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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Phase transitions at unusual values of θ

We calculate the θ dependence in a cousin of QCD, where the vacuum structure can be analyzed exactly. The theory is $\mathcal{N}$ = 2 SU(2) gauge theory with N F = 0, 1, 2, 3 flavors of fundamentals, explicitly broken to $\mathcal{N}$ = 1 via an adjoint superpotential, and coupled to anomaly mediated supersymmetry breaking (AMSB). The hierarchy m AMSB ≪ μ 𝒩=1 ≪ Λ ensures the validity of our IR analysis. As expected from ordinary QCD, the vacuum energy is a function of θ which undergoes 1st order phase transitions between different vacua where the various dyons condense. For N F = 0 we find the expected phase transition at θ = π, while for N F = 1, 2, 3 we find phase transitions at fractional values of π.

Extended Supersymmetry↗
DOE OSTI2025

Characterization of Recrystallized Grains During Static Recrystallization of Hot-Compressed Mg–Zn–Ca Alloys Using In Situ Far-Field High-Energy Diffraction Microscopy

In this study, we explored the effect of Zn content on the static recrystallization of three 80 pct hot-compressed alloys, Mg–0.5Zn–0.1Ca wt pct (ZX050), Mg–1Zn–0.1Ca wt pct (ZX10), and Mg–3.2Zn–0.1Ca wt pct (ZX30), using far-field high-energy microscopy (ff-HEDM). Individual recrystallized grains were tracked and their 3D centroid, relative volume, and grain-averaged crystallographic orientation were measured during annealing. These measurements were used to compare the recrystallization kinetics and texture evolution of recrystallized grains in ZX alloys as a function of the Zn content. Fully recrystallized microstructures were observed for the ZX30 and the ZX10 alloys after annealing at 230 °C and 330 °C, respectively. In contrast, only a partially recrystallized microstructure for the ZX050 alloy was observed after > 1 hour of annealing at 430 °C. The resistance to recrystallization with decreasing Zn content was also confirmed by detecting faster growth rates of recrystallized grains in the ZX10 and ZX30 alloys, and slower growth rates in the ZX050 alloy. The significant recrystallization texture weakening of the ZX10 and ZX30 alloys and the development of a basal texture in the ZX05 alloy were described based on the orientation dependency of nucleation and growth of recrystallized grains. The analysis demonstrated that texture weakening was associated with increasing Zn content in Mg–Zn–Ca alloys.

Roumina, Reza [Univ. of Michigan, Ann Arbor, MI (U↗
DOE OSTI2026

Adaptive Sampling-Based Bi-Fidelity Stochastic Trust Region Method for Stochastic Derivative-Free Optimization

Bi-fidelity stochastic optimization has gained increasing attention as an efficient approach to reduce computational costs by leveraging a low-fidelity (LF) model to optimize an expensive high-fidelity (HF) objective. In this paper, we propose ASTRO-BFDF, an adaptive sampling trust-region method specifically designed for unconstrained bi-fidelity stochastic derivative-free optimization problems. In ASTRO-BFDF, the LF function serves two purposes: (i) to identify better iterates for the HF function when the optimization process indicates a high correlation between them and (ii) to reduce the variance of the HF function estimates using bi-fidelity Monte Carlo (BFMC). The algorithm dynamically determines sample sizes while adaptively choosing between crude Monte Carlo and BFMC to balance the trade-off between optimization and sampling errors. We prove that the iterates generated by ASTRO-BFDF converge to a first-order stationary point almost surely. Additionally, we demonstrate the effectiveness of the proposed algorithm through numerical experiments on synthetic benchmarks and simulation optimization problems involving discrete event systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Spectral distortions to momentum and scalar exchanges by non-turbulent motion and patchy landscape variability

