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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

MSD CoP Webinar: Advancing MSD Research with Artificial Intelligence

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Recent advances in Artificial Intelligence (AI) are quickly changing the landscape of tools available to conceptualize, execute, and disseminate research. We posit that research efforts in Multi-Sector Dynamics can benefit from these advances; the new AI in MSD Working Group thus aims to identify and quantify opportunities and risks associated with their implementation. In this webinar, we will first introduce the new AI Working Group, which was initially conceived during the first MSD workshop in October 2023. Next, our panelists will explore how generative AI, explainable AI, and machine learning can help us improve modeling efforts in multiple domains, including climate science, hydrology, and energy systems. Finally, we will discuss the aims of the working group, gather inputs from the community, and suggest directions for the next steps. Presenters : Andrea Castelletti (Politecnico di Milano; Invited Speaker), Chaopeng Shen (Pennsylvania State University; Invited Speaker), Nicole Jackson (Sandia National Laboratory; Invited Speaker), Stefano Galelli (Cornell University; Co-Chair), David Gold (Utrecht University; Co-Chair), Jillian Sturtevant (Baylor University; Communications Officer) Moderator: Pat M. Reed (MSD CoP Facilitation Team) This webinar was held on: June 14th, 2024 from 12-1:30 PM EST

Artificial Intelligence↗
DOE OSTI2026

Measurement of the Neutron Elastic Electromagnetic Form Factor Ratio at Large Momentum Transfer

Exploring nucleon structure is vital both for understanding its origin and existence as well as for the advancement of the sciences. It helps us answer key questions such as how quark and gluon dynamics create 99% of the nucleon mass. Electron- nucleon scattering has been widely used for precision studies of the nucleon and nuclear structure since the Nobel Prize winning investigations by Robert Hofstadter and collaborators in the 1950s. These studies provide information about the spatial charge and current densities of the nucleon in terms of the electromagnetic form factors. The form factors are functions of four momentum transfer squared (Q2). Extending the electromagnetic form factor measurements to higher Q2 plays a critical role in furthering the understanding of nucleon structure. This motivated the Super BigBite Spectrometer (SBS) program at Jefferson Lab. The open nature of the spectrometers and the direct line of sight from the target to the tracking detector locations in experimental setups such as SBS creates high levels of background at the detectors. This necessitates the use of tracking detectors with high rate capability and good position resolution. Gas Electron Multiplier (GEM) detectors are an excellent choice for tracking detectors in such experiments. Understanding the performance of the GEM detectors is important not just for SBS experiments but also for future high-luminosity experiments. This thesis reports the exploratory results from the measurement of the neutron elastic electromagnetic form factor ratio (Gn E/Gn M) at high momentum transfer. A longitudinally polarized electron beam was scattered off a polarized 3He target, used as an effective polarized neutron target. In this experiment, the polarized 3He target achieved a world record polarization weighted luminosity at a beam current of 45 µA. Double spin asymmetry of the scattered neutron events is used to extract the neutron form factor ratio. Measurements were taken at Q2 = 3.0, 6.8, 9.8 (GeV/c)2. The lowest Q2 measurement is in good agreement with the existing world data, and the higher-Q2 measurements extend the Q2 reach well beyond the existing world data and are expected to remain unmatched for a long time.

Gamage, Vimukthi Haththotuwa [Univ. of Virginia, C↗
DOE OSTI2024

The ab initio non-crystalline structure database: empowering machine learning to decode diffusivity

