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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
NASA NTRSDate not supplied

The Benefit of NASA's Atmosphere Observing System (AOS) Mission Lidar and Polarimeter Observations for Health and Air Quality Applications

The Atmosphere Observing System (AOS) seeks to explore fundamental questions of how interconnections between aerosols, clouds and precipitation impact our weather and climate, addressing real-world challenges to benefit society. AOS will provide key information to enhance the communities’ ability to improve weather and air quality forecasting today, seasonal to sub-seasonal changes in the near future, and societal challenges resulting from climate change in the decades to come. A fundamental component of the AOS mission is ensuring that health and air quality applications are considered to the greatest extent possible in mission design. As a result, the Applications Impact Team (AIT) was implemented to address this objective. The overarching goal of the AIT is to help improve the capacity for transitioning science to applications to make it possible to more quickly and effectively inform decisions that will directly benefit society. We seek to maximize AOS benefit to impact decisions through early engagement in the mission development phase in order to prepare stakeholders to apply observations as soon as AOS mission data becomes available. To support these efforts, we leverage existing and near future mission applications activities and initiatives, such as the NASA CALIPSO, MAIA, TEMPO, and PACE missions to form a framework to enhance health and air quality applications for AOS. The unique synergy between lidar and polarimeter instruments onboard the AOS constellation, as well as diurnally varying observations of aerosol profiles, will provide new opportunities to engage health and air quality stakeholders for forecasting, monitoring, and warning of hazardous events (e.g., wildfire smoke, volcanic ash) that impact human health. Engaging with existing missions helps identify and understand data needs, gaps and opportunities for current and future stakeholders, determine what aerosol data products are of highest value and use, and helps connect stakeholders with current mission data that can serve as AOS proxy data, among others. In this presentation, we provide an overview of AOS aerosol observations relevant for health and air quality applications, AIT activities and initiatives and how existing aerosol satellite missions and their applications activities can play a critical role in AOS applications development during mission design.

Melanie Follette-Cook↗
NASA NTRS1999

Integrated Avionics System (IAS), Integrating 3-D Technology On A Spacecraft Panel

As spacecraft designs converge toward miniaturization, and with the volumetric and mass challenges placed on avionics, programs will continue to advance the "state of the art" in spacecraft system development with new challenges to reduce power, mass and volume. Traditionally, the trend is to focus on high-density 3-D packaging technologies. Industry has made significant progress in 3-D technologies, and other related internal and external interconnection schemes. Although new technologies have improved packaging densities, a system packaging architecture is required that not only reduces spacecraft volume and mass budgets, but increase integration efficiencies, provide modularity and flexibility to accommodate multiple missions while maintaining a low recurring cost. With these challenges in mind, a novel system packaging approach incorporates solutions that provide broader environmental applications, more flexible system interconnectivity, scalability, and simplified assembly test and integration schemes. The Integrated Avionics System (IAS) provides for a low-mass, modular distributed or centralized packaging architecture which combines ridged-flex technologies, high-density COTS hardware and a new 3-D mechanical packaging approach, Horizontal Mounted Cube (HMC). This paper will describe the fundamental elements of the IAS, HMC hardware design, system integration and environmental test results.

Hunter, Don J.↗
DOE OSTI2020

Comparison of Thermal Management Approaches for Integrated Traction Drives in Electric Vehicles

The continuous push to increase power densities of electric vehicle (EV) traction drive systems necessitates combining electric motor and power electronics into one unit. A single, compact traction drive unit with fewer interconnecting components also facilitates fast, automated assembly of electric vehicles, driving production costs down and enabling wider adoption of EVs. There are a number of challenges associated with the integration of power electronics with the electric machine, including thermal management of the combined traction drive system. However, one important benefit of integration from the thermal management system perspective is the potential for using a single fluid loop instead of two separate cooling systems for the electric machine and the power electronics/inverter. This paper reviews several integration approaches and, employing finite element analysis (FEA), compares thermal management solutions for the combined electric machine and power electronics systems. Namely, three different scenarios are modeled: (1) independent component (motor and power electronics) cooling, which is compared to the combined cooling system approach for (2) radially and (3) axially integrated power electronics modules into the motor enclosure. Temperature distributions for selected thermal loads and thermal resistances from the key heat-generating components to the cooling fluid are compared for each scenario.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Ten years of spasers and plasmonic nanolasers

