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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High order interpolation of magnetic fields with vector potential reconstruction for particle simulations

We propose a method for interpolating divergence-free continuous magnetic fields via vector potential reconstruction using Hermite interpolation, which ensures high-order continuity for applications requiring adaptive, high-order ordinary differential equation (ODE) integrators, such as the Dormand-Prince method. The method provides C(m) continuity and achieves high-order accuracy, making it particularly suited for particle trajectory integration and Poincaré section analysis under optimal integration order and timestep adjustments. Through numerical experiments, we demonstrate that the Hermite interpolation method preserves volume and continuity, which are critical for conserving toroidal canonical momentum and magnetic moment in guiding center simulations, especially over long-term trajectory integration. Furthermore, we analyze the impact of insufficient derivative continuity on Runge-Kutta schemes and show how it degrades accuracy at low error tolerances, introducing discontinuity-induced truncation errors. Lastly, we demonstrate performant Poincaré section analysis in two relevant settings of field data collocated from finite element meshes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A new self-adaptive reconstruction method to identify defects through Wigner–Seitz approach

A new self-adaptive reconstruction method based on local atomic structure at any given molecular dynamics (MD) step has been developed in this article. The method can be used in Wigner–Seitz defect analysis approach to correctly and efficiently explore the information of both point defects and complex defect clusters (e.g. dislocation loops and voids) formed after a displacement cascade where the cascade interacts with grain boundaries and/or dislocations. The algorithm and validation are provided in detail. Results for identification of radiation defects during and after cascades interacting with a dislocation network show that the new method can well recognize all simple and complex defects and defect clusters. Thus, this new method provides a totally new way to explore the density and size of radiation defects at atomic scale after complex MD evolution processes, providing correct information to understand and predict radiation damage in materials through atomic simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Three-dimensional reconstruction of implosion stagnation in laser direct drive on OMEGA

Multidimensional effects on hot-spot formation must be considered to better understand the current limits on the performance of direct-drive inertial confinement fusion experiments on OMEGA with cryogenically layered solid deuterium–tritium targets. A comprehensive reconstruction effort has been established at the Laboratory for Laser Energetics to infer hot-spot and shell conditions at stagnation from a large collection of x-ray, neutron, and particle detectors along multiple lines of sight. Several time-gated and time-integrated x-ray imagers are being used to record the shape of the hot-spot plasma. A 3D hot-spot x-ray emission tomography technique has been developed to infer low-mode drive asymmetries from the hot-spot shape. A suite of neutron diagnostics is used to provide measurements of hot-spot flow velocity, ion temperature, and areal density. Here, the information obtained from the x-ray and neutron detectors will be combined into a coherent model of the shape of the hot spot and shell assembly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Multi-track event reconstruction to constrain the p ̄ background in Mu2e

Mu2e experiment will search for the neutrinoless, coherent conversion of μ − → e − in the field of an Al nucleus. One of the expected backgrounds is p ̄ ’s annihilating in the stopping target to produce signal-like e − ’s. Although not a dominant background, it has a large uncertainty and cannot be suppressed by the timing cuts used to reduce the prompt background. However, at Mu2e energies, p p ̄ annihilation is the only source of events with multiple, simultaneous particles coming from the stopping target. We utilized this unique feature and developed a novel way to reconstruct multi-track events and estimate the p ̄ background.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Measuring very low radiation doses in PTFE for nuclear forensic enrichment reconstruction

Every country that has made nuclear weapons has used uranium enrichment to do so. Despite the centrality of this technology to international security, there is still no reliable physical marker of past enrichment in the open literature that can be used to perform forensic verification of historically produced weapons on gas centrifuges. We show that the extremely low radioactivity from uranium alpha emissions during enrichment leaves detectable and irreversible calorimetric signatures in the common enrichment gasket material PTFE, allowing for historical reconstruction of past enrichment activities at a sensitivity better than one weapon’s quantity of highly enriched uranium. Fast scanning calorimetry also enables the measurement of recrystallization enthalpies of sequentially microtomed slices, confirming the magnitude and the type of radiation exposure while also providing detection of tampering and a method for analyzing field samples useful for treaty verification. Furthermore, this work opens the door for common items to be turned into precise dosimeters to detect the past presence of radioactivity, nuclear materials, and related activities with high confidence.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Re-directing mixed-feed deconstruction products to hybrid polyesters: Tolerance windows for commodity plastics reconstruction