Non-crystalline materials exhibit unique properties that make them suitable for various applications in science and technology, ranging from optical and electronic devices and solid-state batteries to protective coatings. However, data-driven exploration and design of non-crystalline materials is hampered by the absence of a comprehensive database covering a broad chemical space. In this work, we present the largest computed non-crystalline structure database to date, generated from systematic and accurate ab initio molecular dynamics (AIMD) calculations. We also show how the database can be used in simple machine-learning models to connect properties to composition and structure, here specifically targeting ionic conductivity. These models predict the Li-ion diffusivity with speed and accuracy, offering a cost-effective alternative to expensive density functional theory (DFT) calculations. Furthermore, the process of computational quenching non-crystalline structures provides a unique sampling of out-of-equilibrium structures, energies, and force landscape, and we anticipate that the corresponding trajectories will inform future work in universal machine learning potentials, impacting design beyond that of non-crystalline materials. In addition, combining diffusion trajectories from our dataset with models that predict liquidus viscosity and melting temperature could be utilized to develop models for predicting glass-forming ability.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Emerging magnetic materials for electric vehicle drive motors [Slides]

Increasing demand for electric vehicles (EVs) is increasing demand for the permanent magnets that drive their motors, as approximately 80% of modern EV drivetrains rely on high-performance permanent magnets to convert electricity into torque. In turn, these high-performance permanent magnets rely on rare earth elements for their magnetic properties. These elements are "critical" (i.e., at risk of limiting the growth of renewable energy technologies such as EVs), which motivates an exploration for alternative materials. In this article, we overview the relevant fundamentals of permanent magnets, describe commercialized and emerging materials, and add perspective on future areas of research. Currently, the leading magnetic material for EV motors is Nd 2 Fe 14 B, with samarium-cobalt compounds (SmCo 5 and Sm 2 Co 17 ) providing the only high-performing commercialized alternative. Emerging materials that address criticality concerns include Sm 2 Fe 17 N 3 , Fe 16 N 2 , and the L10 structure of FeNi, which use lower cost elements that produce similar magnetic properties. However, these temperature-sensitive materials are incompatible with current metallurgical processing techniques. We provide perspective on how advances in low-temperature synthesis and processing science could unlock new classes of high-performing magnetic materials for a paradigm shift beyond rare earth-based magnets. In doing so, we explore the question: What magnetic materials will drive future EVs?

42 ENGINEERING↗
DOE OSTI2025

OLCF’s Advanced Computing Ecosystem (ACE): FY25 Update for Ongoing Efforts

The advent of widespread use of artificial intelligence (AI) and machine learning (ML) models in science, coupled with fast data production rates of scientific instruments strain the traditional batch-oriented high-performance computing (HPC) environment. As scientific exploration continues to require more data and faster processing and analysis, new emerging technologies and capabilities to enable cross-facility and time-sensitive workflows are required for seamless integration of HPC and experimental facilities. The Advanced Computing Ecosystem (ACE) is a strategic initiative within the Oak Ridge Leadership Computing Facility (OLCF) established in 2024 to support the development of cutting-edge technologies to advance computational research and infrastructure at OLCF and across the Department of Energy (DOE). Several DOE initiatives are spearheading the evolution of the scientific landscape by blurring facility boundaries and connecting the user facilities to advance scientific capabilities and ensure energy dominance. The DOE Integrated Research Infrastructure (IRI) program is one example that is laying a foundation to support complex cross-facility workflows. The IRI program aims to integrate diverse computational resources, data infrastructures, and scientific instruments to facilitate collaboration and accelerate scientific discovery. The Interconnected Science Ecosystem (INTERSECT) initiative at Oak Ridge National Laboratory (ORNL) is another example that aims to revolutionize scientific research through AI-driven, interconnected autonomous laboratories and research facilities. Finally, the American Science Cloud (AmSC), recently announced in the “One Big Beautiful Bill”, aims to leverage prior infrastructure efforts of the IRI and automation and AI efforts of INTERSECT (and others) to build a federated, AI-augmented AmSC platform to unify the DOE’s computing, experimental, and data resources to catalyze scientific innovation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Harnessing citizen science to contextualize adaptation mechanism discovery

