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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Quantum Software Engineering (Dagstuhl Seminar 24512)

The Dagstuhl Seminar 24512 on "Quantum Software Engineering" was held from December 15 to 20, 2024. It brought together 26 participants from industry and academia from 13 different countries, including senior and junior researchers as well as practitioners in the field of Quantum Software Engineering. The aim of the seminar was to advance software engineering methods and tools for the engineering of hybrid quantum systems by promoting personal interaction and open discussion among researchers who are already working in this emerging area of knowledge. The first day of the seminar was devoted to the topic "When software engineering meets quantum mechanics", while the second day focused on "Quantum software engineering and its challenges." During both days, 16 invited presentations were given. The rest of the seminar was organized into three working groups to address the topics "Quantum Software Design, Modelling and Architecturing", "Adaptive Hybrid Quantum Systems", and "Quantum Software Quality Assurance". The seminar was a very fruitful experience for all participants both in terms of scientific outcomes and in terms of the personal relationships that were generated to jointly address future experiences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

An Educational Program on Concentrated Solar Power and Heliostats for Power Generation and Industrial Processes

The objective of this project was to design and implement a comprehensive educational and applied research program in Concentrated Solar Thermal Power (CSTP) and heliostat technologies at Northeastern University. In alignment with the U.S. Department of Energy's Heliostat Consortium (HelioCon) goals, the project aimed to expand student and public understanding of CSTP systems while simultaneously contributing to workforce development and the broader decarbonization strategy. A particular emphasis was placed on integrating hands-on student design projects and publicly disseminating educational content relevant to CSTP systems. The project addressed a critical gap in renewable energy education: CSTP and heliostats, despite their importance in utility-scale solar energy, are rarely included in standard mechanical engineering programs. This project established new pathways for students to engage with the topic through the creation of a 4-credit graduate/senior elective course, development of five industry-facing short courses, and the inclusion of CSTP-based capstone design projects. Over two academic years, 36 students across six senior design teams developed and tested technologies such as deformable heliostats, beacon-based tracking systems, and solar-powered pyrolizers for biomass-to-biochar conversion. Concurrently, 30 undergraduate and graduate students were enrolled in the new academic course centered around CSTP principles. To ensure the relevance and accessibility of the short course content, the project team engaged with industry professionals, technical policy stakeholders, and potential course participants through structured surveys and informal consultations. Feedback from 28 respondents guided the structure, length, and delivery format of the courses - resulting in a modular design broken into five workshops. The feedback emphasized the need for flexible, asynchronous delivery and practical case studies, particularly in areas such as heliostat control, thermal storage, and solar fuel production. This engagement helped align the courses with the evolving knowledge demands of the renewable energy workforce and ensured that participants from both technical and policy backgrounds could meaningfully benefit from the material. The research and educational activities advanced the understanding of heliostat control systems, optical performance under misalignment, and thermal system integration in solar-driven pyrolysis applications. Methods and designs explored in this project proved to be both technically effective and economically feasible at the lab scale. Prototypes were constructed using commercially available components and custom-fabricated elements, demonstrating that meaningful performance improvements can be achieved with modest material and fabrication costs, supporting the feasibility of student-led research in this field. The public benefit of this project is twofold. First, it cultivates a pipeline of engineers trained to be familiar with CSTP principles, an essential workforce need identified by the Department of Energy for achieving its 2030 cost and deployment targets. Second, it contributes openly accessible educational materials, course content, and experimental frameworks to the broader community, enabling other institutions to adopt or adapt similar programming. Through outreach activities, curriculum integration, and technical exposure, this project contributes to a more informed and capable renewable energy workforce while supporting innovation in heliostat and CSTP system design. A new technical report is being prepared to document the development of the course and its outcomes, with plans to publish it in the ASME Open Access Journal of Engineering to ensure global accessibility, free of cost.