Ten years ago, three teams experimentally demonstrated the first spasers, or plasmonic nanolasers, after the spaser concept was first proposed theoretically in 2003. An overview of the significant progress achieved over the last 10 years is presented here, together with the original context of and motivations for this research. After a general introduction, we first summarize the fundamental properties of spasers and discuss the major motivations that led to the first demonstrations of spasers and nanolasers. This is followed by an overview of crucial technological progress, including lasing threshold reduction, dynamic modulation, room-temperature operation, electrical injection, the control and improvement of spasers, the array operation of spasers, and selected applications of single-particle spasers. Research prospects are presented in relation to several directions of development, including further miniaturization, the relationship with Bose–Einstein condensation, novel spaser-based interconnects, and other features of spasers and plasmonic lasers that have yet to be realized or challenges that are still to be overcome.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Emerging Threats and Technology Investigation: Industrial Internet of Things - Risk and Mitigation for Nuclear Infrastructure

Industries supporting the global nuclear infrastructure striving for cost savings, expansions in efficiency, and convenience are likely to adopt components (e.g., hardware, software) that comprise the Internet of Things (IoT) and Industrial Internet of Things (IIoT). These devices offer potential improvements along with security challenges. Modern conveniences achieved through application of technology have propagated through society in the form of interconnected devices, from doorbells to microwave ovens, commonly referred to as IoT. IoT devices are often Internet-connected devices that are designed to send data back to a cloud-based server, where a smart phone application then presents device status and control options. Home-based IoT applications carry a different set of risks when compared to a business or security environment, where there is also a history of convenience and interconnection. Industrial settings have long relied on specifically designed Supervisory Control and Data Acquisition (SCADA) systems for process control where IIoT devices are intended to inform business decisions and augment traditional processes. A recent National Institute of Standards and Technology (NIST) report provides a distinction between process control and IIoT in that traditional process control is not replaced by IIoT, but rather IIoT devices are intended to enhance industrial processes through additional monitoring of various sensors and application of data analytics models using artificial intelligence (AI) and machine learning (ML) (Fagan, Marron, et al. 2021) (Ross, et al. 2021).

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

Edge ML for CAN bus intrusion detection in AVs

Autonomous Vehicles (AVs) are revolutionizing transportation, but their reliance on interconnected cyber-physical systems exposes them to unprecedented cybersecurity risks. This study addresses the critical challenge of detecting real-time cyber intrusions in self-driving vehicles by leveraging a dataset from the Udacity self-driving car project. We simulate four high-impact attack vectors, Denial of Service (DoS), spoofing, replay, and fuzzy attacks, by injecting noise into spatial features (e.g., bounding box coordinates) to replicate adversarial scenarios. We develop and evaluate two lightweight neural network architectures (NN-1 and NN-2) alongside a logistic regression baseline (LG-1) for intrusion detection. The models achieve exceptional performance, with NN-2 attaining an AUC score of 93.15% and 93.15% accuracy, demonstrating their suitability for edge deployment in AV environments. Through explainable AI techniques, we uncover unique forensic fingerprints of each attack type, such as spatial corruption in fuzzy attacks and temporal anomalies in replay attacks, offering actionable insights for feature engineering and proactive defense. Visual analytics, including confusion matrices, ROC curves, and feature importance plots, validate the models' robustness and interpretability. This research sets a new benchmark for AV cybersecurity, delivering a scalable, field-ready toolkit for Original Equipment Manufacturers (OEMs) and policymakers. By aligning intrusion fingerprints with SAE J3061 automotive security standards, we provide a pathway for integrating machine learning into safety-critical AV systems. Our findings underscore the urgent need for security-by-design AI, ensuring that AVs not only drive autonomously but also defend autonomously. This work bridges the gap between theoretical cybersecurity and life-preserving engineering, offering a leap toward safer, more secure autonomous transportation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Nanotubes May Break Through "Chip Wall"

In 1965, just four years after the first planar integrated circuit (IC) was discovered, Cordon Moore observed that the number of transistors per integrated circuit had grown exponentially. He predicted that this would continue, and the media soon began to call his prophesy "Moore's Law" For nearly forty years, Moore's Law has been validated by the technological progress achieved in the semiconductor industry. Now, however, industry experts are warning of a "Red Brick Wall" that may soon block the continued scaling predicted by by Moore's Law. The "red bricks" in the wall are those areas of technical challenge for which no known manufacturable solution exists. One such "brick" is the challenge of finding a new material and processing technology to replace the metals used today to interconnect transistors on a chip.

