING↗
DOE OSTI2026

SPT-3G D1: CMB temperature and polarization power spectra and cosmology from 2019 and 2020 observations of the SPT-3G main field

Here, we present measurements of the temperature and E-mode polarization angular power spectra of the cosmic microwave background (CMB) from observations of 4% of the sky with SPT-3G, the current camera on the South Pole Telescope (SPT). The maps used in this analysis are the deepest used in a CMB TT / TE / EE analysis to date. The maps and resulting power spectra have been validated through blind and unblind tests. The measurements of the lensed EE and TE spectra are the most precise to date at ℓ = 1800 – 4000 and ℓ = 2200 – 4000 , respectively. Combining our TT / TE / EE spectra with previously published SPT-3G CMB lensing results, we find parameters for the standard Λ cold dark matter ( Λ CDM ) model consistent with Planck and ACT DR6 with comparable constraining power. We report a Hubble constant of H 0 = 66.66 ± 0.60 km s - 1 Mpc - 1 from SPT-3G alone, 6.2 σ away from local measurements from SH0ES. For the first time, combined ground-based ( SPT + ACT ) CMB primary and lensing data have reached Planck’s constraining power on some parameters, a milestone for CMB cosmology. The combination of these three CMB experiments yields the tightest CMB constraints to date, with H 0 = 67.19 ± 0.38 km s - 1 Mpc - 1 , and the amplitude of clustering σ 8 = 0.8137 ± 0.0037 . CMB data alone show no evidence for physics beyond Λ CDM , however, we observe a 2.8 σ difference in Λ CDM between CMB and baryon acoustic oscillation (BAO) results from DESI-DR2, which is relaxed in extended models. The combination of CMB and BAO yields 2 − 3 σ shifts from Λ CDM in the curvature of the Universe, the amplitude of CMB lensing, or the dark energy equation of state. It also drives mild preferences for models that address the Hubble tension through modified recombination or variations in the electron mass in a nonflat Universe. This work highlights the growing power of ground-based CMB experiments and lays a foundation for further cosmological analyses with SPT-3G.

Camphuis, Etienne [Sorbonne Université; CNRS; Inst↗
DOE OSTI2025

Dynamic, symmetry-preserving, and hardware-adaptable circuits for quantum computing many-body states and correlators of the Anderson impurity model

We present a hardware-reconfigurable ansatz on N q -qubits for the variational preparation of many-body states of the Anderson impurity model (AIM) with N imp + N bath = N q /2 sites, which conserves total charge and spin z component within each variational search subspace. The many-body ground state of the AIM is determined as the minimum over all minima of O(N$^2_ q$) distinct charge-spin sectors. Hamiltonian expectation values are shown to require ω(N q ) < N meas. $\leqslant$ O(N imp N bath ) symmetry-preserving, parallelizable measurement circuits, each amenable to postselection. To obtain the one-particle impurity Green’s function we show how initial Krylov vectors can be computed via midcircuit measurement and how Lanczos iterations can be computed using the symmetry-preserving ansatz. For a single-impurity Anderson model with a number of bath sites increasing from one to seven, we show using numerical emulation that the ease of variational ground-state preparation is suggestive of linear scaling in circuit depth and subquartic scaling in optimizer complexity. We therefore expect that, combined with time-dependent methods for Green’s function computation, our ansatz provides a useful tool to account for electronic correlations on early fault-tolerant processors. Finally, with a view towards computing real materials properties of interest like magnetic susceptibilities and electron-hole propagators, we provide a straightforward method to compute many-body, time-dependent correlation functions using a combination of time evolution, midcircuit measurement-conditioned operations, and the Hadamard test.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Noisy Intermediate-Scale Quantum Applications on a Pathfinder System