14 SOLAR ENERGY↗
DOE OSTI2025

Liquid Metals for Advanced Batteries: Recent Progress and Future Perspective

ABSTRACT The shift toward sustainable energy has increased the demand for efficient energy storage systems to complement renewable sources like solar and wind. While lithium‐ion batteries dominate the market, challenges such as safety concerns and limited energy density drive the search for new solutions. Liquid metals (LMs) have emerged as promising materials for advanced batteries due to their unique properties, including low melting points, high electrical conductivity, tunable surface tension, and strong alloying tendency. Enabled by the unique properties of LMs, four key scientific functions of LMs in batteries are highlighted: active materials, self‐healing, interface stabilization, and conductivity enhancement. These applications can improve battery performance, safety, and lifespan. This review also discusses current challenges and future opportunities for using LMs in next‐generation energy storage systems. image

Zheng, Tianrui [Materials Science and Engineering ↗
DOE OSTI2025

Dynamics of disordered intermediates during the two-electron alkaline MnO 2 conversion reaction for grid-scale batteries

Battery technologies beyond Li-ion are likely needed for extensive integration of grid-scale storage. The rechargeable Zn-MnO 2 chemistry has the potential for high sustainability, high safety, and low cost, using Earth-abundant basis materials. In an alkaline electrolyte, the MnO 2 cathode can cycle reversibly if modified by including a Bi-containing additive, although the cycling mechanism remains mostly unknown. This work presents an account of the intermediate species involved in the electrochemical transformation from layered δ-MnO 2 to Mn(OH) 2 and back. During charge, a disordered intermediate with a structure resembling layered β-MnOOH exists stably for an extended period, corresponding to a regime known to have unexpected electrochemical activity of Bi. During discharge, β-MnOOH exists only briefly and is never the majority material, revealing that the cycling mechanism is asymmetric. In conclusion, these findings represent a significant advance in mechanistic knowledge and can enable engineering to develop the system for commercial use.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Magnetic resonance control of spin-correlated radical pair dynamics in vivo

Magnetic fields can influence reactions involving spin-correlated radical pairs (SCRPs). This provides a mechanism by which both static and time-varying magnetic fields can affect living systems at the biomolecular level. However, an engineered SCRP system conferring magnetic sensitivity to a non-native biochemical process in a multicellular organism has not yet been demonstrated. Here, in this study, we demonstrate control of SCRP dynamics using magnetic resonance in a live transgenic animal. We show that the emission of various red fluorescent proteins (RFPs), in the presence of a flavin cofactor, can be modified by a combination of static and radiofrequency magnetic fields applied near the electron spin resonance frequency. This effect was measured at room temperature both in vitro and in the nematode Caenorhabditis elegans, genetically modified to express the RFP mScarlet. These observations suggest that the magnetic field effects measured in RFP-flavin systems are due to quantum-correlated radical pairs with a coherence time larger than 4 ns. Our experiments demonstrate that radiofrequency magnetic fields can influence dynamics of reactions involving SCRPs in vivo, potentially enabling new methods for remotely controlling biomolecular processes, such as gene expression, and suggest broader potential for quantum tools in biology.

Burd, Shaun C. [Stanford Univ., CA (United States)↗
DOE OSTI2026

Primary Heat Transport System Design Considerations for Xcimer Energy’s Athena Fusion Pilot Plant

Fusion energy promises a reliable, carbon-free source of power; however, significant challenges remain before it can be deployed as an economical energy source. In addition to achieving fusion conditions, power plants must operate under extreme temperatures, radiation, and mechanical loads while maintaining high efficiency and availability. These requirements place strong demands on engineering design and plant operation. This work focuses on the engineering challenges associated with balance of plant analysis for inertial fusion energy systems. In particular, this paper examines the design considerations for primary heat transfer systems in fusion pilot plants employing molten fluoride salt coolants, with particular emphasis on system layout optimization and the balance between competing design objectives using the Xcimer Energy Athena inertial pilot plant design as a case study. Through systematic analysis of candidate system configurations and parametric sensitivity studies, we identify key engineering trade-offs governing salt inventory, pumping power requirements, and operational flexibility. The analysis employs system-level modeling tools to explore the design space and establish relationships between geometric parameters and system performance metrics.

