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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 325 records · Page 18

Diverse organic carbon dynamics captured by radiocarbon analysis of distinct compound classes in a grassland soil

Soil organic carbon (SOC) is a large, dynamic reservoir composed of a complex mixture of plant- and microbe-derived compounds with a wide distribution of cycling timescales and mechanisms. The distinct residence times of individual carbon components within this reservoir depend on a combination of factors, including compound reactivity, mineral association, and climate conditions. To better constrain SOC dynamics, bulk radiocarbon measurements are commonly used to trace biosphere inputs into soils and to estimate timescales of SOC cycling. However, understanding the mechanisms driving the persistence of organic compounds in bulk soil requires analyses of SOC pools that can be linked to plant sources and microbial transformation processes. Here, we adapt approaches, previously developed for marine sediments, to isolate organic compound classes from soils for radiocarbon ( 14 C) analysis. We apply these methods to a soil profile from an annual grassland in Hopland, California (USA), to assess changes in SOC persistence with depth (down to 1 m). We measured the radiocarbon values of water-extractable organic carbon (WEOC), total lipid extracts (TLEs), total hydrolyzable amino acids (AAs), and an acid-insoluble (AI) fraction from bulk and physically separated size fractions (< 2 mm, 2 mm–63 µm, and < 63 µm). Our results show that Δ 14 C values of bulk soil, size fractions, and extracted compound classes became more depleted with depth, and individual SOC components have distinct age–depth distributions that suggest distinguishable cycling rates. We found that AAs and TLEs cycle faster than the bulk soils and the AI fraction. The AI was the most 14 C-depleted fraction, indicating that it is the most chemically inert in this soil. Our approach enables the isolation and measurement of SOC fractions that separate functionally distinct SOC pools that can cycle relatively quickly (e.g., plant and microbial residues) from more passive or inert SOC pools (associated with minerals or petrogenic) from bulk soils and soil physical fractions. With the effort to move beyond SOC bulk analysis, we find that compound class 14 C analysis can improve our understanding of SOC cycling and disentangle the physical and chemical factors driving OC cycling rates and persistence.

58 GEOSCIENCES↗

Diversifying Composition Leads to Hierarchical Composites with Design Flexibility and Structural Fidelity

Although significant progress has been made in the self-assembly of nanostructures, present successes heavily rely on precision in building block design, composition, and pair interactions. These requirements fundamentally limit our ability to synthesize macroscopic materials where the likelihood of impurity inclusion escalates and, more importantly, to access molecular-to-nanoscopic-to-microscopic-to-macroscopic hierarchies, since the types and compositions of building blocks vary at each stage. Inspired by biological blends and high-entropy alloys, we hypothesize that diversifying the blend’s composition can overcome these limitations. Increasing the number of components increases mixing entropy, leading to the dispersion of different components and, as a result, enhances interphase miscibility, weakens the dependence on specific pair interactions, and enables long-range cooperativity. This hypothesis is validated in complex blends containing small molecules, block copolymer-based supramolecules, and nanoparticles/colloidal particles. Hierarchically structured composites can be obtained with formulation flexibility in the filler selection and blend composition. It is worth noting that, by adding small molecules, we can solve the size constraint that plagues traditional block copolymer/nanoparticle blends. Detailed characterization and simulation further confirm that each component is distributed to locally mediate unfavorable interactions, cooperatively mitigate composition fluctuations, and retain structural fidelity. Furthermore, the blends have sufficient mobility to access tunable microstructures without compromising the order of the nanostructure. Besides establishing a kinetically viable pathway to release current constraints in the composite design and to navigate uncertainties during structure formation over multiple length scales, the present study demonstrates that entropy-driven behaviors can be realized in systems beyond high-entropy alloys despite inherent differences between metal alloys and organic/inorganic hybrids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pore Aperture Control Toward Size‐Exclusion‐Based Hydrocarbon Separations

