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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 55 records · Page 3

Grand Teton Ecological Forecasting: Assessing Forage Change and Winter Habitat Availability for Bighorn Sheep that Employ a High-Elevation Overwintering Strategy to Identify Areas for Intervention

Grand Teton National Park provides habitat for a small native population of approximately 125 bighorn sheep (Ovis canadensis). The reduction in population of this species is attributed to loss of low elevation habitat, changing local environmental and climatic conditions, and increased disturbance from backcountry recreation. In response to these changes, this population of sheep employs a unique high-elevation wintering strategy in which they amass large fat stores in the summer and expend as little energy as possible in the winter while foraging on high elevation wind-swept and snow-free areas. For this project, DEVELOP partnered with Grand Teton National Park and used NASA Earth observations including Landsat 8 Operational Land Imager (OLI), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 5 Thematic Mapper (TM), and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data to assess habitat suitability. Landcover change analyzed between 1987 and 2020 indicated shifting trends in grass and forb cover and tree cover. These trends persisted in the 2031 prediction, with grass cover decreasing and tree cover increasing, which translates to a loss of overall favorable habitat for bighorn sheep. Snow cover analyzed between 2001 and 2020 indicated similar unfavorable trends for the sheep with a decrease in barren areas, important for winter foraging. Finally, habitat suitability was modeled for 2020 and predicted to 2031 to determine habitat gains and losses for this species across the landscape. Overall, the results predicted decreases in suitable habitat and indicated that while these sheep are highly adaptable, strategies to manage suitable bighorn habitat may need to be employed rapidly to effectively conserve this species.

Remote sensing↗

Employing Relaxed Smoothness Constraints on Imaginary Part of Refractive Index in AERONET Aerosol Retrieval Algorithm

In the Aerosol Robotic Network (AERONET) retrieval algorithm, smoothness constraints on the imaginary part of the refractive index provide control of retrieved spectral dependence of aerosol absorption by preventing the inversion code from fitting the noise in optical measurements and thus avoiding unrealistic oscillations of retrievals with wavelength. The history of implementation of the smoothness constraints in the AERONET retrieval algorithm is discussed. It is shown that the latest version of the smoothness constraints on the imaginary part of refractive index, termed standard and employed by Version 3 of the retrieval algorithm, should be modified to account for strong variability of light absorption by brown-carbon-containing aerosols in UV through mid-visible parts of the solar spectrum. In Version 3 strong spectral constraints were imposed at high values of the Ångström exponent (440–870 nm) since black carbon was assumed to be the primary absorber, while the constraints became increasingly relaxed as aerosol exponent deceased to allow for wavelength dependence of absorption for dust aerosols. The new version of the smoothness constraints on the imaginary part of the refractive index assigns different weights to different pairs of wavelengths, which are the same for all values of the Ångström exponent. For example, in the case of four-wavelength input, the weights assigned to short-wavelength pairs (440–675, 675–870 nm) are small so that smoothness constraints do not suppress natural spectral variability of the imaginary part of the refractive index. At longer wavelengths (870–1020 nm), however, the weight is 10 times higher to provide additional constraints on the imaginary part of refractive index retrievals of aerosols with a high Ångström exponent due to low sensitivity to aerosol absorption for longer channels at relatively low aerosol optical depths. The effect of applying the new version of smoothness constraints, termed relaxed, on retrievals of single-scattering albedo is analyzed for case studies of different aerosol types: black- and brown-carbon-containing fine mode aerosols, mineral dust coarse mode aerosols, and urban industrial fine mode aerosol. It is shown that for brown-carbon-containing aerosols employing the relaxed smoothness constraints resulted in significant reduction in retrieved single-scattering albedo and spectral residual errors (compared to standard) at the short wavelengths. For example, biomass burning smoke cases showed a reduction in single-scattering albedo and spectral residual error at 380 nm of ∼ 0.033 and ∼ 17 %, respectively, for the Rexburg site and ∼ 0.04 and ∼ 12.7 % for the Rimrock site, both AERONET sites in Idaho, USA. For a site with very high levels of black-carbon-containing aerosols (Mongu, Zambia), the effect of modification in the smoothness constraints was minor. For mineral dust aerosols at small Ångström exponent values (Mezaira site, UAE), the spectral constraint on the imaginary part of the refractive index was already relaxed in Version 3; therefore the new relaxed constraint results in minimal change. In the case of weakly absorbing urban industrial aerosols at the GSFC site, there are significant changes in retrieved single-scattering albedo using relaxed assumption, especially reductions at longer wavelengths: ∼ 0.016 and ∼ 0.02 at 875 and 1020 nm, respectively, for 440 nm aerosol optical depth (AOD) ∼ 0.3. The modification of smoothness constraints on the imaginary part of the refractive index has a minor effect on retrievals of other aerosol parameters such as the real part of the refractive index and parameters of the aerosol size distribution. The implementation of the relaxed smoothness constraints on the imaginary part of the refractive index in the next version of the AERONET inversion algorithm will produce significant impacts at some sites in short wavelength channels (380 and 440 nm) for some biomass burning smoke cases with significant brown carbon content and possibly in mid-visible channels (500 and 675 nm) to near-infrared channels (870 to 1020 nm) for some urban industrial aerosol types. However, most differences in single-scattering albedo retrievals between those applying the new relaxed constraint and the standard constraint will be within the uncertainty of the single-scattering albedo retrievals, depending on the level of aerosol optical depth, Ångström exponent, brown carbon content and wavelength.