Modifications to the spectra of turbulent velocity and scalars and co-spectra of vertical fluxes of momentum and scalars due to patchy landscape heterogeneity and non-stationarity are explored for a Mediterranean ecosystem. About 9 months of high frequency measurements of the three velocity components, water vapor concentration, carbon dioxide concentration, and air temperature were analyzed for different seasons (spring/summer) and prevalent wind directions (southeast/northwest). The two wind directions sampled a contrast of clumped and patchy landscape comprised of olive trees (southeast) and wall bounded flow disturbed by the presence of few upwind trees (northwest). The measured spectra and co-spectra were also compared to theoretical scaling forms from stationary, planar homogeneous flow, in the absence of subsidence as derived from the Kansas experiment. To assess the role of low frequency non-turbulent motion on the spectral and co-spectral content, a 5-min Fourier cutoff was introduced and the analysis was limited to near-neutral conditions where the boundary layer depth is shallow compared to its unstable counterpart. It was shown that the velocity statistics were not appreciably impacted by the low-frequency motion causing non-stationarity. Moreover, the turbulent scalar fluxes were also shown not to be significantly impacted by such low frequency motion. The scalar variances were impacted, especially the water vapor variance and its concomitant spectral shape. When the non-turbulent motion was filtered, the scalar spectra at low wavenumbers followed expectations from the so-called attached eddy hypothesis (i.e. exhibited a $k^{-1}_x$ scaling with $k_x$ defining the longitudinal wavenumber) applicable for near-neutral conditions. For momentum co-spectra, the canonical shapes from the Kansas experiment appear to describe well the measurements here and in both dominant directions and seasons with some adjustment to the integral time scales based on wind direction. For the scalar co-spectra, deviations from the Kansas experiment were prevalent. The most noticeable and surprising deviations were their slow decay with increased sampling frequency at inertial subrange scales. This slow decay was shown not to contribute appreciably to the overall scalar fluxes. At those fine scales, predictions from local isotropy were expected to hold. The scalar co-spectral deviations from local isotropy were then discussed using a simplified co-spectral budget model where scalar–scalar co-spectra naturally emerged and the interplay between landscape heterogeneity and a scale-dependent pressure-scalar de-correlation time was postulated. It is also envisaged that the findings here offer a preliminary template for analyzing eddy-covariance data in situations that deviate from ideal conditions, especially regarding low-frequency modulations of scalar spectra and vertical scalar flux co-spectra.

Canopy turbulence↗
DOE OSTI2020

Molecular Transducers of Physical Activity Consortium (MoTrPAC): Mapping the Dynamic Responses to Exercise

Exercise provides a robust physiological stimulus that evokes cross-talk between a wide range of tissues via hormonal, cellular and molecular signals that when repeated regularly over time (i.e., training) improves physiological capacity, benefits numerous organ systems and decreases the risk for premature mortality. In spite of its fundamental importance, a gap remains in identifying the detailed molecular signals and responses to exercise and its benefits for health and disease prevention. To further knowledge in this emerging area, the Molecular Transducers of Physical Activity Consortium (MoTrPAC) was established to generate a molecular map of the effects of acute and chronic exercise. MoTrPAC investigators are conducting preclinical and clinical studies to better understand the systemic effects of exercise across multiple tissues. The preclinical studies were performed on more than 700 rats with the analysis of twenty or more organs per rat. The clinical study involves a large cohort of ~2600 individuals with a range of ages and fitness levels (untrained, trained, highly trained) who will be evaluated physiologically and by molecular probing of blood, muscle and adipose tissues before and after acute and chronic endurance or resistance exercise. Multi-omic analyses (genomics, epigenomics, transcriptomics, proteomics and metabolomics/lipidomics) will be performed followed by state-of-the-art bioinformatics to create a molecular map of exercise. This mapping project will provide a public database that is expected to enhance our understanding of the health benefits of physical activity in many organ systems and potentially provide insight into mitigating diseases through activity.

Sanford, James A.↗
DOE OSTI2025

Mucus-derived glycans are inhibitory signals for Salmonella Typhimurium SPI-1-mediated invasion

