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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Combined molecular and spin dynamics simulation of BCC iron with vacancy defects

Utilizing an atomistic computational model, which handles both translational and spin degrees of freedom, combined molecular and spin dynamics simulations have been performed to investigate the effect of vacancy defects on spin wave excitations in ferromagnetic iron. Fourier transforms of space- and time-displaced correlation functions yield the dynamic structure factor, providing characteristic frequencies and lifetimes of the spin wave modes. A comparison of the system with a 5% vacancy concentration with pure lattice data shows a decrease in frequency and a decrease in lifetime for all transverse spin wave excitations observed. In addition, the clearly defined transverse spin wave excitations are distorted with the introduction of vacancy defects, and we observe reduced excitation lifetimes due to increased magnon–magnon scattering. We observe further evidence of increased magnon–magnon scattering, as the peaks in the longitudinal spin wave spectrum become less distinct. Finally, similar impacts are observed in the vibrational subsystem, with a decrease in characteristic phonon frequency and flattening of lattice excitation signals due to vacancy defects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The XPS of pyridine: A combined theoretical and experimental analysis

A detailed analysis of the N(1s) and C(1s) X-Ray Photoelectron Spectroscopy (XPS) is made, where the measured XPS is compared with theoretical Sudden Approximation (SA) intensities and theoretical XPS Binding Energies (BEs). There is remarkably good agreement between the theoretical predictions and the measured XPS; in particular, the different full width at half maximum values for the C(1s) and N(1s) BEs are explained in terms of unresolved C(1s) BEs for the different C atoms in pyridine. Here, this work demonstrates that the combination of theory and XPS measurements can extract analysis of the XPS relevant to the molecular electronic structure. The theory used is based on fully relativistic self-consistent field solutions of the Dirac–Coulomb Hamiltonian, and the SA is used to determine relative XPS intensities.

Binding Energies (BEs)↗
DOE OSTI2025

Elephant range and population, strontium isotopes, and genetics combine to give local-scale specificity to ivory hotspot tracking

We use Sr isotopes to increase the precision of DNA-based origin estimates of wildlife products. Population information is used to develop Sr isotope Elephant Polygons that are overlaid onto the region of origin identified by DNA assignment to determine the sources of seized ivory samples. Our approach is cognizant of isotope mixing due to isotope turnover within animals and also of the large home range of elephants or other mobile species. Genetic information from 3 different law enforcement ivory seizures suggests a region of origin confined to Kenya and Tanzania in eastern Africa. We determine characteristic 87 Sr/ 86 Sr ratios for each of 25 different Elephant Polygons within this region using analyses of more the 600 known-origin reference samples. Using both the 87 Sr/ 86 Sr ratios of the seized ivory samples and elephant population estimates from individual Elephant Polygons we find that at least 75 % of the samples likely came from a single Elephant Polygon which includes the Tsavo National Parks in Kenya and the Mkomazi National Park in Tanzania. A few samples may have come from other regions, most likely from Tanzania. This study illustrates the value of combining genetics, isotope geochemistry, and population surveys in wildlife forensics studies.

Africa↗
DOE OSTI2025

Using the optimal combined index weight ratio to improve the probability of anomaly detection in big area additive manufacturing

Big Area Additive Manufacturing (BAAM) of composites requires significant time, energy, and material, so it is critical to reduce production inefficiencies to make functional parts without multiple iterations. Statistical process control coupled with Principal Component Analysis (PCA) is a powerful technique that provides a quick, computationally inexpensive, and intuitive way for operators to detect defects that form in a manufacturing process without massive datasets. Recently, a combined index that is a weighted sum of the Hotelling's T 2 and squared residual error statistics has been proposed that can be monitored in one chart, improving interpretation accuracy and simplicity. However, the literature does not offer a formal method to optimise the weights. Here, we introduce two new approaches to the traditional weight selection approach using simulated and BAAM image data. Approach 1 uses a theoretically motivated optimum inspired by probabilistic principal component analysis. Approach 2 systematically varies the ratio of the weights to find the optimum. We show that approach 1 delivers optimal anomaly detection performance in select cases while approach 2 fares better in practice. Surprisingly, we also show that choosing a more complex PCA model has a minimal negative impact on anomaly detection performance compared to a more simplistic model.

