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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

An idealized model for the crystal structure of intermetallic compounds isostructural with Mg 3 Cr 2 Al 18

Mg 3 Cr 2 Al 18 (abbreviated in this report as MCA) is the parent phase for a large class of intermetallic compounds that belong to the cubic crystal space group, $Fd\overline{3}m$. The purpose of this paper is to introduce an ideal, unrelaxed crystal structure for compounds isostructural with MCA. There are five distinct atomic sublattices in MCA compounds, which can be denoted, $A, B, C, D,$ and $E$. With this, a general description for MCA structures can be written as $A^{8a}_{1}B^{16c}_{2}C^{16d}_{2}D^{48f}_{6}E^{96g}_{12}$, where the superscripts represent the Wyckoff special equipoints associated with the various sublattices in MCA, and the subscripts indicate the contributions of each sublattice to the stoichiometry of one formula unit in an any given MCA structured compound. Sublattices D and E are where deviations from ideality occur in real, MCA-like compounds. This paper examines MCA bond lengths, nearest-neighbour polyhedral arrangements, 3-D sublattice crystal structures, 2-D atom tessellation patterns, and crystal chemical effects associated with atomic relaxations on the $D$ and $E$ sublattices. The ideal MCA crystal structure developed in this report provides an appropriate initial structure for use as input to crystal structure refinements of diffraction data for MCA-like phases being examined experimentally, or as input for computational, atomistic simulations of the structures of such compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Widen the resonance at ultra-high energies: novel probes of neutrino self-interactions in the high-mass regime

Neutrino self-interactions beyond the Standard Model are well motivated by the nonzero masses of neutrinos, which are the only known particles guaranteed to have new physics. Meanwhile, cosmic messengers, especially neutrinos, play a central role in probing new physics, as they provide experimental conditions far beyond the reach of laboratories and serve as the link between laboratory fundamental-physics discoveries and their roles in the Universe, where many new physics motivations originate.In this work, we propose a novel probe of neutrino self-interactions through ultrahigh-energy neutrinos scattering off the cosmic neutrino background when the lightest neutrino species remains relativistic today.This allows us to “Widen the Resonance” of such scattering [1].In addition, we also provide a semi-analytic framework for cosmogenic ultrahigh-energy neutrino production, avoiding computationally intensive simulations and yielding results precise enough for beyond-the-standard-model studies.The widened resonance enables future ultrahigh-energy neutrino telescopes,in particular GRAND, to probe mediator masses from MeV to GeV, reaching couplings down to g ∼ 10$^{-3}$ — up to two orders of magnitude beyond current bounds.Our results enhance the discovery potential of neutrino self-interactions in the high-mass regime, potentially offering crucial insights into the connections between the neutrino sector and dark sector.

Machado, Pedro A.N. [Fermilab] (ORCID:000000029118↗
DOE OSTI2024

Validation of a synthetic fast ion loss detector model for Wendelstein 7-X

Abstract We present the first validated synthetic diagnostic for fast ion loss detectors (FILDs) in the Wendelstein 7-X (W7-X) stellarator. This model has been developed on, and validated against experimental data from, a FILD provided by the National Institute for Fusion Science (NIFS-FILD), with potential future applicability to the existing Faraday Cup FILD (FC-FILD) on W7-X as well as the scintillating FILD (S-FILD) currently under development. A workflow combining Monte Carlo codes BEAMS3D and ASCOT5 is used to track fast ions produced by neutral beam injection from the moment of ionization until they are thermalized or lost from the last closed flux surface, and from there to a virtual plane which serves as a projection of the entrance aperture to the FILD. Simulations in ASCOT5 are analyzed via a geometric method to determine the probability of transmission through the FILD aperture and onto the detector as a function of normalized momentum, pitch angle, gyrophase, and position at the virtual plane. This probability is then applied to the simulated ions arriving from the plasma, producing a simulated signal from a computationally tractable number of simulated fast ions. Simulated signals are presented for two W7-X experiments with neutral beam injection and quantitatively compared with experimental measurements from the NIFS-FILD diagnostic. An estimate of the frequency of charge-exchange with neutral particles in the edge is performed, and it is found that this process may have a significant impact on the measured signals.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Advection algorithms for quantum neutrino moment transport