Aliaksandr Siniuk↗

Distributional Equity in the Employment and Wage Impacts of Energy Transitions

We use restricted-access, geocoded data on the near-universe of workers in 23 US states to quantify the impact of wind energy development on local earnings and employment, by race, ethnicity, sex, and educational attainment. We find significant impacts that persist for several years beyond the project construction phase. Our estimates are larger than those from previous studies but still small relative to typical economic multipliers for fiscal spending or investment in other industries. We find the largest percentage increases for black workers and workers who either do not have a high school diploma or who have a college degree. We also find the economic gains for men to be much larger than those for women. Finally, we find estimates from data aggregated to the county level to be significantly lower than our worker-level estimates. We suggest a number of areas for further study building off the justice implications of our findings.

employment↗

A data-driven framework for predicting machining stability: employing simulated data, operational modal analysis, and enhanced transfer learning

Chatter, a self-excited vibration phenomenon, presents a significant challenge in machining operations, particularly in high-speed milling, where it can degrade tool life, reduce material removal efficiency, and compromise workpiece quality. Addressing this challenge requires a reliable predictive model that can accommodate the complex dynamics of various machining scenarios. This study introduces a novel, data-driven approach to predicting machining stability, leveraging over 140,000 simulated datasets and employing advanced techniques such as operational modal analysis (OMA), enhanced transfer learning (TL), and receptance coupling substructure analysis (RCSA). By integrating these methodologies, the framework effectively classifies and predicts chatter across diverse operational modes, achieving robust and accurate outcomes. Our model utilizes a Random Forest (RF) classifier trained with the comprehensive dataset, which demonstrates substantial improvements in both predictive accuracy and robustness. Specifically, the RF model achieved an accuracy rate of 85%, an area under the curve (AUC) of 0.90, and an F1 score of 0.88, underscoring its capability to adapt to varying machining configurations. These results highlight the framework’s potential to enhance operational efficiency and machining quality by providing reliable chatter predictions across a broad range of machining parameters. In conclusion, this research thus offers a significant advancement in predictive maintenance for machining processes, enabling more stable and efficient manufacturing operations.

42 ENGINEERING↗

Wave energy resource characterization employing joint distributions in frequency-direction-time domain

Joint and marginal distributions in the frequency, direction, and time domain are employed to demonstrate their value for wave energy resource characterization when full spectra are available. Insights gained through analysis of these distributions support wave energy converter concept design, operation and maintenance. Spatial trends in the wave energy resource and contributing wave energy systems along the continental shelf of the West Coast of the United States are investigated using the most recent two-dimensional wave spectra measurements at four buoys over an eleven year period (2008 to 2018). Resource hot spots and dominant resolved energy resource bands in the frequency-direction-time domain are delineated. Resource attributes, including frequency and directional spreading, and seasonal variability, are characterized using joint distributions and marginal distributions of wave power spectra. North Pacific westerly swells in the winter season, augmented by Aleutian low-pressure southwesterly swells, are the principal suppliers of the dominant resource and main drivers influencing resource attributes. In conclusion, the modification of these systems southward, especially the North Pacific westerly swells, explains the observed spatial resource trends. The dominant resource wave period shifts two seconds to higher wave periods, thirty degrees in the dominant direction band to a more northward orientation, and forward by one month.

