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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 307 records · Page 17

The impact of nickel concentration and stacking fault energy on deformation mechanisms in high-purity austenitic Fe-Cr-Ni alloys

Understanding how composition affects deformation mechanisms in austenitic stainless steels is essential for developing accurate predictive models of stress-induced failures and stress corrosion cracking. Nickel (Ni), an element classified as a critical element, plays a crucial role in these processes. It is important to examine how Ni concentration influences stacking fault energy (SFE) and, consequently, the deformation mechanisms of austenitic stainless steels. However, in commercial stainless steels, the effects of other alloying elements and impurities can obscure Ni's role, complicating efforts to isolate its impact. Here, in this study, we use two high-purity Fe-Cr-Ni alloys to investigate how Ni concentration and SFE interact to alter deformation mechanisms and induce martensitic transformation. By combining in situ synchrotron X-ray diffraction (XRD) tensile testing and post-mortem electron microscopy with density functional theory simulations, we gain precise insights into these phenomena. We find that the Fe18Cr10Ni (wt%) alloy, with its low SFE, exhibits higher stacking fault probability, deformation-induced martensitic transformation, and a lesser increase in dislocation density with plastic strain. In contrast, the Fe18Cr14Ni (wt%) alloy, with its higher SFE, shows enhanced deformation twinning and greater dislocation density with increasing strain. These findings from high-purity ternary alloys provide valuable insights that can guide the search for alternative elements to replace Ni while achieving similar effects on phase stability and deformation behavior.

36 MATERIALS SCIENCE↗

Potent Inhibition of E. coli DXP Synthase by a gem -Diaryl Bisubstrate Analog

New antimicrobial strategies are needed to address pathogen resistance to currently used antibiotics. Bacterial central metabolism is a promising target space for the development of agents that selectively target bacterial pathogens. 1-Deoxy- D -xylulose 5-phosphate synthase (DXPS) converts pyruvate and d-glyceraldehyde 3-phosphate ( D -GAP) to DXP, which is required for synthesis of essential vitamins and isoprenoids in bacterial pathogens. Thus, DXPS is a promising antimicrobial target. Toward this goal, our lab has demonstrated selective inhibition of Escherichia coli DXPS by alkyl acetylphosphonate (alkylAP)-based bisubstrate analogs that exploit the requirement for ternary complex formation in the DXPS mechanism. Here, we present the first DXPS structure with a bisubstrate analog bound in the active site. Insights gained from this cocrystal structure guided structure–activity relationship studies of the bisubstrate scaffold. A low nanomolar inhibitor (compound 8) bearing a gem-dibenzyl glycine moiety conjugated to the acetylphosphonate pyruvate mimic via a triazole-based linker emerged from this study. Compound 8 was found to exhibit slow, tight-binding inhibition, with contacts to E. coli DXPS residues R99 and R478 demonstrated to be important for this behavior. This work has discovered the most potent DXPS inhibitor to date and highlights a new role of R99 that can be exploited in future inhibitor designs toward the development of a novel class of antimicrobial agents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deciphering yield modification of hadron-triggered semi-inclusive recoil jets in heavy-ion collisions

Jet quenching is recognized as critical evidence for the existence of the quark-gluon plasma (QGP) and serves as an essential probe to study its transport properties. Measurements of hadron-triggered semi-inclusive recoil jets have gained popularity due to its capability to probe jets over an extended phase space at low transverse momenta (p T ) and large radii. Recent ALICE measurements showed that the I AA , yield ratio of recoil jets between heavy-ion and p+p collisions, rises with jet p T and exceeds unity at high p T , contradicting conventional expectations that jet quenching should result in I AA values less than one. In this contribution, we re-examine the surface bias and study the effects of energy losses for both trigger hadrons and recoil jets on I AA , employing the Linear Boltzmann Transport (LBT) model to simulate jet-medium interactions. Our findings suggest that a large portion of hadrons used for the triggers undergoes substantial energy loss, despite surface bias. In particular, the energy loss of the trigger hadrons elevates the I AA baseline, corresponding to the case of no energy loss for recoil jets, to be greatly larger than unity. This enhancement of the baseline implies that the measured I AA values being larger than unity could still signal jet quenching.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Regional Economic Impacts of the Los Angeles 100% Renewable Energy Transition