Neutrino transport in compact objects is an inherently challenging multidimensional problem. Here, this difficulty is compounded if one includes flavor transformation—an intrinsically quantum phenomenon requiring one to follow the coherence between flavors and thus necessitating the introduction of complex numbers. To reduce the computational burden, simulations of compact objects that include neutrino transport often make use of momentum-angle-integrated moments (the lowest order ones being commonly referred to as the energy density and flux) and these quantities can be generalized to include neutrino flavor, i.e., they become quantum moments. Numerous finite-volume approaches to solving the moment evolution equations for classical neutrino transport have been developed based on solving a Riemann problem at cell interfaces. In this paper we describe our generalization of a Riemann solver for quantum moments, specifically decomposing complex numbers in terms of a (signed) magnitude and phase instead of real and imaginary parts. We then test our new algorithm in numerous cases showing a neutrino fast flavor instability, varying from toy models with analytic solutions to snapshots from neutron star merger simulations. Compared to previous algorithms for neutrino transport with flavor mixing, we find uniformly smaller growth rates of the flavor transformation along with concomitantly larger length-scales, and that the results are a better match with the growth rates seen from multiangle codes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Prediction of defect properties in concentrated solid solutions using a Langmuir-like model

The alleged existence of sluggish diffusion in high-entropy alloys has drawn controversy. In high-entropy alloys and, in general, in all solids, transport properties are controlled by point defect concentration, which must be known before performing atomistic simulations to compute transport coefficients. In this work, we present a general Langmuir-like model for defect concentration in an arbitrarily complex solid solution and apply this model to generate expressions for concentrations of vacancies and small interstitial atoms. We then calculate the vacancy concentration as a function of temperature in the equiatomic CoNiCrFeMn and FeAl alloys with modified embedded-atom-method potentials for various chemical orderings, showing there is no clear correlation between vacancy thermodynamics and chemical ordering in the CoNiCrFeMn alloy, but clear systematic patterns for FeAl. We believe this is due to the high stability of disordered, random, and ordered intermetallic phases, respectively, in the CoNiCrFeMn and FeAl systems. Finally, this work provides future avenues to the prediction of thermal interstitials and vacancies in solid solutions, which is necessary for models of nonequilibrium behavior of solid solutions.

composition↗
DOE OSTI2024

Raman Sideband Cooling of Molecules in an Optical Tweezer Array to the 3D Motional Ground State

Ultracold polar molecules are promising for quantum information processing and searches for physics beyond the standard model. Laser cooling to ultracold temperatures is an established technique for trapped diatomic and triatomic molecules. Further cooling of the molecules to near the motional ground state is crucial for reducing various dephasings in quantum and precision applications. In this work, we demonstrate Raman sideband cooling (RSC) of CaF molecules in optical tweezers to near their motional ground state, with average motional occupation quantum numbers of n ¯ x = 0.16 ( 12 ) , n ¯ y = 0.17 ( 17 ) (radial directions), and n ¯ z = 0.22 ( 16 ) (axial direction), and a 3-D motional-ground-state probability of 54 ± 18 % of the molecules that survive the RSC. This process paves the way to increase molecular coherence times in optical tweezers for robust quantum computation and simulation applications. Published by the American Physical Society 2024