Mucus forms a critical barrier against enteric pathogens like Salmonella enterica serovar Typhimurium. While in vivo studies indicate that secreted, gel-forming mucins and specifically core 3 glycosylation are protective against S. Typhimurium, the molecular mechanisms involved remain unclear. Here, we demonstrate that native intestinal mucins inhibit Salmonella invasion of colonic epithelial cells by downregulating the type 3 secretion system through suppression of the key virulence regulator, HilD. Our study identifies mucin glycans and specific mucin sugars, namely N-acetyl galactosamine and N-acetyl glucosamine, as the components responsible for mucin’s anti-virulence effect, likely via functional or direct interaction with HilD’s putative carbohydrate-binding domain. Notably, we find that the native presentation of these sugars is important for activity. These insights provide a mechanistic foundation for mucin-based strategies to combat enteric infections and, given the prevalence of homologous AraC-type regulators in other pathogens, suggest mucins’ potential as broad-spectrum anti-virulence agents.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Development of an interatomic potential for the Ta–Li system

A new interatomic potential for the Ta–Li system is introduced to facilitate the study of phase stability, mechanical properties and non-equilibrium dynamics after Li implantation in Ta. Here, this potential is based on a generalization of the embedded atom method (GEAM) and includes contributions from embedding energy, explicit two- and three-body interactions, and nonlocal many-body interaction terms. The parameters of the potential are optimized using energies and atomic forces for a wide range of configurations obtained from ab initio density functional theory (DFT) calculations. The potential is rigorously validated across a range of physical properties, including elastic constants, equations of state, phonon dispersion curves, point defect properties, and melting temperatures for different compositions. Although our potential is trained on a small dataset, its accuracy is comparable to that of available machine learning potentials for Li and Ta. Our simulations show that at temperatures below 500 K, Li atoms in Ta–Li alloys form clusters separated by Ta-rich domains, and we find no evidence of ordered phase formation. For Li concentrations below a few percent, Li atoms preferentially segregate to surfaces and grain boundaries. However, in alloys containing more than ~10% Li, the accumulation of Li in symmetric-tilt grain boundaries can lead to one of the following effects: formation of amorphous-like regions, changes in grain boundary structural units, or lateral movement of the grain boundary.

GEAM potential↗
DOE OSTI2026

Discovery of additional ancient genome duplications in yeasts

Whole-genome duplication (WGD) has had profound macroevolutionary impacts on diverse lineages, preceding adaptive radiations in vertebrates, teleost fish, and angiosperms. In contrast to the many known ancient WGDs in animals, and especially plants, we are aware of evidence for only four WGDs in fungi. The oldest of these occurred ∼100 million years ago (mya) and is shared by ∼60 extant Saccharomycetales species, including the baker’s yeast Saccharomyces cerevisiae. Notably, this is the only known ancient WGD event in the yeast subphylum Saccharomycotina. The dearth of ancient WGD events in fungi remains a mystery. Some studies have suggested that fungal lineages that experience chromosome and genome duplication quickly go extinct, leaving no trace in the genomic record, while others contend that the lack of known WGDs is due to an absence of data. Under the second hypothesis, additional sampling and deeper sequencing of fungal genomes should lead to the discovery of more WGD events. Coupling hundreds of recently published genomes from nearly every described Saccharomycotina species, with three additional long-read assemblies, we discovered three novel WGD events. Although the functions of retained duplicate genes originating from these events are broad, they bear similarities to the well-known WGD that occurred in the Saccharomycetales. In conclusion, our results suggest that WGD may be a more common evolutionary force in fungi than previously believed.

convergent evolution↗
DOE OSTI2026

Interactive effects of precipitation, temperature, and grazing pressure on the net ecosystem carbon balance of grazing lands across the continental United States

Grazing lands cover approximately one-third of the contiguous United States, support much of the nation's beef production, and are an important component of the U.S. terrestrial carbon budget. In this study, we quantified net ecosystem carbon balance (NECB), the net status of grazing lands as a carbon sink (C-sink) or source (C-source) and a key determinant of soil health and productivity. Our primary objective was to synthesize multiple years of annual NECB across heterogeneous grazing lands across the continental U.S and evaluate annual NECB against physical drivers (mean annual precipitation (MAP), mean annual temperature (MAT), vegetation, and moisture condition) and management practices (grazing pressure index (GPI) and fertilization history). We hypothesized that (1) NECB is higher in mesic and fertilized grasslands; (2) NECB increases with MAP and MAT but decreases with GPI; and (3) interactive effects exist among MAP, MAT, and GPI. Using carbon fluxes measured by eddy covariance towers and methane emissions including both enteric methane and manure derived from stocking rates across seven USDA Long-term Agroecosystem Research Network sites, we found: (1) grazing lands were a C-sink or carbon neutral at most sites; (2) vegetation type, moisture conditions, or fertilization had no significant effect on NECB; (3) NECB increased with MAP and MAT, but decreased with a higher GPI; and (4) MAT had a significant positive effect on NECB when MAP exceeded 750 mm (greater water availability). The effect of GPI on NECB was significantly negative when MAP was below 1000 mm, significantly negative when MAT < 12 °C and significantly positive when MAT > 16 °C. Thus, most grazing lands in our study acted as C-sinks unless water deficit, low temperature, or heavy grazing were interactively present. Understanding how climate and management influence NECB of grazing lands is key to maintaining resilient agroecosystems that secure beef production and sustain rural prosperity.