Greenwood, Scott [ORNL] (ORCID:0000000333480736)↗
DOE OSTI2024

Combustion-Pele: An Exascale Capability for Improving Engine Design

Combustion, the complex chemical reaction made possible by igniting a mixture of fuel and oxygen to produce heat and light, serves as the nation’s primary source of power generation and the linchpin of the transportation industry. For more than 100 years, internal combustion engines (ICEs) have been converting energy from the burning of fuel—gasoline, for example—into a mechanical process that makes vehicles move. Recently, ICEs have come under heavy scrutiny for their contribution to greenhouse gas emissions, yet combustion-based systems are projected to dominate the marketplace for decades. Exascale systems are helping researchers design new high-efficiency, low-emission combustion engines that operate at much lower temperatures to maintain the nation’s energy security and limit negative environmental impacts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Revealing the three-dimensional arrangement of polar topology in nanoparticles

In the early 2000s, low dimensional ferroelectric systems were predicted to have topologically nontrivial polar structures, such as vortices or skyrmions, depending on mechanical or electrical boundary conditions. A few variants of these structures have been experimentally observed in thin film model systems, where they are engineered by balancing electrostatic charge and elastic distortion energies. However, the measurement and classification of topological textures for general ferroelectric nanostructures have remained elusive, as it requires mapping the local polarization at the atomic scale in three dimensions. Here we unveil topological polar structures in ferroelectric BaTiO3 nanoparticles via atomic electron tomography, which enables us to reconstruct the full three-dimensional arrangement of cation atoms at an individual atom level. Our three-dimensional polarization maps reveal clear topological orderings, along with evidence of size-dependent topological transitions from a single vortex structure to multiple vortices, consistent with theoretical predictions. The discovery of the predicted topological polar ordering in nanoscale ferroelectrics, independent of epitaxial strain, widens the research perspective and offers potential for practical applications utilizing contact-free switchable toroidal moments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Graph-Based Modeling for the Detection and Tracking of Sarin-Surrogate-Induced Neurotoxicity Using a Human-Relevant, In-Vitro Brain Model

Organophosphorus (OP) nerve agents are a chemical threat to the United States, to the civilian population (e.g., pesticides) and historically weaponized (e.g., sarin) as chemical warfare agents. The unprecedented, accelerated process from “bench-to-bedside” during the SARSCov2 pandemic has made it clear that technology and tools need to be readily available for immediate response. Advances in human organ tissue mimetic systems are a promising technology to evaluate the human-relevant response in vitro for basic and applied research and drug screening. In particular, current brain microphysiological systems (MPS) have the capability to monitor and detect changes in engineered human neural circuit activity. However, current data analytics approaches for these systems lack the granularity to functionally detect and distinguish the different mechanisms that occur in the brain following neurotoxicity, injury, and disease. The goal of this project was to advance the computational analytical capabilities of the brain MPS to detect functional changes in neural circuit structure at different stages of Sarin surrogate-induced neurotoxicity. We developed graph-based models to (1) identify the composition of the neural circuit structure; (2) detect and monitor how this structure changes following sarin-induced neurotoxicity; and (3) evaluate the analytical pipeline using known/promising oxime reactivators. Through experiments on the bMPS where in vitro neuronal cultures were exposed to a sarin surrogate, we demonstrated the capabilities of our computational pipeline to identify different responses in the functional networks of brain cells exposed to low and high concentrations of the nerve agent. We identified a biphasic response of human neural network activity following exposure to a sarin-surrogate that had not been reported in the literature before. The graph-based models and software developed in this project can be used for future studies that leverage the brain MPS technology, such as treatment efficacy assessment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Bridging Cloud and Edge Computing at NREL Using CONNECT: Cloud Optimized Networking for Next-Gen Edge Computing Technologies [Slides]

CONNECT is an innovative on-premise hardware and software solution that integrates edge and cloud computing infrastructure at NREL. Built on the AWS Greengrass middleware and leveraging the MQTT protocol, CONNECT enables real-time data streaming from IoT devices and gateways to both cloud and local services, empowering researchers to rapidly capture, analyze, and act upon edge-generated data while leveraging cloud capabilities. The platform addresses research infrastructure challenges by providing a pre-approved platform which is already configured with the correct networking and cybersecurity baselines thus eliminating procurement delays and enabling on-demand availability. CONNECT's hybrid architecture efficiently manages burstable workloads, allowing research teams to dynamically scale computational capacity, handle peak data loads, and reduce operational bottlenecks. Advanced capabilities include built-in GPU support for executing machine learning models which enables low-latency inference at the edge from models trained in the cloud. This architecture supports real-time analytics and filtering, providing a mechanism to allow only transmitting and processing high-value data. Cloud-based configuration management permits engineers to manage on-premise systems remotely, optimizing operational efficiency. By bridging edge and cloud computing, CONNECT provides NREL researchers with a flexible, scalable platform that accelerates scientific discovery while maintaining robust security and performance standards.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Engineering tertiary chirality in helical biopolymers