Physics↗
DOE OSTI2026

Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs

Dirichlet-to-Neumann maps enable the coupling of multiphysics simulations across computational subdomains by ensuring continuity of state variables and fluxes at artificial interfaces. We present a novel method for learning Dirichlet-to-Neumann maps on graphs using Gaussian processes, specifically for problems where the data obey a conservation law arising from an underlying partial differential equation. Our approach combines discrete exterior calculus and nonlinear optimal recovery to infer relationships between vertex and edge values. This framework yields data-driven predictions with uncertainty quantification across the entire graph, even when observations are limited to a subset of vertices and edges. By minimizing the reproducing kernel Hilbert space norm while penalizing kernel complexity through maximum likelihood estimation, our method ensures that the resulting surrogate strictly enforces conservation laws without overfitting. We demonstrate our method on two representative applications: subsurface flow in fracture networks and arterial blood flow. Finally, the results demonstrate that the method maintains high accuracy and well-calibrated uncertainty estimates even under severe data scarcity, highlighting its potential for scientific applications where limited data and reliable uncertainty quantification are critical.

Dirichlet-to-Neumann map↗
DOE OSTI2026

Non-Invasive Electrode Impedance Estimation for Optimized Charge Profile Parameterization of Lithium-Ion Batteries

This work presents a non-invasive method for parameterizing a physically motivated equivalent circuit model of lithium-ion batteries using operando electrochemical impedance spectroscopy and time-domain data. The proposed model consists exclusively of linear circuit elements, enabling computationally efficient simulation and real-time implementation on battery management system chips. By integrating frequency- and time-domain measurements, the model accurately estimates internal states such as the negative electrode potential, achieving a root mean square error of 12.3 mV during fast charging validation. Parameterization requires only rate tests with sinusoidal perturbations at three different ambient temperatures, making the approach experimentally accessible. The model reveals key insights into battery behavior, including rate-dependent overpotentials primarily governed by charge transfer kinetics at the positive electrode, and temperature-dependent impedance contributions from both charge transfer and solid-state diffusion processes. Validation using reference electrodes confirms the model’s ability to detect lithium plating onset and reproduce impedance behavior across a wide range of operating conditions. The approach enables in situ optimization of fast charging profiles and lays the foundation for future extensions incorporating aging effects and plating dynamics.

25 ENERGY STORAGE↗
DOE OSTI2026

Astigmatism-free 3D optical tweezer control for rapid atom rearrangement

Reconfigurable neutral-atom arrays are a promising platform for quantum computing, quantum simulation, and quantum metrology, but atom transport using frequency-chirped acousto-optic deflectors (AODs) is limited by chirp-induced acoustic lensing and trajectory distortion. We address these limitations using a three-dimensional acousto-optic deflector lens (3D-AODL), a design predicted to reduce long-range transport times by more than a factor of two. We further introduce fading-Shepard waveforms that circumvent finite AOD bandwidth, enabling sustained axial displacement. We demonstrate unrestricted three-dimensional optical-tweezer motion over a 200 μm × 200 μm × 136 μm volume with velocities exceeding 4.2 m/s. Arbitrary three-dimensional control of optical-tweezer trajectories enables rapid atom rearrangement and dynamical engineering of optical potentials in tweezer arrays and optical lattices. This capability advances quantum control and atom manipulation in neutral-atom quantum processors by enabling faster rearrangement, higher clock rates, and scalable sorting in complex geometries.

Lu, Yue-Hui [University of California, Berkeley, C↗
DOE OSTI2026

Genesis Data Card Schema, Template and Supporting Tools

Genesis Data Cards provide a standardized template and schema for documenting scientific datasets in support of discovery, access, interoperability, reusability, governed use, and AI usability. This release of the Genesis Data Card repository includes a versioned Markdown template, a LinkML schema with generated Pydantic and JSON artifacts, schema documentation, and example completed data cards. Validation tooling is provided to ensure that completed data cards conform to the schema prior to submission. Accompanying documentation for the structured metadata is provided as a Field Reference Guide. The schema and accompanying template provided in this repository address the call for actionable context that enables humans and AI systems to find, access, interpret, cite, and reuse data, and, when appropriate, integrate it into AI and machine learning workflows. The data card is intended to serve as a common metadata artifact intended to support standardized, cross-program dataset documentation across Department of Energy (DOE)-aligned efforts, including but not limited to Genesis Mission-related implementations, the Office of Science, National Nuclear Security Administration (NNSA), and Advanced Simulation and Computing (ASC) data governance and stewardship initiatives.