Metal–organic frameworks (MOFs) have been proposed as a promising material for non-thermal chemical separations owing to their high structural diversity and tunability. Here, we report the synthesis of a zinc-based MOF containing a three-dimensional (3D) linker, bicyclo[2.2.2]octane-1,4-dicarboxylic acid, with high thermal stability towards the separation of hexane isomers. The incorporation of the 3D linker enhances the structural stability and provides well-defined pore apertures/channels with sub-Ångstrom precision. This precision allowed for the separation of similarly sized hexane isomers based on subtle differences in their kinetic diameters. Multi-component liquid phase batch experiments confirmed the separation of hexanes mixture into linear, monobranched, and dibranched isomers. This work represents a significant milestone in the construction of stable Zn-based MOFs and the incorporation of 3D linkers as a potential solution to challenging separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improvement of Oxygen Reduction Performance in Alkaline Media by Tuning Phase Structure of Pd–Bi Nanocatalysts

Tuning the crystal phase of bimetallic nanocrystals offers an alternative avenue to improving their electrocatalytic performance. Herein, we present a facile and one-pot synthesis approach that is used to enhance the catalytic activity and stability toward oxygen reduction reaction (ORR) in alkaline media via control of the crystal structure of Pd-Bi nanocrystals. By merely altering the types of Pd precursors under the same conditions, the monoclinic structured Pd 5 Bi 2 and conventional face-centered cubic (fcc) structured Pd 3 Bi nanocrystals with comparable size and morphology can be precisely synthesized, respectively. Interestingly, the carbon-supported monoclinic Pd 5 Bi 2 nanocrystals exhibit superior ORR activity in alkaline media, delivering a mass activity (MA) as high as 2.05 A/mg Pd . After 10,000 cycles of ORR durability test, the monoclinic structured Pd 5 Bi 2 /C nanocatalysts still remain a MA of 1.52 A/mg Pd , which is 3.6 times, 16.9 times, and 21.7 times as high as those of the fcc Pd 3 Bi/C counterpart, commercial Pd/C, and Pt/C electrocatalysts, respectively. Moreover, structural characterizations of the monoclinic Pd 5 Bi 2 /C nanocrystals after the durability test demonstrate the excellent retention of the original size, morphology, composition, and crystal phase, greatly alleviating the leaching of the Bi component. Overall, this work provides new insight for the synthesis of multimetallic catalysts with a metastable phase and demonstrates phase-dependent catalytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Neutrinos from Earth-bound dark matter annihilation

Abstract A sub-component of dark matter with a short collision length compared to a planetary size leads to efficient accumulation of dark matter in astrophysical bodies. We analyze possible neutrino signals from the annihilation of such dark matter and conclude that in the optically thick regime for dark matter capture, the Earth provides the largest neutrino flux. Using the results of the existing searches, we consider two scenarios for the neutrino flux, from stopped mesons and prompt higher-energy neutrinos. In both cases we exclude some previously unexplored parts of the parameter space (dark matter mass, its abundance, and the scattering cross section on nuclei) by recasting the existing neutrino searches.

Astronomy & Astrophysics↗

The AMACStar ASIC for the HL-LHC ATLAS ITk Strip detector: design, verification, testing, and quality assurance

For the high-luminosity upgrade to the LHC (HL-LHC), the ATLAS detector at CERN requires an all-new inner detector, the Inner Tracker (ITk). The ITk Strip subdetector is made up of silicon modules, which include three types of radiation-hard ASICs. One of these is the Autonomous Monitor and Control (AMAC). The AMAC is manufactured by Global Foundries using 130 nm CMOS8RF DM technology and is approximately 3 by 5 mm in size. This ASIC autonomously monitors the temperatures, voltages, and currents in the module components while controlling critical values in order to prevent these quantities from reaching dangerous levels. The final design, AMACStar, was verified, tested, and ensured to perform all necessary functions. A quality control procedure using an in-house probe station set-up was developed in order to ensure that every individual chip on each wafer of AMACStars required by the ITk Strip project met performance requirements. The average per wafer yield of usable AMACStars is 92.33%, exceeding the design-specific 90% yield estimated for project costing. This estimate was based on actual yields for similar designs in this process.