To help mitigate greenhouse gas (GHGs) generation from burning fossil fuels, many state and local governments are requiring utilities to dramatically increase the share of electricity generated from renewable sources. The City of Los Angeles has set a target of 100% renewable energy by 2045 and has formulated a plan that considers nine potential alternative scenarios that differ by technology, location, and timing. Each scenario has a unique set of local investments, operating and maintenance (O&M) costs, and concomitant rate structures. In this study we develop and apply a computable general equilibrium (CGE) model built specifically for LA to estimate and compare the economic impacts for each of the scenarios over time relative to a reference case. We find differences in economic impacts across scenarios, depending on the level and timing of investment and O&M expenditures, as well as differences in the relative rate changes across scenarios. Results show that employment and economic output are positively correlated with greater capital and O&M spending, while higher electricity rates can dampen economic activity. Several scenarios generate positive economic impacts relative to the reference case, showing that the transition need not have harmful economic impacts, and all scenarios generate a number of other positive co-benefits, such as reduced damage to health from the reduction of ordinary air pollutants. The net employment impacts from 2026 to 2045 across the scenarios range from a low of 3,600 job-year losses annually to 4,700 job-year gains, both around only 0.1% of the baseline average annual employment in the city over that period. The analysis also indicates that lower-income households are relatively more affected than others by the scenarios. Overall, even in the most negatively impactful case, the economic output and employment effects are quite small when taken in the context of the overall size of the regional economy and the large reduction in GHGs.

economic impact modeling↗

Codebase release 2.0 for sauce

Low energy nuclear physics experiments are transitioning towards fully digital data acquisition systems. Realizing the gains in flexibility afforded by these systems relies on equally flexible data reduction techniques. In this paper, methods utilizing data frames and in-memory techniques to work with data, including data from self-triggering, digital data acquisition systems, are discussed within the context of a Python package, sauce. It is shown that data frame operations can encompass common analysis needs and allow interactive data analysis. Two event building techniques, dubbed referenced and referenceless event building, are shown to provide a means to transform raw list mode data into correlated multi-detector events. These techniques are demonstrated in the analysis of two example data sets.

Marshall, Caleb (ORCID:0000000211942920)↗

Entropy-Assisted Quality Pattern Identification in Finance

Short-term patterns in financial time series form the cornerstone of many algorithmic trading strategies, yet extracting these patterns reliably from noisy market data remains a formidable challenge. In this paper, we propose an entropy-assisted framework for identifying high-quality, non-overlapping patterns that exhibit consistent behavior over time. We ground our approach in the premise that historical patterns, when accurately clustered and pruned, can yield substantial predictive power for short-term price movements. To achieve this, we incorporate an entropy-based measure as a proxy for information gain: patterns that lead to high one-sided movements in historical data yet retain low local entropy are more “informative” in signaling future market direction. Compared to conventional clustering techniques such as K-means and Gaussian Mixture Models (GMMs), which often yield biased or unbalanced groupings, our approach emphasizes balance over a forced visual boundary, ensuring that quality patterns are not lost due to over-segmentation. By emphasizing both predictive purity (low local entropy) and historical profitability, our method achieves a balanced representation of Buy and Sell patterns, making it better suited for short-term algorithmic trading strategies. This paper offers an in-depth illustration of our entropy-assisted framework through two case studies on Gold vs. USD and GBPUSD. While these examples demonstrate the method’s potential for extracting high-quality patterns, they do not constitute an exhaustive survey of all possible asset classes.

Physics↗

The Santorini Volcanic Complex as a Valuable Source of Enzymes for Bioenergy

Marine microbial communities are an untapped reservoir of genetic and metabolic diversity and a valuable source for the discovery of new natural products of biotechnological interest. The newly discovered hydrothermal vent field of Santorini volcanic complex located in the Aegean Sea is gaining increasing interest for potential biotechnological exploitation. The conditions in these environments, i.e., high temperatures, low pH values and high concentration of heavy metals, often resemble harsh industrial settings. Thus, these environments may serve as pools of enzymes of enhanced catalytic properties that may provide benefits to biotechnology. Here, we screened 11 metagenomic libraries previously constructed from microbial mat samples covering the seafloor and the polymetallic chimneys of Kolumbo volcano as well as mat samples from Santorini caldera, to mine, in silico, genes associated with bioenergy applications. We particularly focused on genes encoding biomass hydrolysis enzymes such as cellulases, hemicellulases and lignin-degrading enzymes. A total of 10,417 genes were found for three specific groups of enzymes—i.e., the endoglucanases, the three different beta-glucosidases BGL, bglX and bglB, and the alpha-galactosidases melA, and rafA. Overall, we concluded that the Santorini–Kolumbo volcanic ecosystems constitute a significant resource of novel genes with potential applications in bioenergy that deserve further investigation.