Species occupying broad geographic regions have evolved multiple mechanisms to regulate phenological characteristics, enabling adaptations to diverse native habitats. By developing computer vision AI to process citizen science observations across native habitats over North America, we uncovered a consistent latitudinal trend of earlier flowering at higher latitudes in warm-season perennial grasses. To explore the underlying mechanisms of adaptation, we conducted common garden experiments with one species (switchgrass) and discovered the opposite latitudinal flowering-time trend. Integration of differential plasticity of GI-Hd1-FTL1 haplotypes of flowering time regulatory genes, haplotype range, and local environmental profiles found that observations from native habitats capture only part of the genotype-environment-phenotype spectrum established in common garden experiments, therefore reconciling the discrepancy. Two mechanisms emerged as key forces shaping current haplotype ranges and influencing future shifts. Our study highlights the power of combining citizen science observations with designed experiments to uncover mechanisms of adaptation across spatiotemporal scales.

FTL1↗
DOE OSTI2024

Exploration of Novel Neuromorphic Methodologies for Materials Applications

Many of today's most interesting questions involve understanding and interpreting complex relationships within graph-based structures. For instance, in materials science, predicting material properties often relies on analyzing the intricate network of atomic interactions. Graph neural networks (GNNs) have emerged as a popular approach for these tasks; however, they suffer from limitations such as inefficient hardware utilization and over-smoothing. Recent advancements in neuromorphic computing offer promising solutions to these challenges. In this work, we evaluate two such neuromorphic strategies known as reservoir computing and hyperdimensional computing. We compare the performance of both approaches for bandgap classification and regression using a subset of the Materials Project dataset. Our results indicate recent advances in hyperdimensional computing can be applied effectively to better represent molecular graphs.

Gobin, Derek [George Mason University, Virginia]↗
DOE OSTI2025

Outflowing photoionized plasma in Circinus X-1 using the high-resolution X-ray spectrometer Resolve onboard XRISM and the radiative transfer code cloudy

High-resolution X-ray spectroscopy is a key to understanding the mass inflow and outflow of compact objects. Spectral lines carry information about the ionization, density, and velocity structures through their intensity ratios and profiles. They are formed in non-local thermodynamic equilibrium conditions under the intense radiation field from the compact objects; thus radiative transfer (RT) calculation is a requisite for proper interpretations. We present such a study for a low-mass X-ray binary, Circinus X-1, from which the P Cygni profile was discovered using the X-ray grating spectrometer onboard Chandra. We observed the source using the X-ray microcalorimeter onboard XRISM at an orbital phase of 0.93–0.97 and revealed many spectral features unidentified before: the higher series transitions ($n{\rightarrow }1$; $n>2$) of highly ionized (H- and He-like) S, Ca, Ar, and Fe in emission and absorption, the Fe K$\alpha$ and K$\beta$ inner-shell excitation absorption of mildly ionized (O- to Li-like) Fe, and resolved fine-structure level transitions in the Fe Ly$\alpha$ and He$\alpha$ complexes. They blend with each other at different velocity shifts on top of apparently variable continuum emission that changed its flux by an order of magnitude within a 70 ks telescope time. Despite such complexity in the observed spectra, most of them can be explained by a simple model consisting of the photoionized plasma outflowing at $\sim$300 km s$^{-1}$ and the variable blocking material in the line of sight of the incident continuum emission from the accretion disk. We demonstrate this with the aid of the RT code cloudy for the line ratio diagnostics and spectral fitting. We further constrain the physical parameters of the outflow and argue that the outflow is launched close to the outer edge of the accretion disk and can be driven radiatively by being assisted by the line force calculated using the RT simulation.

X-rays: binaries↗
DOE OSTI2025

XRISM high-resolution X-ray spectroscopy of Cygnus X-1: Highly ionized iron absorption structures