Solvolysis is a promising strategy for mixed-feed polyester recycling, but little attention has been given to downstream product separations or the impact of using imperfectly separated monomer mixtures in recycled polymer reconstruction. Here, we challenge the traditional need for high-purity monomers in polycondensation synthesis of engineering thermoplastics. Monomer mixtures are derived from catalyzed methanolysis of polyethylene terephthalate (PET), polybutylene terephthalate (PBT), and polybutylene adipate-co-terephthalate (PBAT), with separation scenarios ranging from high (99:1) to low (90:10) purity. We focus on challenging-to-separate products like ethylene glycol and 1,4-butanediol and evaluate tolerance for comonomer incorporation in recycled hybrid polyesters: polybutylene-co-ethylene terephthalate (PBET) and polybutylene ethylene adipate-co-terephthalate (PBEAT). Evaluations are made between “contaminant” monomer incorporation, and the resulting materials’ thermal properties, crystalline structure, tensile toughness, and rheology. Ultimately, we highlight that despite incorporation of contaminant monomer, high-performance hybrid polyesters of PET, PBT, and PBAT are obtained while reducing the strain of high-throughput separations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Accelerating Embedding Potential Optimization by Reconstructing the Pseudo-Valence Electron Density

Density functional embedding theory (DFET) enables use of electronic structure methods with higher accuracy than density functional theory in a local region, with applications thus far ranging from (photo/electro)catalysis to reactions in solution. DFET partitions a large collection of atoms into smaller groups that interact via a shared embedding (interaction) potential V emb , determined via functional optimization. The optimized effective potential (OEP) process used to optimize V emb is time-consuming and becomes a computational bottleneck due to sharp, oscillating features of V emb near nuclei. Here, similar to pseudopotential theory, by reconstructing electron densities used in the OEP process from smoother pseudo-valence-only (PVO) electron densities as proxies for total densities of the full system and subsystems, we can retain accuracy in the embedded electronic structure calculations while potentially reducing the overhead of V emb construction, within the projector augmented-wave (PAW) formalism. We explore three different chemical reactions as exemplars to test PVO–DFET, namely, H 2 dissociative adsorption on a Cu(111) surface, H 2 O adsorption on a Pt(111) surface, and aqueous [Ca 2+ –SO 4 2– ] ion-pair formation. The PVO approximation works well for all three systems with minimal loss of accuracy (∼10–70 meV error relative to the original exact-derivative (ED) approach) while accelerating V emb generation for the Cu and Pt systems respectively by 20× and 5×. Given proper numerical convergence parameters, the spatial distributions of differences between PVO- and ED-based V emb outside the core regions are small, explaining the exceptional agreement between the two approaches. Finally, we anticipate that this more efficient PVO–DFET approximation will be useful whenever computation of V emb is much more expensive than subsequent embedded high-level electron correlation calculations.

approximation↗
DOE OSTI2024

Composition-Dependent Reconstructions of Titanium Oxide Clusters and Cu(111) Support via Cluster-Adatom Interactions

Mass-selected cluster deposition and scanning tunneling microscopy (STM) were used to investigate the surface structure and thermal stability of Ti 3 O y (y = 5, 6) clusters on a Cu(111) surface. STM imaging shows that the substoichiometric Ti 3 O 5 clusters aggregate into large dendritic assemblies at step edges, while the stoichiometric Ti 3 O 6 clusters are highly dispersed as single or small groupings of clusters. Cluster deposition also results in extensive reconstruction of the Cu(111) surface. The Ti 3 O 5 /Cu(111) surface exhibits one Cu-layer deep pits that are ringed by cluster assemblies that nucleate and grow at the perimeter step edges. By comparison, the Ti 3 O 6 /Cu(111) surface consists of irregular step edges and small one Cu-layer islands that are decorated with clusters. The restructuring of the Cu(111) surface is attributed to strong Cu-cluster interactions that release Cu adatoms from the step edges. This mechanism is supported by density functional theory (DFT) calculations, which predict that the Cu adatom attachment to the clusters is energetically favorable. Annealing the surfaces at elevated temperatures (400-700 K) results in higher densities of irregular steps, pits and isolated Cu islands as well as increased cluster aggregation. In conclusion, this work highlights adatom-cluster interactions as another manifestation of strong cluster-support interactions that can significantly alter the nature of the oxide-metal interface.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Stable Co-valorization of Carbon Dioxide and Methane via Dynamic Reconstruction of a Metal Oxide Solid Solution Catalyst