LTAR↗
DOE OSTI2026

The relative influences of hydrologic information and dams’ hydropower scheduling decisions on electricity price forecasts

Price dynamics in wholesale electricity markets are driven by supply and demand. In markets with hydroelectric dams, the timing and amount of hydropower offered can influence prices in similar ways to wind and solar power. Unlike variable renewable energy, however, the supply of hydropower in wholesale markets is a function of both water availability and operational decisions at dams. Dam operators maximize revenues in wholesale markets by aligning generation with the periods of highest expected prices, and these scheduling decisions may in turn influence prices. Here, we examine the relative importance of two types of information in predicting forward electricity prices: a) water availability at dams, in the form of short-to-medium-range hydrological forecasts; and b) hourly scheduling decisions at dams. Using softly coupled hydrologic, hydropower scheduling, and power systems models spanning the U.S. Western Interconnection, we quantify the importance of hydrologic forecast accuracy in correctly predicting wholesale electricity prices and compare this with the influence of dam operators’ own hourly scheduling decisions on realized market prices. We find that aligning hydropower generation schedules with the periods of high forecasted prices causes larger, inadvertent price forecast errors than imperfect hydrologic forecasts. This suggests that knowledge of how water is managed by dam operators within the week is more important than weekly inflow forecast errors when predicting forward electricity prices. Our findings have implications for optimal hydropower scheduling by region. Specifically, accounting for price effects is critical in markets dominated by hydropower capacity.

Electricity markets↗
DOE OSTI2023

Low-temperature oxidation pathways are critical to thermal incineration of PFAS-laden materials

With growing desire to destroy per- and poly-fluoroalkyl substances (PFAS) now known to be detrimental to human health, a sound understanding of fluorocarbon combustion chemistry is important to efficient thermal destruction within incinerators. While most fluorocarbon combustion models and the sets of reactions contained within them were originally developed for the high temperatures encountered in flame suppression applications, they have often been used to assess PFAS destruction in incinerators, which emphasize a lower range of temperatures. We present results that demonstrate that low-temperature fluorocarbon oxidation pathways—not yet known to play a role in fluorocarbon combustion—impact key incinerator performance metrics, including: PFAS surrogate mole fractions, products of incomplete destruction, and waste destruction efficiencies. The results further point to the utility of NO as a potential additive. The present results show the influence of these pathways for CF 3 O 2 , for which some data are available, but analogous pathways would also occur for other fluoroalkylperoxy radicals, for which little is known. Furthermore, the results demonstrate the need for future work to identify and characterize low-temperature pathways more generally, consider such pathways in kinetic model development, and experimentally probe intermediate temperature conditions to better understand, design, and control thermal destruction technologies for improved PFAS management.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Wide-Scale Clinical Implementation of Knowledge-Based Planning: An Investigation of Workforce Efficiency, Need for Post-automation Refinement, and Data-Driven Model Maintenance

Our purpose was to investigate the effect of automated knowledge-based planning (KBP) on real-world clinical workflow efficiency, assess whether manual refinement of KBP plans improves plan quality across multiple disease sites, and develop a data-driven method to periodically improve KBP automated planning routines.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Large language models for transportation research: Methodologies, state of the art, and future opportunities