We present the first high-resolution X-ray spectral analysis of Cygnus X-1 using XRISM. The observation wa3s carried out from 2024 April 7 to 10, covering the orbital phase range 0.65–0.17 during its low/hard state. Taking advantage of the exceptional energy resolution of the Resolve instrument, we examined highly ionized iron absorption lines and characterized the ionization states, column densities, and line-of-sight velocities of the absorbing plasma. Spectral analysis revealed an ionization parameter of $\xi \sim 3$, column densities of a few $\times 10^{21}$ cm$^{-2}$, and a blueshifted velocity of $\sim$100 km s$^{-1}$. The observation was divided into two phases: before and after orbital phase $\phi _{\rm {orb}} = 0.9$, corresponding to non-dipping and dipping intervals. While only weak absorption features were present before $\phi _{\rm {orb}} = 0.9$, strong absorption by He-like and H-like Fe appeared during the dipping phase. We measured equivalent widths of 2.3, 0.4, and 1.2 eV for He-like Fe K$\alpha$ and H-like Ly$\alpha _1$ and Ly$\alpha _2$, respectively—demonstrating the capability of XRISM Resolve to securely detect narrow absorption features of only a few eV. These measurements trace the motion of the absorbing material and offer insight into the kinematics and spatial distribution of the wind in the vicinity of the black hole. These findings enhance our understanding of wind-fed accretion in Cygnus X-1 and highlight the importance of continued high-resolution X-ray observations to further constrain the physical properties of winds and accretion flows in high-mass X-ray binaries.

Astronomy and AstroPhysics↗
DOE OSTI2024

A Study of Slow-mode Shocks in the Near-Earth Magnetotail with MMS Observations and Hybrid Simulations

The structure of the magnetic reconnection boundary, particularly the presence of slow-mode shocks in the near-Earth magnetotail was studied by using magnetospheric multiscale (MMS) observations and 2.5D hybrid simulations. A total of 51 crossings of MMS from 2017 to 2021 were analyzed. We found that the detection percentage of slow-mode shocks in the near-Earth magnetotail is 41%–55%. Previous studies have only reported one slow-mode shock event in the near-Earth magnetotail and a slow-mode shock detection percentage of 10% or lower in the mid-to-distant magnetotail. It was observed that if the high-energy beam region data is removed from the slow-mode shock downstream observations then the detection of slow-mode shocks reduces, implying that the kinetic effects play an important role in the detection of slow-mode shocks. For the crossings where the interface was not identified as a slow-mode shock, it was found that the turbulence in those crossings can change the mass flux values and disrupt the detection of slow-mode shock. However, the macroscopic slow-mode shock-like structure stably exists around the magnetic reconnection interface, as most of the conditions for slow-mode shocks were satisfied. This result suggests that slow-mode shocks are a general feature of magnetic reconnection geometry. We find that the lack of detection of slow-mode shocks in previous observations and simulations can be explained by taking into account the kinetic structure of slow-mode shocks and the presence of turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The phototrophic purple non‐sulfur bacteria Rhodomicrobium spp. are novel chassis for bioplastic production

Abstract Petroleum‐based plastics levy significant environmental and economic costs that can be alleviated with sustainably sourced, biodegradable, and bio‐based polymers such as polyhydroxyalkanoates (PHAs). However, industrial‐scale production of PHAs faces barriers stemming from insufficient product yields and high costs. To address these challenges, we must look beyond the current suite of microbes for PHA production and investigate non‐model organisms with versatile metabolisms. In that vein, we assessed PHA production by the photosynthetic purple non‐sulfur bacteria (PNSB) Rhodomicrobium vannielii and Rhodomicrobium udaipurense. We show that both species accumulate PHA across photo‐heterotrophic, photo‐hydrogenotrophic, photo‐ferrotrophic, and photo‐electrotrophic growth conditions, with either ammonium chloride (NH 4 Cl) or dinitrogen gas (N 2 ) as nitrogen sources. Our data indicate that nitrogen source plays a significant role in dictating PHA synthesis, with N 2 fixation promoting PHA production during photoheterotrophy and photoelectrotrophy but inhibiting production during photohydrogenotrophy and photoferrotrophy. We observed the highest PHA titres (up to 44.08 mg/L, or 43.61% cell dry weight) when cells were grown photoheterotrophically on sodium butyrate with N 2 , while production was at its lowest during photoelectrotrophy (as low as 0.04 mg/L, or 0.16% cell dry weight). We also find that photohydrogenotrophically grown cells supplemented with NH 4 Cl exhibit the highest electron yields – up to 58.89% – while photoheterotrophy demonstrated the lowest (0.27%–1.39%). Finally, we highlight superior electron conversion and PHA production compared to a related PNSB, Rhodopseudomonas palustris TIE‐1. This study illustrates the value of studying non‐model organisms like Rhodomicrobium for sustainable PHA production and indicates future directions for exploring PNSB metabolisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Delving into the depths of NGC 3783 with XRISM