16 TIDAL AND WAVE POWER↗

Manipulating symmetry-breaking charge separation employing molecular recognition

The exploration of symmetry-breaking charge separation (SB-CS) is imperative when designing functional light-harvesting materials. Past explorations, however, have been confined to covalent systems, more often than not requiring complicated/demanding syntheses and facing inconvenient regulation of charge transfer processes. Here, in this work, we present a concept that regulates the efficiency of SB-CS through molecular recognition utilizing a pyridinium-based cyclophane as a host. This host undergoes photo-driven excited-state SB-CS. By employing different guests with distinct frontier molecular orbital energy levels, we have achieved comprehensive control of electron transfer pathways in the cyclophane, modulating between accelerated (>10-fold) intramolecular SB-CS involving superexchange and direct intermolecular electron transfer between the host and guest. The improvement in SB-CS efficiency results in catalytic activity for the photo-oxidation of a sulfur-mustard simulant. This research offers an opportunity for tuning SB-CS by utilizing molecular recognition, which holds the potential for achieving precise regulation without complicated organic syntheses.

charge transfer↗

Breakthrough Zn(II) Catalyst for Direct Air Capture Employing CO 2 Hydration

Direct air capture (DAC) represents a vital technology for atmospheric CO₂ remediation, but few studies have tested catalysts at dilute atmospheric CO₂ concentrations. Inspired by the carbonic anhydrase metalloenzyme, we report a catalytic DAC strategy employing robust zinc(II) enzyme mimics that enable efficient CO₂ sequestration pathways. A catalyst-mediated CO₂ hydration cycle in aqueous sorbents facilitates accelerated capture from dilute atmospheric air, thereby addressing the kinetic limitations observed in carbonate-based systems. Our developed complexes [ZnC1] and [ZnC2] enhance capture rates up to two-fold at millimolar concentrations and improve CO₂ mass transfer by 40-60% in 1 M K₂CO₃ sorbent under ambient conditions. These bench-stable, earth-abundant zinc catalysts operate effectively under dilute CO₂ concentrations, overcoming the kinetic limitations of conventional carbonate-based sorbents. As a result, mechanistic studies support a biomimetic catalytic cycle that facilitates rapid CO₂ conversion, demonstrating that catalyst-assisted DAC can enable energy-efficient, scalable carbon capture technologies.

Atmospheric chemistry↗

Large-Scale Interlaboratory DI-FT-ICR MS Comparability Study Employing Various Systems

We report ultra-high resolution mass spectrometry (UHR-MS) coupled with direct infusion (DI) electrospray ionization offers a fast solution for accurate untargeted profiling. Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometers have been shown to produce a wealth of insights into complex chemical systems because they enable unambiguous molecular formula assignment even if the vast majority of signals is of unknown identity. Inter-laboratory comparisons are required to apply this type of instrumentation in quality control (for food industry or pharmaceutics), large-scale environmental studies or clinical diagnostics. Extended comparisons employing different FT-ICR MS instruments with qualitative direct infusion analysis are scarce since the majority of detected compounds cannot be quantified. The extent to which observations can be reproduced by different laboratories remains unknown. We set up a preliminary study which encompassed a set of seventeen laboratories around the globe, diverse in instrumental characteristics and applications, to analyze the same sets of extracts from commercially available standard human blood plasma and Standard Reference Material (SRM) for blood plasma (SRM1950), which were delivered at different dilutions or spiked with different concentrations of pesticides. The aim of this study was to assess the extent to which the outputs of differently tuned FTICR mass spectrometers, with different technical specifications, are comparable for setting the frames of a future DI-FT-ICR MS ring trial. We concluded that a cluster of five laboratories, with diverse instrumental characteristics showed comparable and representative performance across all experiments, setting a reference to be used in a future ring trial on blood plasma.

47 OTHER INSTRUMENTATION↗

Unleashed from constrained optimization: quantum computing for quantum chemistry employing generator coordinate inspired method

Hybrid quantum-classical approaches offer potential solutions to quantum chemistry problems, yet they often manifest as constrained optimization problems. Here, we explore the interconnection between constrained optimization and generalized eigenvalue problems through the Unitary Coupled Cluster (UCC) excitation generators. Inspired by the generator coordinate method, we employ these UCC excitation generators to construct non-orthogonal, overcomplete many-body bases, projecting the system Hamiltonian into an effective Hamiltonian, which bypasses issues such as barren plateaus that heuristic numerical minimizers often encountered in standard variational quantum eigensolver (VQE). Diverging from conventional quantum subspace expansion methods, we introduce an adaptive scheme that robustly constructs the many-body basis sets from a pool of the UCC excitation generators. This scheme supports the development of a hierarchical ADAPT quantum-classical strategy, enabling a balanced interplay between subspace expansion and ansatz optimization to address complex, strongly correlated quantum chemical systems cost-effectively, setting the stage for more advanced quantum simulations in chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Root angle is controlled by EGT1 in cereal crops employing an antigravitropic mechanism