Analogue electronic circuits↗

Hybrid MEMS-CMOS ion traps for NISQ computing

Surging interest in engineering quantum computers has stimulated significant and focused research on technologies needed to make them manufacturable and scalable. In the ion trap realm this has led to a transition from bulk three-dimensional macro-scale traps to chip-based ion traps and included important demonstrations of passive and active electronics, waveguides, detectors, and other integrated components. At the same time as these technologies are being developed the system sizes are demanding more ions to run noisy intermediate scale quantum (NISQ) algorithms, growing from around ten ions today to potentially a hundred or more in the near future. To realize the size and features needed for this growth, the geometric and material design space of microfabricated ion traps must expand. In this paper we describe present limitations and the approaches needed to overcome them, including how geometric complexity drives the number of metal levels, why routing congestion affects the size and location of shunting capacitors, and how RF power dissipation can limit the size of the trap array. Finally, we also give recommendations for future research needed to accommodate the demands of NISQ scale ion traps that are integrated with additional technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Atacama Cosmology Telescope: Constraints on prerecombination early dark energy

The early dark energy (EDE) scenario aims to increase the value of the Hubble constant (H0) inferred from cosmic microwave background (CMB) data over that found in the standard cosmological model (Λ CDM ), via the introduction of a new form of energy density in the early Universe. The EDE component briefly accelerates cosmic expansion just prior to recombination, which reduces the physical size of the sound horizon imprinted in the CMB. Previous work has found that nonzero EDE is not preferred by Planck CMB power spectrum data alone, which yield a 95% confidence level (C.L.) upper limit f EDE < 0.087 on the maximal fractional contribution of the EDE field to the cosmic energy budget. In this paper, we fit the EDE model to CMB data from the Atacama Cosmology Telescope (ACT) data release 4. We find that a combination of ACT, large-scale Planck TT (similar to WMAP), Planck CMB lensing, and BAO data prefers the existence of EDE at >99.7 % C .L . : f EDE = 0.091$^{+0.020}_{-0.036}$, with H 0 = 70.9$^{+1.0}_{-2.0}$ km/s/Mpc (both 68% C.L.). From a model-selection standpoint, we find that EDE is favored over Λ CDM by these data at roughly 3 σ significance. In contrast, a joint analysis of the full Planck and ACT data yields no evidence for EDE, as previously found for Planck alone. We show that the preference for EDE in ACT alone is driven by its TE and EE power spectrum data. The tight constraint on EDE from Planck alone is driven by its high-ℓ TT power spectrum data. Understanding whether these differing constraints are physical in nature, due to systematics, or simply a rare statistical fluctuation is of high priority. Here, the best-fit EDE models to ACT and Planck exhibit coherent differences across a wide range of multipoles in TE and EE, indicating that a powerful test of this scenario is anticipated with near-future data from ACT and other ground-based experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

ASDFL: An adaptive super‐pixel discriminative feature‐selective learning for vehicle matching

Abstract There are a large number of cameras in modern transportation system that capture numerous vehicle images continuously. Therefore, automatic analysis of these vehicle images is helpful for traffic flow management, criminal investigations and vehicle inspections. Vehicle matching, which aims to determine whether two input images depict an identical vehicle, is one of the core tasks in vehicle analysis. Recent relevant studies have focused on local feature extraction instead of global extraction, since local details can provide crucial cues to distinguish between cars. However, these methods do not select local features; that is, they do not assign weights to local features. Therefore, in this research, we systematically study the vehicle matching task, and present a novel annotation‐free local‐based deep learning method called Adaptive super‐pixel discriminative feature‐selective learning (ASDFL) to address this issue. In ASDFL, vehicle images are segmented into clusters of super‐pixels of similar size by considering the location and colour similarities of pixels without using any component‐level annotation. These super‐pixels are deemed to be the virtual components of vehicles. Moreover, a convolutional neural network is used to extract the deep features of these virtual components. Thereafter, an instance‐specific mask generation module driven by the extracted global features is enhanced to produce a mask to select the most distinctive virtual components of each vehicle image pair in the feature space. Finally, the vehicle matching task is accomplished by classifying the selected virtual component features of each imaged vehicle pair. Extensive experiments on two popular vehicle identification benchmarks demonstrate that our method is 1.57% and 0.8% more accurate than the previous baselines in a vehicle matching task on the VeRi and VehicleID datasets, respectively, which demonstrates the effectiveness of our method.