We present our study of the X-Ray Imaging and Spectroscopy Mission (XRISM) observation of the Seyfert-1 galaxy NGC 3783. XRISM’s Resolve microcalorimeter has enabled, for the first time, a detailed characterization of the highly ionized outflows in this active galactic nucleus. Our analysis constrains their outflow and turbulent velocities, along with their ionization parameter (ξ) and column density (N H ). The high-resolution Resolve spectrum reveals a distinct series of Fe absorption lines between 6.4 and 7.8 keV, ranging from Fe XVIII to Fe XXVI. At lower energies (1.8−3.3 keV), absorption features from Si, S, and Ar are also detected. Our spectroscopy and photoionization modeling of the time-averaged Resolve spectrum uncovers six outflow components, five of which exhibit relatively narrow absorption lines with outflow velocities ranging from 560 to 1170 km s −1 . In addition, a broad absorption feature is detected, which is consistent with Fe XXVI outflowing at 14 300 km s −1 (0.05 c). The kinetic luminosity of this component is 0.8−3% of the bolometric luminosity. Our analysis of the Resolve spectrum shows that more highly ionized absorption lines are intrinsically broader than those of lower-ionization species, indicating that the turbulent velocity of the six outflow components (ranging from 0 to 3500 km s −1 ) increases with ξ. Furthermore, we find that the column density (N H ) of the outflows generally declines with the ionization parameter up to log ξ = 3.2 but rises beyond this point, suggesting a complex ionization structure. The absorption profile of the Fe XXV resonance line is intriguingly similar to UV absorption lines (Lyα and C IV) observed by the Hubble Space Telescope, from which we infer that the outflows are clumpy in nature. Our XRISM/Resolve results from lower- and higher-ionization regimes support a “hybrid wind” scenario in which the observed outflows have multiple origins and driving mechanisms. We explore various interpretations of our findings within active galactic nucleus wind models.

X-rays: galaxies↗
DOE OSTI2025

SITCOMTN-154: Initial studies of photometric redshifts with LSSTComCam from DP1

This technote holds reports based on the first analyses of the Data Preview 1 (DP1) data by the Science Unit for photometric redshifts. Although photometric redshifts are not an official DP1 data product, the "Photo-z Science Unit" generated photo-z estimates for every galaxy in DP1 using the available multi-band imaging on a best-effort basis. This work included developing training and test datasets by matching DP1 data to high-quality reference redshifts obtained with spectroscopy, Grism data, and multi-band photometry. The Science Unit used the RAIL software package to make photometric redshift estimates using eight different algorithms, developed simple scientific performance metrics, used those metrics to explore how the performance of the algorithms varied with configuration changes, derived more optimized configurations of the algorithms and tested the performance of those configurations. This work, the resulting data products and expected data distribution mechanism are all described there.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Accelerating Discovery of Atomistic Defects via Machine Learning

The quantification of defects such as vacancies in crystalline structures is a cornerstone of materials science research. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within a crystalline lattice, aiming to expedite detection while improving accuracy. Additionally, we explore the transferability of these ML techniques, identifying characteristics of atomistic imaging data that complicate this task. We show how the integration of ML can drive innovation, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2D materials↗
DOE OSTI2024