59 BASIC BIOLOGICAL SCIENCES↗

Low-Power Characterization and Integration of Carbon Black Resistive Ink for Aerosol Jet-Printed RF Components

Aerosol jet printing (AJP) is gaining attention in additive manufacturing research, especially in the discipline of microwave engineering. Currently, no reliable AJP method exists to fabricate resistors that are both electrically small and with a resistance compatible with waveguide impedances for use in microwave components. In this work, the commercially available Metalon JR-038 is characterized and used to fabricate a resistor that is 100 μ m long by 250 μ m wide for the first time to the best of our knowledge. Furthermore, this resistor was then used to fabricate a Ka-band Wilkinson power divider using only the AJP process.

36 MATERIALS SCIENCE↗

The North American Renewable Integration Study (NARIS): A U.S. Perspective

The North American electric power system is undergoing significant change, with renewable resources now contributing more generation than ever before. This transformation is poised to continue given decreasing technology costs and ambitious decarbonization goals at the federal, state, local, corporate, and consumer levels. The North American Renewable Integration Study (NARIS) aims to inform grid planners, utilities, industry, policymakers, and other stakeholders about challenges and opportunities for continental system integration of large amounts of wind, solar, and hydropower to support a low-carbon future grid. The National Renewable Energy Laboratory (NREL) conducted a detailed, continent-wide analysis with planning scenarios of transmission, generation, and demand to reach 80%–92% carbon reductions (from 2005) for the Canadian electric power system, and up to 80% reductions continent-wide. We used a suite of models to study future scenarios and gain insights, including potential impacts on costs, emissions, resource adequacy, and the specific technologies that help enable the transition to a low-carbon grid. Our analysis had a particular focus on the potential role of cooperation among the three North American countries and between regions within each country, and how transmission can support sharing of supply and demand diversity. The NARIS project began in 2016. This report describes a U.S. perspective in coordination with the U.S. Department of Energy, and a companion report describes a Canadian perspective in coordination with the Natural Resources Canada. NARIS was an extension of a previous body of work, including the Western Wind and Solar Integration Study, the Eastern Renewable Generation Integration Study, Interconnections Seam Study, and the Pan Canadian Wind Integration Study. NARIS analyzed the entire continent in detail while studying higher renewable generation than previous studies. The scenarios in NARIS were informed by the goals in the Mid-Century Strategies for the Paris Agreement in each country.

14 SOLAR ENERGY↗

The North American Renewable Integration Study (NARIS): A Canadian Perspective

The North American electric power system is undergoing significant change, with renewable resources now contributing more generation than ever before. This transformation is poised to continue given decreasing technology costs and ambitious decarbonization goals at the federal, state, local, corporate, and consumer levels. The North American Renewable Integration Study (NARIS) aims to inform grid planners, utilities, industry, policymakers, and other stakeholders about challenges and opportunities for continental system integration of large amounts of wind, solar, and hydropower to support a low-carbon future grid. The National Renewable Energy Laboratory (NREL) conducted a detailed, continent-wide analysis with planning scenarios of transmission, generation, and demand to reach 80%–92% carbon reductions (from 2005) for the Canadian electric power system, and up to 80% reductions continent-wide. We used a suite of models to study future scenarios and gain insights, including potential impacts on costs, emissions, resource adequacy, and the specific technologies that help enable the transition to a low-carbon grid. Our analysis had a particular focus on the potential role of cooperation among the three North American countries and between regions within each country, and how transmission can support sharing of supply and demand diversity. The NARIS project began in 2016. This report describes a Canadian perspective in coordination with the Natural Resources Canada, and a companion report describes a U.S. perspective in coordination with the U.S. Department of Energy. NARIS was an extension of a previous body of work, including the Western Wind and Solar Integration Study, the Eastern Renewable Generation Integration Study, Interconnections Seam Study, and the Pan Canadian Wind Integration Study. NARIS analyzed the entire continent in detail while studying higher renewable generation than previous studies. The scenarios in NARIS were informed by the goals in the Mid-Century Strategies for the Paris Agreement in each country.

14 SOLAR ENERGY↗

Boosting the signal-to-noise of low-field MRI with deep learning image reconstruction

Recent years have seen a resurgence of interest in inexpensive low magnetic field (< 0.3 T) MRI systems mainly due to advances in magnet, coil and gradient set designs. Most of these advances have focused on improving hardware and signal acquisition strategies, and far less on the use of advanced image reconstruction methods to improve attainable image quality at low field. We describe here the use of our end-to-end deep neural network approach (AUTOMAP) to improve the image quality of highly noise-corrupted low-field MRI data. We compare the performance of this approach to two additional state-of-the-art denoising pipelines. We find that AUTOMAP improves image reconstruction of data acquired on two very different low-field MRI systems: human brain data acquired at 6.5 mT, and plant root data acquired at 47 mT, demonstrating SNR gains above Fourier reconstruction by factors of 1.5- to 4.5-fold, and 3-fold, respectively. In these applications, AUTOMAP outperformed two different contemporary image-based denoising algorithms, and suppressed noise-like spike artifacts in the reconstructed images. The impact of domain-specific training corpora on the reconstruction performance is discussed. The AUTOMAP approach to image reconstruction will enable significant image quality improvements at low-field, especially in highly noise-corrupted environments.