3-dimensional printing↗
DOE OSTI2026

Combination of searches for nonresonant Higgs boson pair production in proton–proton collisions at $\sqrt{s}$ = 13 TeV

This paper presents a combination of searches for the nonresonant production of Higgs boson pairs (HH) in proton–proton collisions at a centre-of-mass energy of 13 TeV. The dataset was collected by the CMS experiment at the LHC from 2016 to 2018 and corresponds to a total integrated luminosity of 138 fb –1 . The observed (expected) upper limit on the inclusive HH production cross-section relative to the standard model (SM) prediction is found to be 3.5 (2.5). Assuming all other Higgs boson couplings are equal to their SM values, the Higgs boson trilinear self-coupling modifier κ λ = λ 3 /λ$^{SM}_{3}$ is constrained in the range –1.35 ≤ κ λ ≤ 6.37 at 95% confidence level (CL). Similarly, for the coupling modifier κ 2V , which governs the interactions between two vector bosons and two Higgs bosons, we have excluded κ 2V = 0 at more than five standard deviations for all values of κ λ . At 95% CL, assuming that the other couplings are equal to their SM values, κ 2V is constrained in the range 0.64 ≤ κ 2V ≤ 1.40. This work also investigates HH production in several new physics scenarios, using the Higgs effective field theory (HEFT) framework. The HEFT framework is further exploited to study various ultraviolet complete models with an extended Higgs sector and set constraints on specific parameters. An extrapolation of the results in the expected integrated luminosity following the high-luminosity upgrade of the LHC is also reported.

BSM↗
DOE OSTI2026

Understanding polaronic transport in complex oxides by combining precise synthesis and first-principles many-body theory

In complex oxides, charge carriers often couple strongly with lattice vibrations to form polarons–entangled electron–phonon quasiparticles whose transport properties remain difficult to characterize. Experimental access to intrinsic polaronic transport requires ultraclean samples, while theoretical description demands methods beyond low-order perturbation theory. Here, we show a predictive theory–experiment workflow to study polaron transport in complex oxides. Focusing on a prototypical polaronic oxide, anatase TiO 2 , we combine growth of high-quality oxygen-vacancy-doped films using hybrid molecular beam epitaxy with a first-principles electron–phonon diagrammatic Monte-Carlo (FEP-DMC) framework recently developed for accurate polaron predictions. Our films exhibit record-high electron mobility for anatase TiO 2 , in excellent agreement with FEP-DMC calculations conducted prior to experiment, which predict a room-temperature mobility of 45 ± 15 cm −2 V −1 s −1 and a mobility-temperature scaling of μ ∝ T −1.9 ± 0.077 . Microscopic analysis using scanning transmission electron microscopy and x-ray photoelectron spectroscopy reveals the role of oxygen vacancies in modulating transport at lower temperatures. FEP-DMC further provides quantitative insight into polaron formation energy, phonon cloud distribution, lattice distortion around the polaron, and the polaronic contribution to mobility. Together, these results provide a deeper microscopic understanding of large-polaron transport in a complex oxide and provide the blueprint to characterize other polaronic materials.

anatase TiO2↗
DOE OSTI2025

Combining physics-based and data-driven models for quantitatively accurate plasma profile prediction that extrapolates well; with application to DIII-D, AUG, and ITER tokamaks

For design, scenario planning, and control, ITER and all other envisioned tokamaks rely on a variety of statistical and physics-based models to extrapolate to unseen regimes; most notably from low plasma current to high. A 'meta-learning' methodology for combining the accuracy of data-driven models with the generalizability of physics-based models is described and tested, yielding a 5–10 percent improvement in performance beyond either alone for the task of extrapolating time-dependent plasma profile prediction from low- to high- plasma current DIII-D tokamak discharges. Meanwhile, it is shown that both machine learning models extrapolated far-distribution and state-of-the-art 'physics-based' profile predictors fare worse than merely assuming plasma profiles do not change from their initial values. Finally, a variety of other mechanisms for helping data-driven models generalize—transfer learning, adding contextual information from physics simulators, and adding data from the ASDEX Upgrade tokamak—are attempted for similar extrapolation tasks but, in the methodology used in this paper, yield no significant improvement beyond simple data-driven models. Results are summarized in figures 15 and 16.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Graph-learning approach to combine multiresolution seismic velocity models