Coulomb Interaction-Driven Entanglement of Electrons on Helium

The generation and evolution of entanglement in many-body systems is an active area of research that spans multiple fields, from quantum information science to the simulation of quantum many-body systems encountered in condensed matter, subatomic physics, and quantum chemistry. Motivated by recent experiments exploring quantum information processing systems with electrons trapped above the surface of cryogenic noble gas substrates, we theoretically investigate the generation of entanglement between two electrons via their unscreened Coulomb interaction. The model system consists of two electrons confined in separate electrostatic traps that establish microwave-frequency quantized states of their motion. We compute the motional energy spectra of the electrons, as well as their entanglement, by diagonalizing the model Hamiltonian with respect to a single-particle Hartree product basis. We also compare our results with the predictions of an effective Hamiltonian. The computational procedure outlined here can be employed for device design and guidance of experimental implementations. In particular, the theoretical tools developed here can be used for fine-tuning and optimization of control parameters in future experiments with electrons trapped above the surface of superfluid helium or solid neon. Published by the American Physical Society 2024

Physics↗
DOE OSTI2025

Report for the 2024 ASCR Workshop on Energy-Efficient Computing for Science

In September 2024, the US Department of Energy’s Advanced Scientific Computing Research pro gram convened a Workshop on Energy-Efficient Computing for Science to address the critical research challenges and opportunities in this field. The workshop brought together experts from academia, government, and industry to explore innovative approaches to improve energy efficiency across the computing stack over the next two decades. Participants identified five priority research directions (PRDs) that emphasize the need for a holistic approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

MSD CoP Webinar: "Advances in MSD-LIVE to Support the MSD Community of Practice"

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Advances in MSD-LIVE to Support the MSD Community of Practice Presenters: Casey Burleyson and Zoe Guillen (Pacific Northwest National Laboratory) Abstract: The MultiSector Dynamics Living, Intuitive, Value-adding, Environment (MSD-LIVE; msdlive.org) is a cloud-based data management system and advanced computing platform that enables MSD researchers to document and archive their data, run their models and analysis tools, and share their data, software, and workflows within the MSD Community of Practice. Recently, several high-profile datasets have attracted many new users to MSD-LIVE. This webinar has two goals: 1) To refamiliarize the MSD community and new users with the components of the platform (e.g., the data repository, model training notebooks, and data dashboards) and to highlight examples of how these components are advancing MSD science and 2) To demonstrate new features in v3 of the platform, released in late 2025. The main new feature in v3 is the ability to interactively explore data in MSD-LIVE without downloading it. MSD-LIVE users can now click a button in our data repository and launch a blank Jupyter notebook with access to the underlying data on AWS. Users can use the notebook to write analysis, visualization, or subsetting routines that process the data directly on the AWS cloud. We also added a GitHub integration feature that allows users to share analysis or visualization code they develop with the community of MSD-LIVE users. The webinar will wrap up with a look at what's coming next for MSD-LIVE in 2026. Moderator: Patrick M. Reed (MSD CoP Facilitation Team) This webinar was held on: May 12th, 2026 from 1-2 PM EST.

Open Science↗
DOE OSTI2025

Altermagnetism in NiSi and Antiferromagnetic Candidate Materials with Non‐Collinear Spins

Recently, a new class of magnetic phenomenon, called altermagnetism, is proposed where the underlying spin configuration resembles antiferromagnetic structure, but the system violates PT (PT: Parity times Time reversal) symmetry due to the alternation of crystalline symmetry across magnetic ions. Although the original idea is proposed for the collinear spin structure, a recent report by Cheong et al. has suggested that antiferromagnetic materials with non-collinear spin structure and local alternation of crystalline arrangement can also manifest altermagnetism. Besides breaking the PT symmetry, altermagnetic compounds are also expected to exhibit anomalous Hall effects of odd orders. Here, possible candidates are discussed in this regard. One example is nickel monosilicide, which is recently shown to exhibit high temperature antiferromagnetism with non-collinear spin structure. It fulfills both criteria of breaking the PT symmetry and manifesting nonlinear anomalous Hall effect. In addition to NiSi, other potential antiferromagnetic materials are also discussed with non-collinear spin configuration for the exploration of altermagnetic states.

altermagnetism↗