Dry reforming of methane (DRM) is a process that converts two greenhouse gases (methane and carbon dioxide) into syngas, a mixture of H 2 and CO, that can lead to a variety of value-added chemicals. Owing to its endothermic nature, high reaction temperatures up to 800 °C are typically required and the grand challenge lies in developing robust catalysts without sintering and coking-induced deactivation during the long-term on-stream operation. Towards this aim, herein, a robust complex oxide-supported NiCu alloy catalyst was generated in situ during DRM. By leveraging the configurational stability of a solid oxide solution precursor, tightly anchored NiCu bimetallic nanoparticles were in situ exsoluted and acted as the active sites in DRM. The as-afforded catalyst exhibited stable performance for DRM due to the ability to repel coke off the surface as the reaction proceeds. Kinetic experiments along with top surface characterization detail the reconstruction behavior of the solid oxide solution under DRM reaction conditions. In conclusion, the fundamental insights from this work provide guidance on generating resistant and flexible catalysts via in situ active sites formation from easily synthesized metal oxide solid solutions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Strained-Induced Morphological Reconstruction of RuO 2 (110) Thin-Film Electrocatalysts

Strain is a widely used strategy for electrocatalyst engineering. Overstraining, however, can lead to unintentional materials transformation. We investigate the impact of strain on the surface morphology of a rutile RuO 2 (110) film grown on a symmetry-matching rutile TiO 2 (110) substrate. When the film thickness exceeds 9 nm, the RuO 2 surface relaxes by forming step edges that expose the {011} plane. Density functional theory (DFT) calculation shows that the (011) facet is among the lower energy surfaces of rutile RuO 2 , suggesting that this formation incurs minimal energetic penalties. In situ atomic force microscopy (AFM) shows that the film maintains the (110) structure of the terrace during electrochemistry. Inductively coupled plasma–mass spectrometry (ICP-MS) further reveals the insensitivity of the Ru dissolution to strain. Here, our findings show a strain-relieving pathway via surface reconstruction in RuO 2 (110) and provide an example of a strain-relieving mechanism that does not affect dissolution.

Evolution reactions↗
DOE OSTI2026

Selective Bidentate Coordination Reconstructs Residual PbI 2 to Homogenize Interfacial Energetics in Perovskite Solar Cells

Spatially heterogeneous interfacial energetics, often originating from residual lead iodide (PbI 2 ), represent a fundamental bottleneck to both the efficiency and operational stability of perovskite photovoltaics. Conventional PbI 2 passivation strategies based on monodentate ligands or highly polar solvents either interact weakly with PbI 2 or undesirably perturb the underlying three-dimensional perovskite lattice. Here, we report a diammonium bidentate strategy that selectively reconstructs residual PbI 2 into corner-sharing PbI 6 octahedra while preserving the bulk perovskite. Enabled by dual-site coordination, a newly designed thiophene-based bidentate ligand (MeXT) stabilizes PbI 6 units during passivation and establishes spatially homogeneous interfacial energetics. Perovskite solar cells incorporating MeXT achieve 26.19% power conversion efficiency and retain over 80% of their initial efficiency after 1000 h of continuous 1-sun illumination at 75 °C. This dual-anchor coordination passivation strategy establishes a general design principle for selectively treating residual PbI 2 and creating electronically coherent and operationally stable interfaces in perovskite photovoltaics.

ligands↗
DOE OSTI2025

Confronting Large‐Eddy Simulations With Stereo Camera Data by Means of Reconstructed Hemispheric Cloud Size Distributions