The rapid rise of large language models (LLMs) is transforming transportation research, with significant advancements emerging between 2023 and 2025, a period marked by the inception and swift growth of adopting and adapting LLMs for various transportation applications. Despite these significant advancements, however, a systematic review and synthesis of the existing literature remains lacking. This paper aims to fill this gap by providing a comprehensive review of the methodologies and applications of LLMs in transportation. We explore key applications, including autonomous driving, travel behavior prediction, and general transportation-related queries, alongside LLM methodologies such as zero- or few-shot learning, prompt engineering, and fine-tuning. From the review, critical research gaps are identified. From the methodological perspective, many of the research limitations can be addressed by integrating LLMs with existing tools and refining LLM architectures. From the application perspective, research opportunities for LLMs to address various transportation challenges are also explored. By synthesizing these findings, this review not only presents the state-of-the-art LLM adoption and adaptation in transportation, but also proposes future research directions as well as insights and recommendations for policymakers and practitioners, paving the way for greater LLM-driven research innovations in transportation in the future.

42 ENGINEERING↗
DOE OSTI2025

DOME: Directional medical embedding vectors from Electronic Health Records

Motivation: The increasing availability of Electronic Health Record (EHR) systems has created enormous potential for translational research. Recent developments in representation learning techniques have led to effective large-scale representations of EHR concepts along with knowledge graphs that empower downstream EHR studies. However, most existing methods require training with patient-level data, limiting their abilities to expand the training with multi-institutional EHR data. On the other hand, scalable approaches that only require summary-level data do not incorporate temporal dependencies between concepts. Methods: We introduce a DirectiOnal Medical Embedding (DOME) algorithm to encode temporally directional relationships between medical concepts, using summary-level EHR data. Specifically, DOME first aggregates patient-level EHR data into an asymmetric co-occurrence matrix. Then it computes two Positive Pointwise Mutual Information (PPMI) matrices to correspondingly encode the pairwise prior and posterior dependencies between medical concepts. Following that, a joint matrix factorization is performed on the two PPMI matrices, which results in three vectors for each concept: a semantic embedding and two directional context embeddings. They collectively provide a comprehensive depiction of the temporal relationship between EHR concepts. Results: We highlight the advantages and translational potential of DOME through three sets of validation studies. First, DOME consistently improves existing direction-agnostic embedding vectors for disease risk prediction in several diseases, for example achieving a relative gain of 5.5% in the area under the receiver operating characteristic (AUROC) for lung cancer. Second, DOME excels in directional drug-disease relationship inference by successfully differentiating between drug side effects and indications, correspondingly achieving relative AUROC gain over the state-of-the-art methods by 10.8% and 6.6%. Finally, DOME effectively constructs directional knowledge graphs, which distinguish disease risk factors from comorbidities, thereby revealing disease progression trajectories. The source codes are provided at https://github.com/celehs/Directional-EHRembedding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Bundling measures for food systems transformation: a global, multimodel assessment

Background Current food systems leave one in ten individuals at risk of hunger while driving unsustainable environmental impacts. Inaction risks further exacerbating negative impacts on both human and planetary health. These challenges emerge from complex system interactions, requiring approaches that engage with this complexity and consider how transformation measures interact across food systems. We aimed to quantify the magnitude and uncertainty of the impacts of key food systems transformation measures both individually and in a bundle using an ensemble of global economic models. Methods In this global multimodel assessment, we applied an ensemble of ten state-of-the-art global economic models to evaluate the potential of four key measures in transforming food systems: increasing agricultural productivity, halving food loss and waste, shifting towards healthier diets, and economy-wide climate mitigation policies aligned with limiting warming to 1·5°C. The scenarios used a middle-of-the-road shared socioeconomic pathway for population and gross domestic product growth, climate impact data from Jägermeyr and colleagues, Thornton and colleagues, and Nelson and colleagues, and dietary targets based on the EAT–Lancet healthy reference diet, with model simulations conducted from 2020 to 2050. We then assessed the effect of these measures in isolation and in combination in a bundled scenario. To further understand the interactions between these measures, we conducted a decomposition analysis that distinguishes between the individual effects of a measure (effect when implemented alone), total effects (its contribution within the bundle), and interaction effects (the difference between total and individual effects). This approach aimed to show complementarities and trade-offs that emerge when multiple measures are implemented simultaneously. Findings Our analysis showed that individual measures in isolation are insufficient to achieve high-level environmental objectives and might generate unintended consequences. In contrast, bundling measures produces co-benefits: avoiding 50% of projected agricultural greenhouse gas emissions by 2050 and almost 20% of anticipated land conversion, while moderating food price increases associated with ambitious climate change mitigation policies. Our decomposition analysis further shows that measures can have varying effects across different dimensions. Although dietary shifts and climate mitigation policies are the largest drivers of environmental benefits (each contributing to a median decline of >10 percentage points in non-CO 2 emissions and 5 percentage points in agricultural land use globally), productivity improvements and reducing food loss and waste play essential roles in moderating price increases (each contributing to a median decline of >5 percentage points in average prices). Interpretation This study highlights the importance of implementing coordinated approaches to food system transformation and climate change mitigation rather than relying on isolated interventions. Comprehensive transformation requires understanding how supply-side and demand-side changes can interact with climate mitigation policies, enabling policy makers to design intervention packages that maximise benefits while minimising trade-offs across environmental, economic, and social dimensions.