42 ENGINEERING↗

Density Functional Theory Investigation of Oxidation Intermediates on Gold and Gold–Silver Surfaces

Gold and gold-silver alloys can be active and selective oxidation catalysts. Previous work has suggested that O 2 dissociation occurs at bimetallic step sites on gold-silver alloys, but the site responsible for the rest of the reaction steps has not been studied. As a first step in gaining insight into this issue, in this work we investigated the adsorption of oxygen and other oxidation intermediates on the (111) and (211) facets of gold-silver alloys using density functional theory. Oxygen and silver coverage effects were analyzed, and different model structures were compared. We also examined the energy barriers for the diffusion of atomic oxygen to gain insight into O migration and spillover. On (111) surfaces, O adsorption is much stronger at low O coverage (less than 0.22 ML), while on (211) surfaces O is strongly bound at both high and low O coverage. O diffusion across the step is faster than diffusion along the step. Ag stabilizes O, both when directly bound to it and when in an adjacent site. Ag also reduces repulsive O-O interactions at low O coverage. Our calculated reaction barriers for O-assisted CH 3 O dehydrogenation suggest that reaction is faster on steps than on terraces. Overall, our findings suggest that spillover of O from Ag-rich steps to Au-rich terraces does not occur, and that oxidation reactions on gold-silver alloys occurs on step sites. More specifically, oxidation likely occurs either on Ag-rich step sites or on Au-rich step sites that are adjacent to Ag-rich step sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spatial and chemical heterogeneity in aqueous Zn/MnO 2 batteries: role of Zn and Mn containing complexes

Aqueous Zn/MnO 2 batteries are a promising, safe alternative for grid-scale energy storage, owing to their environmentally safe and low-cost nature. The dissolution–deposition reaction mechanism in a mild aqueous pH regime has recently gained significance due to its relevance in battery design. Comprehending both the specific locations and the way reaction progresses is crucial for efficient batteries. This study demonstrates that Zinc Hydroxy Sulfate (ZHS) formed during discharge primarily near the dissolved MnO2 particles. Acting as a host for charge reactants in subsequent cycles, the charge product morphology was visualized using operando X-ray fluorescence microscopy. After ∼400 hours of cycling, capacity fade was linked to the formation of a Zn–Mn core–shell phase which is attributed to an irreversible core phase in the electrode, visualized through three-dimensional chemical mapping. Altogether, this research underscores the importance of understanding local morphological evolution in designing electrodes and chemistries for advanced grid-scale energy storage technologies.

36 MATERIALS SCIENCE↗

GRAPH — an readout ASIC for large MCP based detectors

We present a programmable 16 channel, mixed signal, low power readout ASIC, having the project historically named Gigasample Recorder of Analog waveforms from a PHotodetector (GRAPH). It is designed to read large aperture single photon imaging detectors using micro channel plates for charge multiplication, and measuring the detector's response on crossed strips anodes to extrapolate the incoming photon position. Each channel consists of a fast, low power and low noise charge sensitive amplifier, which provides a myriad of coarse and fine programmable options for gain and shaping settings. Further, the amplified signal is recorded using, to our knowledge novel, the Hybrid Universal sampLing Architecture (HULA) ADC. A kind of mixed signal double buffer memory, that enables concurrent waveform recording, and selected event digitized data extraction. The sampling frequency is freely adjustable between few kHz up to 125 MHz, while the chip's internal digital memory holds a history 2048 samples for each channel, with a digital headroom of 12 bits. An optimized region of interest sample-read algorithm allows to extract the information just around the event pulse peak, while selecting the next event, thus substantially reducing the operational dead time. The chip is designed in 130 nm TSMC CMOS technology, and its power consumption is around 47 mW per channel.