Qin, Rong↗

PV O&M Cost Model [SWR-21-14]

This tool presents a method for calculating costs associated with the operation and maintenance (O&M) of photovoltaic (PV) systems. The tool compiles details regarding the cost and frequency of multiple O&M services to estimate annual O&M costs ($/year) for each year of an analysis period, the net present value ($) of life cycle costs accumulated over the analysis period, and the reserve account amount ($) that might be required to fund unexpected repairs. The reserve account includes parts inventory and is important for providing a source of funds to make repairs quickly and avoid lost production. This method allows a detailed selection of services to perform based on system size, market served (e.g., residential, commercial, or utility), type and configuration of system components (e.g., micro-, string, or central inverter), and site and environmental conditions (e.g., pollen, bird populations) which is an improvement over simple per unit valuations of O&M costs ($/kW/year). This model also distinguishes costs that vary from year to year and increase at different rates over time as modeled by heuristic failure distributions (e.g., Weibull or Lognormal distribution) based on actuarial data for many of the services.

Walker, Andy↗

Model of Operation-and-Maintenance Costs for Photovoltaic Systems

This article presents a method for calculating costs associated with operation and maintenance (O&M) of photovoltaic (PV) systems. It compiles details regarding the cost and frequency of multiple O&M services to estimate annual O&M costs ($\$$/year) for each year of an analysis period, the net present value ($\$$) of life cycle costs accumulated over the analysis period, and the reserve account amount ($\$$). Here we show that this method is an improvement over the previous averaged or levelized per-unit ($\$$/kW/year) valuations for estimating PV O&M costs, because it allows a detailed selection of services to perform based on system size, market served (e.g., residential, commercial, or utility), type and configuration of system components (e.g., micro-, string or central inverter) and site and environmental conditions (e.g., snow, pollen, bird populations). This model also distinguishes costs that vary from year to year and increase at different rates over time because of heuristic failure distributions (e.g. Weibull or Lognormal distribution) based on actuarial data for many of the services. This cost model was created by the PV O&M Working Group of researchers and industry, sponsored by DOE Solar Energy Technologies Office, and has been published in an on-line version hosted by SunSpec Alliance at apsuite.sunspec.org. A spreadsheet version is included with this paper as supplementary material.

14 SOLAR ENERGY↗

Compact Diffusion Bonded Heat Exchanger Fatigue Life Simulations (Final Report)

Compact diffusion bonded heat exchangers are essential for high pressure heat exchange, but they are subject to thermal fatigue and ramp rate limitations. Simulation of these geometries is challenging with a large range of length and time scales from thousands of mm-sized microchannels inside a m-sized heat exchanger. Multi-physics simulations including thermal, fluid, and solid mechanics components are being used to predict stress within the heat exchangers under these conditions. These predictions can then be used to understand thermal ramp rate limitations while keeping maximum stresses low as well as fatigue life predictions from well-known empirical models.

42 ENGINEERING↗

Develop a Fast Analysis Solver for Welding Sequence Optimization

During the shipbuilding manufacturing process, materials are exposed to significant stresses, as induced both thermally and mechanically, that alter the intended design and significantly affect the production schedule, labor hours (fitting, welding, rework, etc.), and material structural performance. The type and magnitude of deformation of a given structure depends on many factors such as the material, thickness and quality of components, the process heat input, preheat and inter-pass temperatures, type and size of welds, welding sequence and direction, location, sequence, and degree of fixturing. Numerical simulations using finite element analysis (FEA) have long been used to analyze welding-induced structural distortion. For large assemblies, transient thermal elastic-plastic analysis (TEPA) can take days or weeks to run, and optimization of welding sequence is not feasible. Simplified analysis methods were developed to reduce computational time. However, it is challenging to use these techniques to fully optimize welding sequencing because of their applied simplifications in modeling weld details. A fast analysis solver that could be used by the shipbuilding industry is being developed for optimizing welding sequences by taking full advantage of modern GPU-based HPC hardware and incorporating patented acceleration schemes. The accelerated processing factors are up to 2200 times greater for large, multi-pass welded structures.

Yang, Yu-Ping↗

Magnetic properties of CrFeCoNi based high entropy alloys

Monte Carlo simulations are performed on three high entropy alloys: Cr0.25Fe0.25Co0.25Ni0.25, Cr0.2Fe0.2Co0.2Ni0.2Pd0.2, and Cr0.2Mn0.2Fe0.2Co0.2Ni0.2, with exchange interactions extracted from The ab initio Korringa-Kohn-Rostoker method combined with the coherent potential approximation calculations. Using finite size scaling analyses, we estimate the magnetic phase transition temperature for the four component alloy to be 108(2) K, and although the individual critical exponents are different from 3D Heisenberg universality class, the reduced exponent follows Suzuki weak universality. With the additional Palladium component, the transition temperature elevates to about 200 K. In contrast, we find no magnetic order for the five component alloy with Manganese at any finite temperatures.