Work performed under this one-year LDRD was concerned with estimating resource requirements for small quantum test beds that are expected to be available in the near future. This work represents a preliminary demonstration of our ability to leverage quantum hardware for solving small quantum simulation problems in areas of interest to the DOE. The algorithms enabling such studies are hybrid quantum-classical variational algorithms, in particular the widely-used variational quantum eigensolver (VQE). Employing this hybrid algorithm, in which the quantum computer complements the classical one, we implemented an end-to-end application-level toolchain that allows the user to specify a molecule of interest and compute the ground state energy using the VQE approach. We found significant limitations attributable to the classical portion of the hybrid system, including a greater than greater-than-quartic power scaling of the classical memory requirements with the system size. Current VQE approaches would require an exascale machine for solving any molecule with size greater than 150 nuclei. Our findings include several improvements that we implemented into the VQE toolchain, including a new classical optimizer that is decades old but hadn't been considered before in the VQE ecosystem. Our findings suggest limitations to variational hybrid approaches to simulation that further motivate the need for a gate-based fault-tolerant quantum processor that can implement larger problems using the fully digital quantum phase estimation algorithm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Electropotential Verification for Nuclear Safeguards

The international safeguards regime desires methods to efficiently verify that facilities are only performing declared activities. Electropotential verification (EPV) is a newly proposed technique that was tested for its feasibility to perform facility design information verification (DIV) and verification of spent nuclear fuel while in a cooling pool. EPV works by passing a constant, low voltage current through a conductive system (facility infrastructure of nuclear fuel assembly) and measuring the resulting voltage at various places throughout the infrastructure in order to establish a baseline. Changes made to the system affect these voltage readings, which will deviate from the baseline and indicate that a change to the system was made. For facility DIV, it appears feasible that changes in configuration of the system’s grounding can be detected in real-time, and the location of the change can be inferred from the measured intensity of the change in voltage. Determination of whether or not spent fuel was present in a fuel rod, as well as the presence/absence of a fuel rod from an assembly using EPV, proved unsuccessful with the sensitivity of instrumentation used in this study.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Deep Learning Classification of Cheatgrass Invasion in the Western United States Using Biophysical and Remote Sensing Data

Cheatgrass (Bromus tectorum) invasion is driving an emerging cycle of increased fire frequency and irreversible loss of wildlife habitat in the western US. Yet, detailed spatial information about its occurrence is still lacking for much of its presumably invaded range. Deep learning (DL) has demonstrated success for remote sensing applications but is less tested on more challenging tasks like identifying biological invasions using sub-pixel phenomena. We compare two DL architectures and the more conventional Random Forest and Logistic Regression methods to improve upon a previous effort to map cheatgrass occurrence at >2% canopy cover. High-dimensional sets of biophysical, MODIS, and Landsat-7 ETM+ predictor variables are also compared to evaluate different multi-modal data strategies. All model configurations improved results relative to the case study and accuracy generally improved by combining data from both sensors with biophysical data. Cheatgrass occurrence is mapped at 30 m ground sample distance (GSD) with an estimated 78.1% accuracy, compared to 250-m GSD and 71% map accuracy in the case study. Furthermore, DL is shown to be competitive with well-established machine learning methods in a limited data regime, suggesting it can be an effective tool for mapping biological invasions and more broadly for multi-modal remote sensing applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Spatiotemporal Modeling of Real World Backsheets Field Survey Data: Hierarchical (Multilevel) Generalized Additive Models: Preprint

Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Lab based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Field surveyed data is critical to assess the performance of component lifetime. Using a documented field survey protocol, 13 field surveys where conducted. Each measurement is encoded with it's spatial location in respect to the other modules. By combining field survey data on degradation predictors with real time satellite weather data, data-driven predictive models of backsheet degradation were trained. LOESS models were constructed to investigate the spatial dependence of measurements. It was found that micro-climatic effects like treelines, ground surface changes, and elevation changes effected the magnitude and variance of the measurements. A GAM model was created to predict the value of degradation based on measured predictors. The model includes variables on the climate of the system and the location of each measurement in the PV mounting structure. The model performed well with an adj:R2 of 0:95 for yellowness index prediction. The model was cross-validated using k-folds.

backsheet↗
DOE OSTI2023

Nuclear three-body short-range correlations in coordinate space

Here, we study the effects of three-nucleon short-range correlations on nuclear coordinate-space densities. For this purpose, novel three-body densities are calculated for ground-state nuclei using the auxiliary-field diffusion Monte Carlo method. The results are analyzed in terms of the generalized contact formalism, extended to include three-body correlations, revealing the universal behavior of nucleon triplets at short distances. We identify the quantum numbers of such correlated triplets and extract scaling factors of triplet abundances that can be compared to upcoming inclusive electron-scattering data. We also show that the dynamics of these triplets is sensitive to three-body forces, and, therefore, the short-range part of three-body force models could be tested against appropriate exclusive electron-scattering data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Quantifying Optical Loss of High-Voltage Degradation Modes in PV Modules Using Spectral Analysis [Slides]