data card↗
DOE OSTI2026

Accelerating lattice gauge theory studies with Agentic AI

Lattice gauge theory research, with its computationally intensive simulations and complex multi‑stage workflows, is well positioned to benefit from agentic AI systems. We demonstrate how such tools can support key components of lattice gauge theory research, including novel simulation code development using standard LQCD frameworks, HPC job orchestration, simulation data analysis, and expert‑guided tuning of algorithmic parameters such as Hasenbusch mass preconditioning and multigrid solvers. Our results show that agentic AI can reduce manual effort, improve productivity, and accelerate the research cycle while maintaining essential human oversight.

Ayyar, Venkitesh [Fermilab]↗
DOE OSTI2024

Scalable, ab initio protocol for quantum simulating SU($N$)×U(1) Lattice Gauge Theories

We propose a protocol for the scalable quantum simulation of SU(N)×U(1) lattice gauge theories with alkaline-earth like atoms in optical lattices in both one- and two-dimensional systems. The protocol exploits the combination of naturally occurring SU(N) pseudo-spin symmetry and strong inter-orbital interactions that is unique to such atomic species. A detailed ab initio study of the microscopic dynamics shows how gauge invariance emerges in an accessible parameter regime, and allows us to identify the main challenges in the simulation of such theories. We provide quantitative results about the requirements in terms of experimental stability in relation to observing gauge invariant dynamics, a key element for a deeper analysis on the functioning of such class of theories in both quantum simulators and computers.

Physics↗
DOE OSTI2026

Theoretical Calculation Study of Nanomaterials

In recent years, theoretical simulations using computational physics and chemistry models have been used widely to predict the physical, chemical, and structural properties of nanomaterials. To reflect such rapid progress, two Special Issues on the theoretical study of nanomaterials were published. The 36 articles collected cover broad re-search fields and applications. In this Editorial, we provide an overview of these pub-lications and summarize the main findings. Based on these research outcomes, we lay out some future research directions.

First-principles calculations↗
DOE OSTI2026

The Molecular Structures of Liquid and Glassy Nifedipine and Felodipine and Their Incorporation into PVP

Background: Amorphous drug formulations are commonly used to improve the solubility and bioavailability of poorly soluble molecular pharmaceuticals, yet less is known about their molecular conformations and local bonding interactions than their crystalline phases. Methods: High-energy X-ray diffraction structure factor measurements have been made on liquid and glassy nifedipine (NIF), felodipine (FEL), NIF 1:3 polyvinylpyrrolidone (PVP), and FEL 1:3 PVP wt.% mixtures. The corresponding X-ray pair distribution functions have been interpreted using empirical potential structure refinement using different models and density functional theory conformer calculations. Results: In both NIF and FEL, the NH···O inter-molecular hydrogen bonds between the pyridyl nitrogen and ester carbonyls are found to be considerably weaker than those observed in the crystalline polymorphs. For nifedipine, it is proposed that either inter-molecular NH…ON nitro bonds are present and/or a fraction (<20%) of conformational changes, with the aryl ring flipped, occur in the liquid state. For felodipine, the models indicate significant disorder associated with the methyl and ethyl side chains in the liquid state, with the main peak intensity at 3.0 Å arising from intra-molecular Cl-Cl atom pairs. When nifedipine molecules are incorporated into PVP, our models show they possess stronger NH···O bonds to the PVP polymer than felodipine molecules, which have stronger affinity for bonding to the polymer than to other felodipine molecules. Conclusions: The amorphous forms of both NIF and FEL show much weaker hydrogen bonding than found in their crystalline phases. Liquid NIF also exhibits configurations which are not observed in the crystal phases.