Yin, Junqi↗

SURFACE FINISHING AND ELECTROLESS NICKEL PLATING OF ADDITIVELY MANUFACTURED (AM) METAL COMPONENTS

This study investigates the application of electroless nickel deposition on additively manufactured stainless steel samples. Current additive manufacturing (AM) technologies produce metal components with a rough surface. Rough surfaces generally exhibit fatigue characteristics, increasing the probability of initiating a crack or fracture to the printed part. For this reason, the direct use of as-produced parts in a finished product cannot be actualized, which presents a challenge. Post-processing of the AM parts is therefore required to smoothen the surface. This study analyzes chempolish (CP) and electropolish (EP) surface finishing techniques for post-processing AM stainless steel components CP has a great advantage in creating uniform, smooth surfaces regardless of size or part geometry EP creates an extremely smooth surface, which reduces the surface roughness to the sub-micrometer level. In this study, we also investigate nickel deposition on EP, CP, and as-built AM components using electroless nickel solutions. Electroless nickel plating is a method of alloy treatment designed to increase manufactured component's hardness and surface resistance to the unrelenting environment. The electroless nickel plating process is more straightforward than its counterpart electroplating.. We use low-phosphorus (2-5% P), medium-phosphorus (6-9% P), and high-phosphorus (10-13% P). These Ni deposition experiments were optimized using the L9 Taguchi design of experiments (TDOE), which compromises the prosperous content in the solution, surface finish, plane of the geometry, and bath temperature. The pre-and post-processed surface of the AM parts was characterized by KEYENCE Digital MicroscopeVHX-7000 and Phenom XL Desktop SEM. The experimental results show that electroless nickel deposition produces uniform Ni coating on the additively manufactured components up to 20 μm per hour. Mechanical properties of as-built and Ni coated AM samples were analyzed by applying a standard 10 N scratch test. Nickel coated AM samples were up to two times scratch resistant compared to the as-built samples. This study suggests electroless nickel plating is a robust viable option for surface hardening and finishing AM components for various applications and operating conditions.

Keywords: additive manufacturing, fatigue, chempol↗

Design of Modular Test Facility for Particle/sCO2 Heat Exchanger Evaluation

Heliogen has designed a 1.3 MW particle and supercritical carbon dioxide (sCO2) test loop to retire technical and manufacturing risks. The data from this facility will be used to validate near commercial-scale particle heat exchanger modules. The heat exchanger is scaled to capture all features of the full-scale modules. Testing will be conducted with CARBOBEAD HSP 16/30, a larger particle size than other recent testing. The system was designed to ASME codes with the constraint that sCO2 piping and other major components are stainless steels.

14 SOLAR ENERGY↗

Electrostatic Superlattices Beyond 1:1 Stoichiometry

ABSTRACT Exotic nanoparticle superstructures can be accessed by harnessing nanoparticle softness and charge regulation, features often viewed as obstacles to structural control. Here, we show that regulated charge mismatch in polymer‐grafted nanoparticles enables the assembly of high‐stoichiometry cubic superlattices. By co‐tuning grafting density, particle size, and bulk composition, we realize ionic‐lattice analogues, such as and , as well as single‐component and superlattices without atomic counterparts. The superlattice has recently been identified theoretically as a photonic band‐gap lattice. These phases emerge from a 1:1 “parent” lattice when local charge neutrality cannot be satisfied, driving either progressive interstitial filling or reorganization into a larger basis. For instance, the systematic occupation of ZnS tetrahedral sites yields , while ligand‐swapping symmetry breaking converts CsCl into . Upon heating, the assemblies exhibit reversible lattice contraction and pronounced negative thermal expansion. Furthermore, the energetic penalty for defects increases with nanoparticle size, facilitating the scalable production of high‐quality, open superlattices for photonic applications.

36 MATERIALS SCIENCE↗