High-resolution hemispheric camera images at a meteorological site in western Germany are used to analyze the multi-dimensional spatial characteristics of continental cumulus cloud fields, and to evaluate Large-Eddy Simulations on this aspect. Traditional non-hemispheric cloud-detecting instruments provide additional reference data. The main model-observation comparison focuses on cloud size distributions (CSDs), employing two methods: (a) directly using three-dimensional model fields, direct CSDs, and (b) using rendered hemispheric images of the model fields as produced by a camera simulator based on path-tracing. In the latter method, both the real and rendered images are used to three-dimensionally reconstruct the cloud fields, yielding hemispheric CSDs. Advantages of hemispheric comparisons over more classic approaches include (a) fair comparisons between model and data, and (b) full use of the enhanced resolutions and hemispheric spatial coverage of the camera imagery. Basic evaluation of the simulations demonstrates good agreement on thermodynamic structure and its diurnal cycle. Cloud heights and cloud cover are intercompared between the model, camera data and other instrumentation, providing insight into their structural differences. A consistent alignment is found between the hemispheric CSDs from both the model and the cameras. Power law fits reveal structurally lower exponents in hemispheric CSDs compared to non-hemispheric CSDs, which particularly caution against directly comparing hemispheric CSDs to non-hemispheric distributions. This result is robust for sample size and fitting method. These findings inform future use of hemispheric camera systems for studying cumulus cloud field morphology and model evaluation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Selective semihydrogenation of acetylene in ethylene using defect-rich boron nitride catalyst from flux reconstruction

Efficient removal of trace acetylene from ethylene streams is essential for producing polymer-grade ethylene, yet achieving highly selective semihydrogenation without over-hydrogenation remains a long-standing challenge. A key barrier is the lack of a simple, low-cost catalyst that can activate hydrogen effectively while preventing ethylene from reacting further. Here we show that defect-rich boron nitride, prepared through a straightforward flux reconstruction method, serves as a highly selective and metal-free catalyst for acetylene semihydrogenation. The catalyst contains abundant open boron and nitrogen sites that enable efficient hydrogen activation and rapid release of ethylene, thereby avoiding over-hydrogenation. Experiments combined with isotope labeling and theoretical analysis reveal that these defects lower the energy barrier for hydrogen activation while accelerating product desorption. Our findings demonstrate a scalable strategy for defect engineering in boron nitride and highlight its potential as a robust, sustainable alternative to metal-based catalysts in industrial ethylene purification.

Wang, Tao [Oak Ridge National Laboratory (ORNL), O↗
DOE OSTI2024

Modeling Si/SiGe quantum dot variability induced by interface disorder reconstructed from multiperspective microscopy

SiGe heteroepitaxial growth yields pristine host material for quantum dot qubits, but residual interface disorder can lead to qubit-to-qubit variability that might pose an obstacle to reliable SiGe-based quantum computing. By convolving data from scanning tunneling microscopy and high-angle annular dark field scanning transmission electron microscopy, we reconstruct 3D interfacial atomic structure and employ an atomistic multi-valley effective mass theory to quantify qubit spectral variability. The results indicate (1) appreciable valley splitting (VS) variability of ~50% owing to alloy disorder and (2) roughness-induced double-dot detuning bias energy variability of order 1–10 meV depending on well thickness. For measured intermixing, atomic steps have negligible influence on VS, and uncorrelated roughness causes spatially fluctuating energy biases in double-dot detunings potentially incorrectly attributed to charge disorder. Our approach yields atomic structure spanning orders of magnitude larger areas than post-growth microscopy or tomography alone, enabling more holistic predictions of disorder-induced qubit variability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Learning robust parameter inference and density reconstruction in flyer plate impact experiments

Estimating physical parameters or material properties from experimental observations is a common objective in many areas of physics and material science. In many experiments, especially in shock physics, radiography is the primary means of observing the system of interest. However, radiography does not provide direct access to key state variables, such as density, which prevents the application of traditional parameter estimation approaches. Here we focus on flyer plate impact experiments on porous materials, and resolving the underlying parameterized equation of state (EoS) and crush porosity model parameters given radiographic observation(s). We use machine learning as a tool to demonstrate with high confidence that using only high impact velocity data does not provide sufficient information to accurately infer both EoS and crush model parameters, even with fully resolved density fields or a dynamic sequence of images. We thus propose an observable data set consisting of low and high impact velocity experiments/simulations that capture different regimes of compaction and shock propagation, and proceed to introduce a generative machine learning approach which produces a posterior distribution of physical parameters directly from radiographs. We demonstrate the effectiveness of the approach in estimating parameters from simulated flyer plate impact experiments, and show that the obtained estimates of EoS and crush model parameters can then be used in hydrodynamic simulations to obtain accurate and physically admissible density reconstructions. Finally, we examine the robustness of the approach to model mismatches, and find that the learned approach can provide useful parameter estimates in the presence of out-of-distribution radiographic noise and previously unseen physics, thereby promoting a potential breakthrough in estimating material properties from experimental radiographic images.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Reconstruction of unstable heavy particles using deep symmetry-preserving attention networks