Amorphous Solid Dispersion↗
DOE OSTI2024

Robotics for Systems Integration in Buildings - Pilot Study of Viable Approaches to Install Hygrothermal and Rigid Electrical Systems: Preprint

The Industrialized Construction Innovation (ICI) team at the National Renewable Energy Laboratory (NREL) has been exploring the use of robotics to integrate hygrothermal, mechanical, electrical, and plumbing systems in prefabricated building assemblies (offsite construction) and 3D Printed buildings (onsite construction). Such multi-system integration tasks often require specialized robots and custom end-effectors for handling a range of rigid and non-rigid building components. This paper begins with a brief overview of the current state of robotics in construction, followed by a pilot study exploring the use of robotics to integrate a simple prototype multi-trade wall assembly composed of structural studs, hygrothermal layer, wall finishing, and electrical fixtures. The study was funded by the Department of Energy's (DOE) Advanced Materials and Manufacturing Technologies Office (AMMTO). Insights about the implementation of design for manufacturing and assembly (DfMA) principles in designing the prototype wall for robotic assembly, and selection of appropriate robotic end effector hardware for handling these components are included. Detailed comparison of computational toolpath simulations of the robotic assembly process and real-life demonstration of the same is presented. Finally, limitations and lessons learned from this study along with future research recommendations for robotic assembly of more complex multi-trade assemblies, including potential scenarios such as robotic outfitting of facilities in extra-terrestrial environments is included.

advanced manufacturing↗
DOE OSTI2024

CO2 Capture Using Amines Bound to Silica

One of the main culprits of global warming is the increased amount of carbon dioxide, or CO2, in the atmosphere. NASA's global climate reports a 13% increase in atmospheric CO2 from 2000 to present. Adsorptive CO2 capture by nitrogen groups of amine-containing solvents is one of the most mature technologies deployed in petrochemical and natural gas processing plants to purify industrial gases. However, key challenges in widespread application include solvent induced reactor corrosion, amine degradation, and high regeneration energy for repeated cycling. An alternative approach is to immobilize amines on solid supports. Key performance metrics of solid amine-based CO2 adsorbents include the CO2 adsorption capacity and stability to degradation over hundreds of thousands of regeneration cycles. Our research aims to develop descriptors for CO2 capture capacity and stability against oxygen-induced degradation for amines bound to porous silica supports using experimental and computational techniques. We experimentally measure the change in CO2-uptake using solid amine adsorbents with varying chemical compositions and exposure to varying gas streams and use high-performance computers to simulate the nature and strength of CO2-adsorption and oxidative degradation reaction mechanisms. Insights from our work can facilitate the development of stable solid amine adsorbents for large-scale CO2 capture processes.

amines↗
DOE OSTI2024

Robotics for Systems Integration in Buildings: Pilot Study of Viable Approaches to Install Hygrothermal and Rigid Electrical Systems

The Industrialized Construction Innovation (ICI) team at the National Renewable Energy Laboratory (NREL) has been exploring the use of robotics to integrate hygrothermal, mechanical, electrical, and plumbing systems in prefabricated building assemblies (off-site construction) and 3D-printed buildings (on-site construction). Such multisystem integration tasks often require specialized robots and custom end effectors to handle a range of rigid and nonrigid building components. This paper begins with a brief overview of the current state of robotics in construction, followed by a pilot study exploring the use of robotics to integrate a simple prototype multitrade wall assembly composed of structural studs, hygrothermal layer, wall finishing, and electrical fixtures. The study was funded by the US Department of Energy's (DOE's) Advanced Materials and Manufacturing Technologies Office (AMMTO). Insights about the implementation of design for manufacturing and assembly (DfMA) principles in designing the prototype wall for robotic assembly, and selection of appropriate robotic end-effector hardware to handle these components are included. Detailed comparison of computational toolpath simulations of the robotic assembly process and real-life demonstration of the same are presented. Finally, limitations and lessons learned from this study are included, along with future research recommendations for robotic assembly of more complex multitrade assemblies, including potential scenarios such as robotic outfitting of facilities in extraterrestrial environments.

advanced manufacturing↗