SUMMARY The resolution of velocity models obtained by tomography varies due to multiple factors and variables, such as the inversion approach, ray coverage, data quality, etc. Combining velocity models with different resolutions can enable more accurate ground motion simulations. Toward this goal, we present a novel methodology to fuse multiresolution seismic velocity maps with probabilistic graphical models (PGMs). The PGMs provide segmentation results, corresponding to various velocity intervals, in seismic velocity models with different resolutions. Further, by considering physical information (such as ray path density), we introduce physics-informed probabilistic graphical models (PIPGMs). These models provide data-driven relations between subdomains with low (LR) and high (HR) resolutions. Transferring (segmented) distribution information from the HR regions enhances the details in the LR regions by solving a maximum likelihood problem with prior knowledge from HR models. When updating areas bordering HR and LR regions, a patch-scanning policy is adopted to consider local patterns and avoid sharp boundaries. To evaluate the efficacy of the proposed PGM fusion method, we tested the fusion approach on both a synthetic checkerboard model and a fault zone structure imaged from the 2019 Ridgecrest, CA, earthquake sequence. The Ridgecrest fault zone image consists of a shallow (top 1 km) high-resolution shear-wave velocity model obtained from ambient noise tomography, which is embedded into the coarser Statewide California Earthquake Center Community Velocity Model version S4.26-M01. The model efficacy is underscored by the deviation between observed and calculated traveltimes along the boundaries between HR and LR regions, 38 per cent less than obtained by conventional Gaussian interpolation. The proposed PGM fusion method can merge any gridded multiresolution velocity model, a valuable tool for computational seismology and ground motion estimation.

Geochemistry & Geophysics↗
DOE OSTI2025

Tiny Bubbles: Combined HR(S)TEM and 4D-STEM Analysis of Sub-Nanometer He Bubbles in Au

Irradiation produces a distribution of defect sizes in materials, with the smallest defects often below one nanometer in size and approaching the scale of a single unit cell in metals. While high-resolution scanning transmission electron microscopy (STEM)-based imaging can directly image structures at this level, techniques such as four-dimensional STEM (4D-STEM) enable characterization of materials across large fields of view, capturing a more representative volume that can be valuable for quantifying defects, their distributions, and the associated strain fields. Here we present a combined HRSTEM and 4D-STEM approach to study the model system of He bubble implantation in an Au thin film. The present work is of general interest for the study of materials in extreme environments, as it demonstrates an effective way to characterize even the tiniest sub-nanometer sized He bubbles in addition to larger irradiation defects.

atomic-resolution STEM↗
DOE OSTI2025

Combining Machine Learning and Comparative Effectiveness Methodology to Study Primary Care Pharmacotherapy Pathways for Veterans With Depression

Our objective is to demonstrate an innovative method combining machine learning with comparative effectiveness research techniques and to investigate a hitherto unstudied question about the effectiveness of common prescribing patterns. For Operation Enduring Freedom/Operation Iraqi Freedom veterans with major depressive disorder, we generate pharmacotherapy pathways (of antidepressants) using process mining and machine learning. We select the medication episodes that were started at subtherapeutic doses by the first assigned primary care physician and observe the paths that those medication episodes follow. Using 2-stage least squares, we test the effectiveness of starting at a low dose and staying low for longer versus ramping up fast while balancing observable and unobservable characteristics of patients and providers through instrumental variables. We leverage predetermined provider practice patterns as instruments. We collected outpatient pharmacy data for selective serotonin reuptake inhibitors and selective norepinephrine reuptake inhibitors, patient and provider characteristics (as control variables), and the instruments for our cohort. All data were extracted for the period between 2006 and 2020. There is a statistically significant positive effect (0.68, 95% CI 0.11–1.25) of “ramping up fast” on engagement in care. When we examine the effect of “ramping up slow”, we see an insignificant negative impact on engagement in care (−0.82, 95% CI −1.89 to 0.25). As expected, the probability of drop-out also seems to have a negative effect on engagement in care (−0.39, 95% CI −0.94 to 0.17). We further validate these results by testing with medication possession ratios calculated periodically as an alternative engagement in care metric. Our findings contradict the “Start low, go slow” adage, indicating that ramping up the dose of an antidepressant faster has a significantly positive effect on engagement in care for our population.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Combining resonant and tail-based anomaly detection

In many well-motivated models of the electroweak scale, cascade decays of new particles can result in highly boosted hadronic resonances (e.g., Z / W / h ). This can make these models rich and promising targets for recently developed resonant anomaly detection methods powered by modern machine learning. We demonstrate this using the state-of-the-art classifying anomalies through outer density estimation () method applied to supersymmetry scenarios with gluino pair production. We show that , despite being model agnostic, is nevertheless competitive with dedicated cut-based searches, while simultaneously covering a much wider region of parameter space. The gluino events also populate the tails of the missing energy and H T distributions, making this a novel combination of resonant and tail-based anomaly detection. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

First combined tuning on transverse kinematic imbalance data with and without pion production constraints