Tertiary chirality describes the handedness of supramolecular assemblies and relies not only on the primary and secondary structures of the building blocks but also on topological driving forces that have been sparsely characterized. Helical biopolymers, especially DNA, have been extensively investigated as they possess intrinsic chirality that determines the optical, mechanical, and physical properties of the ensuing material. Here, we employ the DNA tensegrity triangle as a model system to locate the tipping points in chirality inversion at the tertiary level by X-ray diffraction. We engineer tensegrity triangle crystals with incremental rotational steps between immobile junctions from 3 to 28 base pairs (bp). We construct a mathematical model that accurately predicts and explains the molecular configurations in both this work and previous studies. Our design framework is extendable to other supramolecular assemblies of helical biopolymers and can be used in the design of chiral nanomaterials, optically active molecules, and mesoporous frameworks, all of which are of interest to physical, biological, and chemical nanoscience.

Science & Technology - Other Topics↗
DOE OSTI2026

Design and Development of the Handling Frame Assembly Table for the National Ignition Facility Blast Shields

The Handling Frame Assembly Table is a custom designed piece of equipment developed to support the NIF Sustainment Project. The goal of the NIF Sustainment Project is to refurbish the National Ignition Facility (NIF), the world’s largest and most energetic laser, so it can continue advancing research in fusion energy, national security, and high energy density physics. A key aspect of this effort involves replacing all 1,728 blast shields on the NIF, which requires specialized equipment such as the Handling Frame Assembly Table to support the production of new blast shields. This project follows a systems engineering approach that guides the design sequence. This report documents the design process from initial concept through final design, including stakeholder analysis, requirements development, conceptual design, final design, and design validation. Future work will focus on building and commissioning the system.

42 ENGINEERING↗
DOE OSTI2026

Photodynamic melting of phase-reversed charge stripes and enhanced condensation

The interplay between charge stripes and pairing has long been a subject of scrutiny in a broad class of unconventional superconductors, as in some cases it is unclear whether this interplay benefits the ensuing superfluidity. Experiments that explore the out-of-equilibrium dynamics of these systems aim to tip the balance toward one phase or the other by selectively coupling to relevant modes. Leveraging the fact that competition between stripes and pairing is not exclusive to fermionic systems, we explore the photoirradiation dynamics of interacting hardcore bosons in which density-wave phase-reversal melting leads to enhanced phase-coherent transport response, as quantified by the dynamic amplification of both the zero-momentum occupancy and the condensate fraction, as well as finite out-of-equilibrium charge stiffness and superfluid weight, for a given system size. Finally, our results, obtained using unbiased methods for an interacting system on a ladder geometry, demonstrate how one can engineer time-dependent perturbations to release suppressed orders, potentially providing insight into the underlying mechanism in related experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Scripts for Surface Fluxes Paper

SAND2025-10129O Scripts for Surface Fluxes Paper uses Matlab scripts and plots to investigate surface coupling mechanisms between the atmosphere and the ocean in Earth system models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Guba, Oksana [Sandia National Lab. (SNL-CA), Liver↗
DOE OSTI2025

An accumulation method for early fault warning and its application to wind turbine systems

Unexpected failures in engineering systems lead to expensive maintenance actions and should be avoided if at all possible. This is particularly true for wind turbine systems for which unexpected failures not only demand costly repairs but also cause long downtime. Motivated by this need, we present an accumulation method for fault early warning and failure anticipation. Here, our research shows that one critical element allowing the ability of early warning is to accumulate the small-magnitude symptoms resulting from gradual changes in an engineering system like wind turbines. Our idea is inspired by the classical cumulative sum method, or CUSUM, but we have to redesign the accumulation mechanism for tackling unique challenges in wind turbine data. The new accumulation method is applied to two real wind turbine datasets, one with gearbox failures and the other with generator failures, and demonstrates superior performance as compared with CUSUM.