Abstract Reconstructing unstable heavy particles requires sophisticated techniques to sift through the large number of possible permutations for assignment of detector objects to the underlying partons. An approach based on a generalized attention mechanism, symmetry preserving attention networks (SPA-NET), has been previously applied to top quark pair decays at the Large Hadron Collider which produce only hadronic jets. Here we extend the SPA-NET architecture to consider multiple input object types, such as leptons, as well as global event features, such as the missing transverse momentum. In addition, we provide regression and classification outputs to supplement the parton assignment. We explore the performance of the extended capability of SPA-NET in the context of semi-leptonic decays of top quark pairs as well as top quark pairs produced in association with a Higgs boson. We find significant improvements in the power of three representative studies: a search for$$t\bar{t}H$$ t t ¯ H , a measurement of the top quark mass, and a search for a heavy$${Z}^{{\prime} }$$ Z ′ decaying to top quark pairs. We present ablation studies to provide insight on what the network has learned in each case.

Physics↗
DOE OSTI2025

Reconstruction framework advancements to support streaming for the ePIC detector at the EIC

The ePIC collaboration adopted the JANA2 framework to manage its reconstruction algorithms. This framework has since evolved substantially in response to ePIC’s needs. There have been three main design drivers: integrating cleanly with the Podio-based data models and other layers of the key4hep stack, enabling external configuration of existing components, and supporting timeframe splitting for streaming readout. The result is a unified component model featuring a new declarative interface for specifying inputs, outputs, parameters, services, and resources. This interface enables the user to instantiate, configure, and wire components via an external file. One critical new addition to the component model is a hierarchical decomposition of data boundaries into levels such as Run, Timeframe, PhysicsEvent, and Subevent. Two new component abstractions, Folder and Unfolder, are introduced in order to traverse this hierarchy, e.g. by splitting or merging. The pre-existing components can now operate at different event levels, and JANA2 will automatically construct the corresponding parallel processing topology. This means that a user may write an algorithm once, and configure it at runtime to operate on timeframes or on physics events. Overall, these changes mean that the user requires less knowledge about the framework internals, obtains greater flexibility with configuration, and gains the ability to reuse the existing abstractions in new streaming contexts.

Brei, Nathan [Thomas Jefferson National Accelerato↗
DOE OSTI2026

Automated Signal Timing Plan Reconstruction Using High-Resolution Event-Based Controller Data for Digital Twins

Transportation digital twins are essential tools for evaluating emerging technologies such as connected and automated vehicles, adaptive traffic signal control, and mobility optimization strategies. Realistic digital twins require accurate emulation of real-world signal controllers and detailed signal timing plans. However, signal timing plans are often unavailable or difficult to access, forcing researchers and modelers to rely on assumed fixed timings or halt their analysis. To overcome this challenge, we present a method that directly estimates signal timing plan parameters using high-resolution, event-based data from traffic signal controllers. The proposed method extracts key parameters, including cycle length, offset, phase sequence, coordinated phases, phase-specific minimum and maximum green durations, vehicle extensions, and splits under coordination. A rule-based deterministic signal timing reconstruction algorithm based on traffic signal operation rules, such as those outlined in the Signal Timing Manual, is developed and validated. We evaluate this method, which uses high-resolution controller event logs and verified signal timing plans, on 94 signalized intersections in Nashville, Tennessee, demonstrating their ability to generate accurate, simulation-ready signal timing plans for tools such as SUMO and Vissim.

Saroj, Abhilasha [ORNL] (ORCID:0000000191178063)↗