The direct current bias for photovoltaic (PV) modules interconnected in series-strings may include both high voltage negative ("HV-") and positive ("HV+") polarity with respect to the electrical ground. Multiple degradation modes, resulting in quantifiable optical loss, were found to occur during HV-/HV+ sequential stress, including: corrosion of the external glass surface, encapsulant delamination (at its interfaces with the glass and the PV cell), internal haze formation (resulting from a chemical interaction between the glass and the encapsulant), corrosion and migration of the gridlines, and corrosion of the silicon nitride (SixNy) antireflective coating on the cell. The effects of these separate modes were examined using monolithic (e.g., glass or PV cell) and laminated-coupon (glass/encapsulant/glass or glass/encapsulant/cell/encapsulant/backsheet) specimens. Characterizations during and after unbiased accelerated testing at 85 degrees C/85% relative humidity included: spectrophotometry, optical microscopy, electron microscopy, and ellipsometry. For some module components (i.e., the glass and the SixNy coating), the optical performance was determined through iterative analysis of empirical measurements. Concentrating on just their spectral effect, a novel model was then developed to estimate the transfer of light to the PV cell and the return of light from the PV module with simultaneous degradation mechanisms, which was compared to a mini-module previously subjected to HV-/HV+ stress. The model suggests one-third of the current loss observed for the mini-module can be attributed to the optical degradation of the packaging materials. The dominant degradation modes include encapsulant delamination and corrosion of the SixNy coating. Recommendations are given so that the optical model may be improved relative to accelerated testing and validated relative to field aging.

14 SOLAR ENERGY↗
DOE OSTI2021

Spatio-Temporal Modeling of Field Surveyed Backsheet Degradation

Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Lab based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Field surveyed data is critical to assess the performance of component lifetime. Using a documented field survey protocol, 13 field surveys where conducted. Each measurement is encoded with it's spatial location in respect to the other modules. By combining field survey data on degradation predictors with real time satellite weather data, data-driven predictive models of backsheet degradation were trained. LOESS models were constructed to investigate the spatial dependence of measurements. It was found that micro-climatic effects like tree-lines, ground surface changes, and elevation changes effected the magnitude and variance of the measurements. A GAM model was created to predict the value of degradation based on measured predictors. The model includes variables on the climate of the system and the location of each measurement in the PV mounting structure. The model performed well with an adj.R 2 of 0.95 for yellowness index prediction. The model was cross-validated using k-folds.

backsheet↗
DOE OSTI2022

Nitrogen increases early‐stage and slows late‐stage decomposition across diverse grasslands

1. To evaluate how increased anthropogenic nutrient inputs alter carbon cycling in grasslands, we conducted a litter decomposition study across 20 temperate grasslands on three continents within the Nutrient Network, a globally distributed nutrient enrichment experiment 2. We determined the effects of addition of experimental nitrogen (N), phosphorus (P) and potassium plus micronutrient (K μ ) on decomposition of a common tree leaf litter in a long-term study (maximum of 7 years; exact deployment period varied across sites). The use of higher order decomposition models allowed us to distinguish between the effects of nutrients on early- versus late-stage decomposition. 3. Across continents, the addition of N (but not other nutrients) accelerated early-stage decomposition and slowed late-stage decomposition, increasing the slowly decomposing fraction by 28% and the overall litter mean residence time by 58%. 4. Synthesis. Using a novel, long-term cross-site experiment, we found widespread evidence that N enhances the early stages of above-ground plant litter decomposition across diverse and widespread temperate grassland sites but slows late-stage decomposition. These findings were corroborated by fitting the data to multiple decomposition models and have implications for N effects on soil organic matter formation. For example, following N enrichment, increased microbial processing of litter substrates early in decomposition could promote the production and transfer of low molecular weight compounds to soils and potentially enhance the stabilization of mineral-associated organic matter. By contrast, by slowing late-stage decomposition, N enrichment could promote particulate organic matter (POM) accumulation. Such hypotheses deserve further testing.