Laufenberg, Larry↗
NASA NTRS2011

Bridging the Gap between NASA Hydrological Data and the Geospatial Community

There is a vast and ever increasing amount of data on the Earth interconnected energy and hydrological systems, available from NASA remote sensing and modeling systems, and yet, one challenge persists: increasing the usefulness of these data for, and thus their use by, the geospatial communities. The Hydrology Data and Information Services Center (HDISC), part of the Goddard Earth Sciences DISC, has continually worked to better understand the hydrological data needs of the geospatial end users, to thus better able to bridge the gap between NASA data and the geospatial communities. This paper will cover some of the hydrological data sets available from HDISC, and the various tools and services developed for data searching, data subletting ; format conversion. online visualization and analysis; interoperable access; etc.; to facilitate the integration of NASA hydrological data by end users. The NASA Goddard data analysis and visualization system, Giovanni, is described. Two case examples of user-customized data services are given, involving the EPA BASINS (Better Assessment Science Integrating point & Non-point Sources) project and the CUAHSI Hydrologic Information System, with the common requirement of on-the-fly retrieval of long duration time series for a geographical point

Rui, Hualan↗
NASA NTRS2015

Analysis of Advanced Thermoelectric Materials and Their Functional Limits

The world's demand for energy is increasing dramatically, but the best energy conversion systems operate at approximately 30% efficiency. One way to decrease energy loss is in the recovery of waste heat using thermoelectric (TE) generators. A TE generator is device that generates electricity by exploiting heat flow across a thermal gradient. The efficiency of a TE material for power generation and cooling is determined by the dimensionless Figure of Merit (ZT): ZT = S(exp. 2)sigmaT/κ: where S is the Seebeck coefficient, sigma is the electrical conductivity, T is the absolute temperature, and κ is the thermal conductivity. The parameters are not physically independent, but intrinsically coupled since they are a function of the transport properties of electrons. Traditional research on TE materials has focused on synthesizing bulk semiconductor-type materials that have low thermal conductivity and high electrical conductivity affording ZT values of 1. The optimization of the σ/κ ratio is difficult to achieve using current material formats, as these material constants are complementary. Recent areas of research are focusing on using nanostructural artifacts that introduce specific dislocations and boundary conditions that scatter the phonons. This disrupts the physical link between thermal (phonon) and electrical (electron) transport. The result is that κ is decreased without decreasing σ. These material formats give ZT values of up to 2 which represent approximately 18% energy gain from waste heat recovery. The next challenge in developing the next generation of TE materials with superior performance is to tailor the interconnected thermoelectric physical parameters of the material system. In order to approach this problem, the fundamental physics of each parameter S, sigma, and κ need to be physically understood in their context of electron/phonon interaction for the construction of new high ZT thermoelectric devices. Is it possible to overcome the physical limit imposed by of the effect of phonon lattice oscillation and energetic electrons towards thermal conductivity? Is the Seebeck coefficient, based on the difference in voltage over temperature gradient ( deltaV/deltaT), an intrinsic parameter of each material? All these parameters were manipulated using nano-bridge and twin-lattice structural concepts at the NASA Langley Research Center. This talk will review the current trend of TE research to optimize the ZT and discuss about new approaches on increasing ZT within functional limits of each parameter.

Kim, Hyun Jung↗
DOE OSTI2025

Experimental Validation of a 40kW, 480V Point-to-Point DC Interlinks for Controller-Agnostic, Interoperable Networked Microgrids

This paper presents the experimental validation of point-to-point dc-interlinks for interconnecting two solar-based, laboratory-scale AC microgrids. DC interlinks provide a solution to numerous technical and operational challenges encountered in networked microgrids, including precise power flow control, stable and fast synchronization, enhanced stability, and improved voltage and frequency regulation. By decoupling microgrids through power converters, dc-interlinks enable power exchange among microgrids that can be owned by different entities (such as communities, utilities, or universities) and managed by diverse microgrid controller vendors. This characteristic makes this dc-interlinks a promising solution for networking real-world microgrids. The presented point-to-point dc interlink utilizes two four-quadrant converters: a 40kW 3-phase ac/dc regulating the dc-link voltage to 800V, and a 3-phase dc/ac controlling power flow. These converters, connected via a 20-foot dc cable, interconnect two ac microgrids operating at 480V, each featuring energy storage, photovoltaic generation, and load emulation. Experimental validation employs commercially available off-the-shelf (COTS) converters and real-world data from solar-powered microgrids in Adjuntas, Puerto Rico. To the authors’ knowledge, this work provides the first at-scale experimental validation of dc-interlinks for networked ac microgrids using COTS inverters, demonstrating their practicality and effectiveness in addressing real-world operational challenges.