We present the first combined tuning, using genie, of four transverse kinematic imbalance measurements of neutrino-hydrocarbon scattering, both with and without pion final states, from the T2K and MINERvA experiments. As a proof of concept, we have simultaneously tuned the initial state and final-state interaction models (SF-CFG and hA, respectively), producing a new effective model that more accurately describes the data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Combination of Searches for Higgs Boson Pair Production in pp Collisions at $\sqrt{s}$ = 13 TeV with the ATLAS Detector

This Letter presents results from a combination of searches for Higgs boson pair production using 126–140 fb−1 of proton-proton collision data at √𝑠 =13 TeV recorded with the ATLAS detector. At 95% confidence level (CL), the upper limit on the production rate is 2.9 times the standard model (SM) prediction, with an expected limit of 2.4 assuming no Higgs boson pair production. Constraints on the Higgs boson self-coupling modifier 𝜅 𝜆 = 𝜆 𝐻⁡𝐻⁡𝐻 /𝜆$^{SM}_{𝐻⁡𝐻⁡𝐻}$, and the quartic 𝐻⁡𝐻⁡𝑉⁢𝑉 coupling modifier 𝜅 2⁢𝑉 = 𝑔 𝐻⁡𝐻⁡𝑉⁢𝑉⁡ /𝑔$^{SM}_{𝐻⁡𝐻⁡𝑉⁢𝑉}$, are derived individually, fixing the other parameter to its SM value. The observed 95% CL intervals are −1.2<𝜅 𝜆 < 7.2 and 0.6<𝜅 2⁢𝑉 < 1.5, respectively, while the expected intervals are −1.6<𝜅 𝜆 < 7.2 and 0.4<𝜅 2⁢𝑉 < 1.6 in the SM case. Constraints obtained for several interaction parameters within Higgs effective field theory are the strongest to date, offering insights into potential deviations from SM predictions.

Hadron colliders↗
DOE OSTI2025

Pion-nucleon scattering in baryon chiral perturbation theory combined with the 1/𝑁 𝑐 expansion

This work implements the combined baryon chiral perturbation theory (BChPT) and 1/𝑁 𝑐 expansions for pion-nucleon elastic scattering. The effective theory is based on the baryon sector dynamical spin-flavor 𝑆⁢𝑈⁡(4) symmetry emergent in the large 𝑁 𝑐 limit, whose breaking is controlled by the 1/𝑁 𝑐 expansion. The noncommutativity of the chiral and 1/𝑁 𝑐 expansions in unitarity corrections (loops) requires a linking of both expansions. As it was shown in the case of baryon masses and currents, the natural linking is the 𝜉 expansion, in which 𝒪⁡(𝑝) = 𝒪⁡(1/𝑁 𝑐 ) = 𝒪⁡(𝜉). The spin-flavor symmetry requires that the ground state baryons span an 𝑆⁢𝑈⁡(4) symmetric irreducible representation which implies that in particular 𝑁 and Δ are active degrees of freedom in the effective theory. The scattering amplitude is expanded to the next-to-next-to leading order in the 𝜉 expansion, corresponding to the one-loop contributions with the leading-order Lagrangian. The results are given for generic 𝑁 𝑐 in order to demonstrate the consistency of the framework. The spin-flavor symmetry plays a central role in maintaining the consistency of the effective theory with respect to the 1/𝑁 𝑐 expansion. This consistency manifests itself in an improvement in the convergence of the low energy expansion with respect to the case of the ordinary BChPT without an explicit dynamical Δ, which is known to be inconsistent with the constraints of 𝑁 𝑐 scaling. Fits to the 𝜋⁢𝑁 → 𝜋⁢𝑁, 𝑆, 𝑃, and 𝐷 partial wave amplitudes from the SAID data base are finally used to test the framework and to determine the energy range of its applicability.

Jayakodige, D. [Hampton Univ., Hampton, VA (United↗
DOE OSTI2025

Combined Effects of Electric Vehicle Charging and Rooftop Solar Integration on Voltage Imbalance in Residential Distribution Networks

Residential electric vehicle (EV) chargers, as single phase loads, contribute to unbalanced voltage drops across phases, while rooftop solar systems, as single phase generators, can exacerbate voltage imbalance by causing unbalanced voltage increases. This paper investigates combined effects of residential EV charging and rooftop solar generation on voltage imbalance in residential distribution grids. The study examines these simultaneous impacts using the IEEE 8500-node test system, enhanced with a secondary network to realistically model the EV chargers and rooftop solar integration. To account for the variability and uncertainty in the EV charging loads and solar generation, a Monte Carlo approach is employed to capture and quantify the simultaneous impact of the EV charging and rooftop solar integration. In this approach, multiple influencing factors are considered, including state-of-charge (SOC), maximum charging power levels, and geographic distribution of chargers. The results provide practical insights for utilities and stakeholders, offering expectations for planning and operating strategies that effectively manage the increasing adoption of EVs and solar power while maintaining grid reliability.