Nutrient Network (NutNet)↗
DOE OSTI2023

Triaxial Shear Tests on Simulated Sierra White Fault Gouge & Borehole Simulation in Sierra White Gouge

Laboratory shear tests were conducted on pulverized Sierra White granite (SWG) to investigate slip mechanisms in naturally occurring faults. Synthetic fault geometries were constructed by sandwiching fine grained SWG powder in between steel forcing blocks. For dry experiments, ~3.5 g of SWG powder was poured onto the face of the lower steel forcing block and leveled. For saturated experiments, enough fluid was added to the ~3.5 g of Sierra White granite powder to form a slurry. This slurry was applied to the lower forcing block and leveled. Inclined forcing blocks with 25.4 mm diameter and 35° faces, which were machined from ground steel rods with fine teeth on the faces, help to hold the gouge in place and prevent delamination at the interface. The top forcing block had a 2.03 mm centered hole to allow pore fluid access to the gouge. A fine steel mesh prevented back flow of the gouge into pore fluid lines. Samples were isolated from the confining medium using three layers of heat shrink polyolefin, as shown in Figure 1. The outer layer was shrunk over the o-rings on the end caps to form an impermeable seal, which was reinforced with steel tie wires on both sides of the o-rings. Hardened steel spacers and copper shim stock was placed between the steel forcing blocks and the end caps to preserve the parallelism of the Hastelloy wetted parts. For dry samples, the end caps were plugged, while the end caps for the saturated samples were connected to pore lines.

58 GEOSCIENCES↗
DOE OSTI2024

Predicting the X-ray Absorption Spectrum of Ozone with Single Configuration State Functions

X-ray absorption spectra (XAS) of biradicaloid species are often thought to represent a challenge to theoretical methods. This has led to the testing of recently developed multireference techniques on the XAS of ozone, but reproduction of the experimental spectral profile has proven difficult. We utilize a minimal model consisting of a single configuration state function (CSF) per excited state to model core-level excitations of ozone, with the orbitals of each CSF optimized using the restricted open-shell Kohn–Sham (ROKS) method. This protocol leads to semiquantitative agreement with experimental XAS. In fact, we find that low-lying core-hole excited states in biradicaloids can be approximated with individual CSFs, despite the presence of multireference character in the ground state. Here, we also report that the 1s → π* and 1s → σ* transitions have quite distinct widths for O 3 . This reveals the importance of sampling over a representative range of geometries from the vibrational ground state for properly assessing the accuracy of electronic structure methods against experiments instead of the popular procedure of uniformly broadening stick spectra at the equilibrium geometry.

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

Deep learning methods for obtaining photometric redshift estimations from images

ABSTRACT Knowing the redshift of galaxies is one of the first requirements of many cosmological experiments, and as it is impossible to perform spectroscopy for every galaxy being observed, photometric redshift (photo-z) estimations are still of particular interest. Here, we investigate different deep learning methods for obtaining photo-z estimates directly from images, comparing these with ‘traditional’ machine learning algorithms which make use of magnitudes retrieved through photometry. As well as testing a convolutional neural network (CNN) and inception-module CNN, we introduce a novel mixed-input model that allows for both images and magnitude data to be used in the same model as a way of further improving the estimated redshifts. We also perform benchmarking as a way of demonstrating the performance and scalability of the different algorithms. The data used in the study comes entirely from the Sloan Digital Sky Survey (SDSS) from which 1 million galaxies were used, each having 5-filtre (ugriz) images with complete photometry and a spectroscopic redshift which was taken as the ground truth. The mixed-input inception CNN achieved a mean squared error (MSE) =0.009, which was a significant improvement ($30{{\ \rm per\ cent}}$) over the traditional random forest (RF), and the model performed even better at lower redshifts achieving a MSE = 0.0007 (a $50{{\ \rm per\ cent}}$ improvement over the RF) in the range of z < 0.3. This method could be hugely beneficial to upcoming surveys, such as Euclid and the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST), which will require vast numbers of photo-z estimates produced as quickly and accurately as possible.

79 ASTRONOMY AND ASTROPHYSICS↗