Ferrari Maglia, Max [ORNL]↗
NASA NTRS1993

Mass storage: The key to success in high performance computing

There are numerous High Performance Computing & Communications Initiatives in the world today. All are determined to help solve some 'Grand Challenges' type of problem, but each appears to be dominated by the pursuit of higher and higher levels of CPU performance and interconnection bandwidth as the approach to success, without any regard to the impact of Mass Storage. My colleagues and I at Data Storage Technologies believe that all will have their performance against their goals ultimately measured by their ability to efficiently store and retrieve the 'deluge of data' created by end-users who will be using these systems to solve Scientific Grand Challenges problems, and that the issue of Mass Storage will become then the determinant of success or failure in achieving each projects goals. In today's world of High Performance Computing and Communications (HPCC), the critical path to success in solving problems can only be traveled by designing and implementing Mass Storage Systems capable of storing and manipulating the truly 'massive' amounts of data associated with solving these challenges. Within my presentation I will explore this critical issue and hypothesize solutions to this problem.

Lee, Richard R.↗
DOE OSTI2026

Speed to Power: Solutions for Accelerating Large Load Connections

Rapid growth in demand from data centers and other large loads is creating a range of new challenges for electricity planners, investors, system operators, and regulators, leading to bottlenecks that have slowed connection of large loads to the electric grid. In response, innovative solutions for accelerating large load connections are beginning to emerge across the U.S. Drawing on an extensive document and literature review, this report identifies more than 40 potential solutions for accelerating large load connections, organized into five functional areas: load forecasting, interconnection, resource planning and procurement, markets and operations, and cost allocation and ratemaking. The five functional areas provide a framework for organizing challenges and solutions to large load connection bottlenecks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Impact of Quaternary Pumped Storage Hydropower on Frequency Response of U.S. Western Interconnection with High Renewable Penetrations

As renewable penetration increases in the United States, maintaining stability and reliability of low-inertia power grid by providing sufficient frequency control capability becomes a challenge. Advanced pumped storage hydro technologies (APSH) will be expected to play an important role for future grid as not only an energy supplier, but also as an ancillary services provider. This paper studies the impact of using quaternary pumped storage hydropower (Q-PSH), as one of the newly proposed APSH technology, to provide primary frequency response. To quantify the impact of Q-PSH on frequency response of the U.S. Western Interconnection, a user-defined dynamic model of Q-PSH is developed on the GE Positive Sequence Load Flow (PSLF) platform and is implemented in a set of detailed U.S. Western Electricity Coordination Council (WECC) planning cases in which renewable penetration levels are 20%, 40%, 60% and 80%. Simulation results show that Q-PSH can help improve frequency nadir and settling frequency comparing to the conventional PSH.

frequency response↗
DOE OSTI2023

Low-loss interconnects for modular superconducting quantum processors

Low-loss superconducting aluminium cables and on-chip impedance transformers can be used to link qubit modules and create superconducting quantum computing networks with high-fidelity intermodule state transfer. Scaling is now a key challenge in superconducting quantum computing. One solution is to build modular systems in which smaller-scale quantum modules are individually constructed and calibrated and then assembled into a larger architecture. This, however, requires the development of suitable interconnects. Here we report low-loss interconnects based on pure aluminium coaxial cables and on-chip impedance transformers featuring quality factors of up to 8.1 x 10 5 , which is comparable with the performance of our transmon qubits fabricated on a single-crystal sapphire substrate. We use these interconnects to link five quantum modules with intermodule quantum state transfer and Bell state fidelities of up to 99%. To benchmark the overall performance of the processor, we create maximally entangled, multiqubit Greenberger-Horne-Zeilinger states. The generated intermodule four-qubit Greenberger-Horne-Zeilinger state exhibits 92.0% fidelity. We also entangle up to 12 qubits in a Greenberger-Horne-Zeilinger state with 55.8 ± 1.8% fidelity, which is above the genuine multipartite entanglement threshold of 1/2.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Basic Research Needs for Inverse Methods for Complex Systems under Uncertainty