Choi, Jongchan [ORNL] (ORCID:000000025952455X)↗
DOE OSTI2025

Reimagining Disassembly Interfaces With Visualization: Combining Instruction Tracing and Control Flow With DisViz

In applications where efficiency is critical, developers may examine their compiled binaries, seeking to understand how the compiler transformed their source code and what performance implications that transformation may have. This analysis is challenging due to the vast number of disassembled binary instructions and the many-to-many mappings between them and the source code. These problems are exacerbated as source code size increases, giving the compiler more freedom to map and disperse binary instructions across the disassembly space. Interfaces for disassembly typically display instructions as an unstructured listing or sacrifice the order of execution. Here, we design a new visual interface for disassembly code that combines execution order with control flow structure, enabling analysts to both trace through code and identify familiar aspects of the computation. Central to our approach is a novel layout of instructions grouped into basic blocks that displays a looping structure in an intuitive way. We add to this disassembly representation a unique block-based mini-map that leverages our layout and shows context across thousands of disassembly instructions. Finally, we embed our disassembly visualization in a web-based tool, DisViz, which adds dynamic linking with source code across the entire application. DizViz was developed in collaboration with program analysis experts following design study methodology and was validated through evaluation sessions with ten participants from four institutions. Participants successfully completed the evaluation tasks, hypothesized about compiler optimizations, and noted the utility of our new disassembly view. Our evaluation suggests that our new integrated view helps application developers in understanding and navigating disassembly code.

Computer science↗
DOE OSTI2025

Exploration of a Combined LIBS and LA-ICP-MS Approach for Apatite Characterisation

A combined laser‐induced breakdown spectroscopy (LIBS) and laser ablation‐inductively coupled plasma‐mass spectrometry (LA‐ICP‐MS) method is demonstrated for comprehensive apatite analysis. These measurements provide elemental imaging that can be used as a screening technique for chemical selection of grains for subsequent analysis (e.g., U‐Pb geochronology) or can be used to understand elemental distributions within a single grain that would have direct textural‐chemical implications (e.g., zoning patterns). Adding LIBS as a simultaneous measurement, to LA‐ICP‐MS U‐Pb geochronology, allowed for the direct determination of F (H and O show promise for future applications) in addition to major and trace elements of interest. Here, the quantitative measurements were validated against a series of apatites with known values and used to characterise a wide range of samples. Fluorine detection limits were determined to be as low as 70 μg g ‐1 F (broadband CMOS detector) and 4.2 μg g ‐1 F (ICCD detector). U‐Pb age dating was simultaneously collected by LA‐ICP‐MS with the quantitative elemental data from LIBS, providing a comprehensive method for geochronology.

Apatite↗
DOE OSTI2024

Design-Point Techno-Economics of Brayton Cycle PTES for Combined Heat and Power

Pumped thermal energy storage (PTES) systems are grid batteries that use heat pumps to create both hot and cold thermal energy stores when there is excess electricity and then use a power cycle to convert the thermal energy into electricity when there is demand for electricity. In normal operation, Joule-Brayton PTES discharges low-grade heat at temperatures useful for thermal energy consumers like district and industrial heating. Furthermore, PTES designs, like conventional combined heat and power (CHP) technology, can be modified to sacrifice some round-trip efficiency RTE to increase the temperature of heat rejection. This paper uses design-point performance and cost models that provide a detailed understanding of the efficiency and cost trade-offs of rejecting heat at various temperatures in ideal-gas Brayton PTES configurations. First, we keep the heat rejection in its nominal location in the PTES system: in the discharge cycle after the low-pressure exit of the recuperator before the cold-storage heat exchanger. Next, we move the heat rejection to the discharge turbine exit. We define design-point metrics that isolate both the cost and performance penalty associated with the hotter heat rejection and attribute it exclusively to the heat economic metrics. Finally, we estimate the performance of electric heater technology to generate heat at equivalent temperatures. We find that the levelized cost of heat, including the cost of thermal energy storage (TES) buffering the PTES and heat off-taker, compares favorable versus electric technologies and is less than the cost of natural gas for low temperature scenarios and competitive with the cost of natural gas in some regions of the contiguous United States in high temperature scenarios.

CHP↗