Root angle in crops represents a key trait for efficient capture of soil resources. Root angle is determined by competing gravitropic versus antigravitropic offset (AGO) mechanisms. Here we report a root angle regulatory gene termed ENHANCED GRAVITROPISM1 ( EGT1 ) that encodes a putative AGO component, whose loss-of-function enhances root gravitropism. Mutations in barley and wheat EGT1 genes confer a striking root phenotype, where every root class adopts a steeper growth angle. EGT1 encodes an F-box and Tubby domain-containing protein that is highly conserved across plant species. Haplotype analysis found that natural allelic variation at the barley EGT1 locus impacts root angle. Gravitropic assays indicated that Hvegt1 roots bend more rapidly than wild-type. Transcript profiling revealed Hvegt1 roots deregulate reactive oxygen species (ROS) homeostasis and cell wall-loosening enzymes and cofactors. ROS imaging shows that Hvegt1 root basal meristem and elongation zone tissues have reduced levels. Atomic force microscopy measurements detected elongating Hvegt1 root cortical cell walls are significantly less stiff than wild-type. In situ analysis identified HvEGT1 is expressed in elongating cortical and stele tissues, which are distinct from known root gravitropic perception and response tissues in the columella and epidermis, respectively. We propose that EGT1 controls root angle by regulating cell wall stiffness in elongating root cortical tissue, counteracting the gravitropic machinery’s known ability to bend the root via its outermost tissues. We conclude that root angle is controlled by EGT1 in cereal crops employing an antigravitropic mechanism.

59 BASIC BIOLOGICAL SCIENCES↗

Multiphysics analysis system for heat pipe cooled micro-reactors employing PRAGMA-OpenFOAM-ANLHTP

A multiphysics analysis system for neutronics/thermo-mechanical/heat-pipe analysis of heat pipe cooled micro-reactors was developed using the PRAGMA code as the neutronics engine. PRAGMA, which used to be a GPU-based continuous-energy MC code for power reactor applications, now has an extended geometry package to handle geometries with unstructured meshes generated by the ANSYS Design-Modeler and Meshing. The NVIDIA ray tracing engine OptiX was exploited for efficient neutron transport on unstructured geometry. On the multiphysics side, the open-source CFD tool OpenFOAM and one-dimensional heat pipe analysis code ANLHTP were adopted. The manager-worker system based on the MPI dynamic process management (DPM) model enables efficient coupling of codes employing different parallelization schemes. With all the features, the multiphysics analysis of the one-sixth symmetrical MegaPower 2D core was performed and it demonstrated the benefit of the tight integration of the three-way coupling system and one-to-one geometry coupling strategy. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Quantum time dynamics employing the Yang-Baxter equation for circuit compression

Quantum time dynamics (QTD) is considered a promising problem for quantum supremacy on near-term quantum computers. However, QTD quantum circuits grow with increasing time simulations. This study focuses on simulating the time dynamics of one-dimensional (1D) integrable spin chains with nearest-neighbor interactions. We have proved the existence of a reflection symmetry in the quantum circuit employed for simulating the time evolution of certain classes of 1D Heisenberg model Hamiltonians by virtue of the quantum Yang-Baxter equation, and how this symmetry can be exploited to compress and produce a shallow quantum circuit. With this compression scheme, the depth of the quantum circuit becomes independent of step size and only depends on the number of spins. We show that the depth of the compressed circuit is rigorously a linear function of the system size for the studied Heisenberg model Hamiltonians in the present work. As a consequence, the number of CNOT gates in the compressed circuit only scales quadratically with the system size, which allows for the simulations of time dynamics of very large 1D spin chains. We derive the compressed circuit representations for different special cases of the Heisenberg Hamiltonian. We compare and demonstrate the effectiveness of this approach by performing simulations on quantum computers.

1-dimensional spin chains↗

A 194nW Energy-Performance-Aware loT SoC Employing a 5.2nW 92.6% Peak Efficiency Power Management Unit for System Performance Scaling, Fast DVFS and Energy Minimization