47 OTHER INSTRUMENTATION↗

Quantum metrology of low-frequency electromagnetic modes with frequency upconverters

We present the RF Quantum Upconverter (RQU) and describe its application to quantum metrology of electromagnetic modes between dc and the very high frequency band (VHF) ( ≲ 300 MHz). The RQU uses a Josephson interferometer made up of superconducting loops and Josephson junctions to implement a parametric interaction between a low-frequency electromagnetic mode (between dc and VHF) and a mode in the microwave C Band ( ∼ 5 GHz), analogous to the radiation pressure interaction between electromagnetic and mechanical modes in cavity optomechanics. We analyze RQU performance with quantum amplifier theory and show that the RQU can operate as a quantum-limited op-amp in this frequency range. It can also use nonclassical measurement protocols equivalent to those used in cavity optomechanics, including back-action evading (BAE) measurements, sideband cooling, and two-mode squeezing. These protocols enable experiments using dc VHF electromagnetic modes as quantum sensors with sensitivity better than the standard quantum limit (SQL). We demonstrate signal upconversion from low frequencies to the microwave C band using an RQU and show a phase-sensitive gain (extinction ratio) of 46.9 dB , which is a necessary step towards the realization of full BAE. Published by the American Physical Society 2025

Kuenstner, Stephen E. (ORCID:0000000346128846)↗

Low-threshold laser medium utilizing semiconductor nanoshell quantum dots

Colloidal semiconductor nanocrystals (NCs) represent a promising class of nanomaterials for lasing applications. Currently, one of the key challenges facing the development of high-performance NC optical gain media lies in enhancing the lifetime of biexciton populations. This usually requires the employment of charge-delocalizing particle architectures, such as core/shell NCs, nanorods, and nanoplatelets. Here, we report on a two-dimensional nanoshell quantum dot (QD) morphology that enables a strong delocalization of photoinduced charges, leading to enhanced biexciton lifetimes and low lasing thresholds. A unique combination of a large exciton volume and a smoothed potential gradient across interfaces of the reported CdS bulk /CdSe/CdS shell (core/shell/shell) nanoshell QDs results in strong suppression of Auger processes, which was manifested in this work though the observation of stable amplified stimulated emission (ASE) at low pump fluences. An extensive charge delocalization in nanoshell QDs was confirmed by transient absorption measurements, showing that the presence of a bulk-size core in CdS bulk /CdSe/CdS shell QDs reduces exciton–exciton interactions. Altogether, present findings demonstrate unique advantages of the nanoshell QD architecture as a promising optical gain medium in solid-state lighting and lasing applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BeyondPlanck: I. Global Bayesian analysis of the Planck Low Frequency Instrument data

We describe the BEYONDPLANCK project in terms of our motivation, methodology, and main products, and provide a guide to a set of companion papers that describe each result in more detail. Building directly on experience from ESA’s Planck mission, we implemented a complete end-to-end Bayesian analysis framework for the Planck Low Frequency Instrument (LFI) observations. The primary product is a full joint posterior distribution P(ω | d), where ω represents the set of all free instrumental (gain, correlated noise, bandpass, etc.), astrophysical (synchrotron, free-free, thermal dust emission, etc.), and cosmological (cosmic microwave background – CMB – map, power spectrum, etc.) parameters. Some notable advantages of this approach compared to a traditional pipeline procedure are seamless end-to-end propagation of uncertainties; accurate modeling of both astrophysical and instrumental effects in the most natural basis for each uncertain quantity; optimized computational costs with little or no need for intermediate human interaction between various analysis steps; and a complete overview of the entire analysis process within one single framework. As a practical demonstration of this framework, we focus in particular on low-ℓ CMB polarization reconstruction with Planck LFI. In this process, we identify several important new effects that have not been accounted for in previous pipelines, including gain over-smoothing and time-variable and non-1/f correlated noise in the 30 and 44 GHz channels. Modeling and mitigating both previously known and newly discovered systematic effects, we find that all results are consistent with the ΛCDM model, and we constrained the reionization optical depth to τ = 0.066 ± 0.013, with a low-resolution CMB-based χ 2 probability to exceed of 32%. This uncertainty is about 30% larger than the official pipelines, arising from taking a more complete instrumental model into account. The marginal CMB solar dipole amplitude is 3362.7 ± 1.4 μK, where the error bar was derived directly from the posterior distribution without the need of any ad hoc instrumental corrections. We are currently not aware of any significant unmodeled systematic effects remaining in the Planck LFI data, and, for the first time, the 44 GHz channel is fully exploited in the current analysis. We argue that this framework can play a central role in the analysis of many current and future high-sensitivity CMB experiments, including LiteBIRD, and it will serve as the computational foundation of the emerging community-wide COSMOGLOBE effort, which aims to combine state-of-the-art radio, microwave, and submillimeter data sets into one global astrophysical model.

79 ASTRONOMY AND ASTROPHYSICS↗