Sundiang, Marina [Cornell Univ., Ithaca, NY (Unite↗
DOE OSTI2025

Are quantum materials economically and environmentally sustainable?

Quantum materials have revolutionized energy, information, and healthcare technologies, yet their development has largely prioritized performance over economic and environmental impacts—key factors for industrial adoption. Using topological materials as a case study, we present a data-driven framework that evaluates over 16,000 materials based on cost, supply chain resilience, energy demand, toxicity, and environmental footprint. By integrating the recently proposed quantum weight – a metric quantifying quantum behavior – we reveal a striking trend: materials with stronger quantum effects often exhibit higher environmental impact, posing challenges for scalability and industrial adoption. To address this, we identify a small set of materials that achieve a balance between quantum functionality and sustainability. Furthermore, our approach enables high-throughput, AI-driven materials discovery that incorporates economic and environmental influences from the outset, guiding the development of quantum materials for next-generation microelectronics and energy harvesting technologies.

AI↗
DOE OSTI2026

The incommensurate modulation of tetragonal tungsten bronze quantified by high resolution 4D STEM

Many members of the tetragonal tungsten bronze (TTB) family of oxides display an incommensurate periodic lattice distortion, the nature of which has been the subject of some controversy. Here we present a study of this structural modulation in the relaxor ferroelectric Ba 5 SmSn 3 Nb 7 O 30 (BSSN) by quantitative scanning transmission electron microscopy (STEM). Additionally, we characterize the modulation in BSSN by employing a fast, pixelated direct electron detector to perform high resolution phase contrast STEM imaging of the crystalline lattice. By quantitatively analyzing the images, we visualize the atomic structural correlations present in the material on both the cation and anion sublattices. This analysis reveals the incommensurate structure to have an octahedral tilting pattern and cooperative A2 site cation displacements, analogous to an Ama2 commensurate cell. Finally, we show that the modulation is composed of a structural motif with a period of 3 x $d_{1\bar{1}0}$ and modified by discommensurations, likely arise from frustrated octahedral tilting in the odd-valued periodicity.

Differential phase contrast↗
DOE OSTI2025

Measurements of a LYSO crystal array from threshold to 100 MeV

We report measurements of ten custom-made high-homogeneity LYSO crystals. The investigation is motivated by the need for a compact, high-resolution, and fast electromagnetic calorimeter for a new rare pion decay experiment. Each 2.5 x 2.5 x 18 cm 3 crystal was first characterized for general light yield properties and then its longitudinal response uniformity and energy resolution were measured using low-energy gamma sources. The ten crystals were assembled as an array and subjected to a 30–100 MeV positron beam with excellent momentum definition. The energy and timing resolutions were measured as a function of energy, and the spatial resolution was determined at 70 MeV. An additional measurement using monoenergetic 17.6 MeV gammas produced through a p-Li resonance was later made after the photosensors used in positron testing were improved. Here, as an example of the results, the energy resolution at 70 MeV of (1.52 ± 0.03) % is more than two times better than reported results using previous generation LYSO crystals.

Electromagnetic calorimeter↗