A self-powered IoT system-on-chip (SoC) reduces power to sub-μw and employs multiple power-management techniques to trade-off ultra-low power (ULP), higher performance, smaller energy harvester footprint, and longer operating lifetime. Minimum Energy Point Tracking (MEPT) [1]–[4] keeps an SoC operating at the minimum energy point (MEP) to enhance system lifetime. Previous sample-and-hold MEPT schemes need frequent voltage comparisons and a high-frequency clock that increases power [2]. Current-ratio-based MEPT relies on specialized CMOS technology for body-bias tuning [3]. A switched-capacitor-based MEPT can achieve energy minimization at a targeted performance [4], but it uses a 30MHz clock witμW power consumption and low power efficiency. For ULP IoT applications, SoCs need to have ultra-low quiescent power, high efficiency for energy delivery, performance scaling based on available energy, and energy minimization to increase system lifetime. In this work, we propose an ULP IoT SoC with a triple-mode power management unit (PMU) that integrates energy-performance scaling, event-driven fast DVFS, and MEPT features to improve the system energy efficiency, as shown in Fig. 13.8.1. This work achieves a minimum 194nW power consumption for the SoC and 5.2nW quiescent power for the PMU with a 92.6% peak efficiency and >10 4 dynamic range. The timing waveform in Fig. 13.8.1 (bottom), demonstrates the transition of the three modes including energy aware (EA), performance aware (PA), and MEPT based on event priority and input voltage level which reflects the energy availability. As such, the system energy consumption and performance could be well-balanced based on both the input and output conditions.

self-powered IoT system-on-chip (SoC)↗

A Dual-Active-Bridge Converter Employing a Variable Inductor Without an Auxiliary Circuit

This paper proposes a dual active bridge (DAB) converter employing a variable inductor (VI) without an auxiliary circuit. Unlike conventional VI-based designs that require an external DC bias circuit, the proposed DAB utilizes the input DC current itself as the bias source, enabling automatic inductance variation with load conditions. The inductance naturally increases at low power and decreases at high power, effectively extending the zero voltage switching (ZVS) range and reducing circulating current, respectively. The VI was experimentally implemented and characterized to obtain its inductance-current profile, which was then integrated into a PLECS model of the DAB converter for circuit and thermal simulations. Simulation results confirm that the proposed auxiliary-free VI-DAB converter achieves a wider ZVS range and lower circulating current compared with a conventional fixed-inductor DAB converter. By realizing a variable inductor without any auxiliary bias circuitry, the proposed approach maintains soft switching and reduces reactive current losses across a wide load range, leading to improved efficiency and simplified implementation.

Jo, Cheolhui [ORNL] (ORCID:0000000322692434)↗

Employing Weibull Analysis and Weakest Link Theory to Resolve Crystalline Silicon PV Cell Strength Between Bare Cells and Reduced- and Full-Sized Modules

Weibull analysis and weakest link theory are employed to resolve the probability of crystalline silicon PV cell fracture when measured as bare cells and when stressed in reduced- and full-sized modules. Experimental results indicated that the characteristic cell strength is reduced by ~20% once packaged into the laminate of a one-cell module and loaded in four-point flexure (4PF). This experimental observation was shown consistent with a weakest link theory prediction that the strength limiting flaws reside on the surface of the cell's edge. Here, the analysis is ultimately extended to present the equivalent loading of four-cell modules by uniform pressure and 4PF and a uniformly loaded full-sized module and demonstrates that smaller, representative, modules must be loaded to a much higher level than their parent full-sized modules to achieve an equivalent probability for cell fracture.

14 SOLAR ENERGY↗

Employing Fracture Statistics to Track Cell Reliability Through Module Fabrication

In this work we demonstrate how fracture statistics may be employed to track cell reliability through module fabrication steps. We were able to detect how cell cutting equipment could reduce cell fracture strain by 25 % as well as increase its variability. A smaller reduction was found to result from the ribbon soldering operation, and all cells measured were weaker when strained in an orientation perpendicular to the gridlines. Cell fracture measurements were found to be consistent with the number of cracked cells experienced in full sized modules exposed to mechanical loading. A structural mechanics model was created to elucidate how the requisite fracture strain is developed in a cell encapsulated within a PV module and demonstrates that this strain decreases more than 50 % from its center to edge when placed within the inner loading span of four-point flexure. The associated implications on the apparent cell strength is examined with an effective volume treatment.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Clean Energy Employment Impacts and Occupational Analyses: Building Envelope & Electrification Upgrades

Under the Communities LEAP (Local Energy Action Program) Pilot, the U.S. Department of Energy (DOE) is working with a group of LEAP communities to bolster workforce development initiatives and support the growth of local employment in the clean energy economy. Through this resource, DOE seeks to provide participating communities with an overview of the types of occupations that could be affected by investments in building envelope and building electrification upgrades in existing building stock - differentiating between the residential and commercial sectors. This occupational analysis is intended to be used by communities to inform workforce initiatives (e.g., local training and education programs) as they implement building energy efficiency and electrification projects at scale.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