Inverse problems, which aim to infer unknown properties of a system using experimental and observational data, are central to addressing many of the U.S. Department of Energy’s (DOE) most critical scientific and engineering challenges. Accurate, computationally efficient, and data-efficient solutions to inverse problems are essential for advancing DOE mission-critical science drivers, including analyzing data from large-scale experimental facilities, optimizing fusion reactor performance, accelerating materials discovery, enhancing geophysical imaging, improving wildfire predictions, and enabling autonomous systems and digital twins. However, these problems are becoming increasingly complex, often involving nonlinear, highdimensional, and interconnected systems and models that span multiple physics and scales, while relying on data with varying quantity, quality, and information content. Compounding these challenges is the uncertainty inherent in DOE-relevant systems, where errors in inputs, noise in data, incompleteness of data, and discrepancies between models and reality constrain the accuracy and precision of solutions. At the same time, the convergence of recent scientific computing trends—scientific machine learning, artificial intelligence, and computing advances such as exascale computing—is creating unprecedented opportunities for tackling these challenges. The cross-cutting nature of inverse problems, combined with their growing complexity and rapidly evolving data and algorithmic demands, strongly motivates the formulation of a prioritized research agenda to maximize their capabilities and impact. In response to this need, DOE’s Advanced Scientific Computing Research (ASCR) program in the Office of Science convened the Workshop on Basic Research Needs for Inverse Problems for Complex Systems Under Uncertainty in June 2025. This workshop brought together experts across disciplines to identify grand challenges and major opportunities in the field. Through collaborative discussions, the workshop defined transformative research directions aimed at addressing the mathematical, statistical, and computational challenges posed by inverse problems under uncertainty. As a result of these efforts, four priority research directions (PRDs) were identified to guide future research and development in this area. These PRDs, summarized below, represent a roadmap for advancing the foundational science and mathematics of inverse problems, enabling robust, scalable, and uncertainty-aware solutions that are critical for DOE applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Traversing large graphs on GPUs with unified memory

Due to the limited capacity of GPU memory, the majority of prior work on graph applications on GPUs has been restricted to graphs of modest sizes that fit in memory. Recent hardware and software advances make it possible to address much larger host memory transparently as a part of a feature known as unified virtual memory. While accessing host memory over an interconnect is understandably slower, the problem space has not been sufficiently explored in the context of a challenging workload with low computational intensity and an irregular data access pattern such as graph traversal. We analyse the performance of breadth first search (BFS) for several large graphs in the context of unified memory and identify the key factors that contribute to slowdowns. Next, we propose a lightweight offline graph reordering algorithm, HALO (Harmonic Locality Ordering), that can be used as a pre-processing step for static graphs. HALO yields speedups of 1.5x-1.9x over baseline in subsequent traversals. Our method specifically aims to cover large directed real world graphs in addition to undirected graphs whereas prior methods only account for the latter. Additionally, we demonstrate ties between the locality ordering problem and graph compression and show that prior methods from graph compression such as recursive graph bisection can be suitably adapted to this problem.

Gera, Prasun↗
NASA NTRS2001

Integrated Avionics System (IAS)

As spacecraft designs converge toward miniaturization and with the volumetric and mass constraints placed on avionics, programs will continue to advance the 'state of the art' in spacecraft systems development with new challenges to reduce power, mass, and volume. Although new technologies have improved packaging densities, a total system packaging architecture is required that not only reduces spacecraft volume and mass budgets, but increase integration efficiencies, provide modularity and scalability to accommodate multiple missions. With these challenges in mind, a novel packaging approach incorporates solutions that provide broader environmental applications, more flexible system interconnectivity, scalability, and simplified assembly test and integration schemes. This paper will describe the fundamental elements of the Integrated Avionics System (IAS), Horizontally Mounted Cube (HMC) hardware design, system and environmental test results. Additional information is contained in the original extended abstract.

Hunter, D. J.↗
DOE OSTI2026

Perspectives for artificial intelligence in bioprocess automation

Recent advances in artificial intelligence (AI) have rapidly changed the lab automation landscape, promoting self-driving laboratories (SDLs) that enable autonomous scientific discovery. These trends are increasingly applied in bioprocess development, yet bioprocessing faces unique challenges - biological complexity, regulatory and safety requirements, and multiscale experimentation - that distinguish it from other automation domains. Rather than pursuing full autonomy, we foresee that hybrid SDLs, combining AI-driven decision-making with sustained human oversight, represent the most practical near-term trajectory. This review examines three interconnected perspectives: (i) hybrid human-machine decision-making for bioprocessing; (ii) laboratory design considerations in the era of AI; and (iii) scale-up challenges when transitioning from screening to manufacturing. We highlight critical gaps in data standardization and the required community efforts necessary to realize autonomous bioprocess innovation.

Helleckes, Laura Marie↗