17 WIND ENERGY↗
DOE OSTI2024

Catalytic enhancement in the performance of the microscopic two-stroke heat engine

Here we consider a model of heat engine operating in the microscopic regime: the two-stroke engine. It produces work and exchanges heat in two discrete strokes that are separated in time. The working body of the engine consists of two d-level systems initialized in thermal states at two distinct temperatures. Additionally, an auxiliary nonequilibrium system called catalyst may be incorporated with the working body of the engine, provided the state of the catalyst remains unchanged after the completion of a thermodynamic cycle. This ensures that the work produced by the engine arises solely from the temperature difference. Upon establishing the rigorous thermodynamic framework, we characterize twofold improvement stemming from the inclusion of a catalyst. Firstly, we prove that in the noncatalytic scenario, the optimal efficiency of the two-stroke heat engine with a working body composed of two-level systems is given by the Otto efficiency, which can be surpassed by incorporating a catalyst with the working body. Secondly, we show that incorporating a catalyst allows the engine to operate in frequency and temperature regimes that are not accessible for noncatalytic two-stroke engines. We conclude with a general conjecture about the advantage brought by a catalyst: including the catalyst with the working body always allows to improve efficiency over the noncatalytic scenario for any microscopic two-stroke heat engines. We prove this conjecture for two-stroke engines where the working body is composed of two d-level systems initialized in thermal states at two distinct temperatures, as long as the final joint state leading to optimal efficiency in the noncatalytic scenario is not a product state, or at least one of the d-level system is not thermal.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Adsorption-Induced Surface Magnetism

We report the emergence of adsorption-induced magnetism from heterohelicene molecules on a nonmagnetic Cu(100) surface. Spin-polarized low-energy electron microscopy measurements reveal spin-dependent electron reflectivity for enantiopure 7,12,17-trioxa[11]helicene (TO[11]H) monolayers, indicating the formation of a spin-polarized state localized in the topmost copper layer. Control experiments on clean Cu(100) and TO[11]H on highly oriented pyrolytic graphite show no such effect, excluding artifacts and chirality-induced spin selectivity as origins. Spin-polarized density functional theory calculations with hybrid functionals attribute the magnetism to strong chemisorption, which induces hybridization between the molecular HOMO and copper s- and d-states, driving asymmetric spin-polarized charge redistribution at the interface. An extended Newns-Anderson-Grimley model incorporating on-site Coulomb repulsion in Cu d-orbitals reproduces the emergence of interfacial spin polarization above a threshold interaction strength, highlighting the key roles of hybridization parameters and Coulomb correlation. These findings reveal a mechanism for inducing magnetism at molecule-metal interfaces without inherently magnetic components, offering avenues for engineering spin-polarized states in organic-inorganic hybrid systems.

Hubbard model↗
DOE OSTI2025

DS-TIDE: Harnessing Dynamical Systems for Efficient Time-Independent Differential Equation Solving

Time-Independent Differential Equations (TIDEs) are central to modeling equilibrium behavior across a wide range of scientific and engineering domains, from electrostatics to porous media flow. Conventional numerical solvers offer reliable solutions but incur significant computational costs due to fine-grained discretization and iterative procedures. Machine learning-based approaches address this by replacing iterative solving processes with one-time inference; however, their sophisticated models require extensive training resources that often exceed those of traditional solvers. Consequently, designing a TIDE solver that achieves high accuracy, broad applicability, and exceptional computational efficiency remains a fundamental challenge. In this paper, we propose DS-TIDE, a novel hardware solver that is inspired by, and subsequently leverages, the intrinsic connection between Dynamical Systems (DS) and Differential Equations (DEs) to efficiently and accurately solve TIDEs. DS-TIDE employs a CMOS-compatible DS-based processor, whose physical states evolve under carefully designed DE-driven dynamics and naturally converge to equilibrium -- the solution of the target TIDE -- within ~1µs on a ~1-watt DS-TIDE processor. To enhance expressivity, DS-TIDE incorporates Heterogeneous Dynamics with Temporal Layering (HDTL), which solves TIDEs through a three-stage DS evolution -- conditioning, solving, and decoding -- each governed by specialized dynamics. The entire evolution process is analogous to an infinitely deep neural network temporally unrolled, offering the system the capability of representing complex equations. Furthermore, DS-TIDE is equipped with an on-device DS-DE Auto-Alignment mechanism that dynamically adapts intrinsic hardware dynamics within milliseconds, effectively aligning the system’s dynamics to diverse target DEs. Experimental results across TIDEs from a wide range of scientific and engineering domains demonstrate that DS-TIDE achieves ~10^3× speedup, ~10^5× energy savings, and competitive or superior accuracy compared to state-of-the-art numerical and ML-based solvers.

Liu, Chuan↗