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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Laboratory for Laser Energetics Targets Inertial Confinement Fusion

The University of Rochester’s Laboratory for Laser Energetics is targeting laser-driven inertial confinement fusion, as part of National Nuclear Security Administration’s Stockpile Stewardship Program and in the quest for clean sources of energy. The Laboratory for Laser Energetics (LLE) is home to two extremely powerful lasers—OMEGA and OMEGA EP—and researchers are using them to explore laser-driven inertial confinement fusion (ICF). ICF involves compressing a small amount of fuel consisting of hydrogen isotopes, deuterium (D), and tritium (T), and heating it to temperatures greater than the center of stars. “When these conditions are reached, the fuel undergoes fusion—releasing enormous energy that can be used for research relevant to the National Nuclear Security Administration’s (NNSA) Stockpile Stewardship Program (SSP) and to drive carbon-free power plants,” explains Valeri Goncharov, distinguished scientist and director of the Theory Division at LLE. LLE was established at the University of Rochester in 1970 and is the largest U.S. Department of Energy university-based research program in the nation, supported by the National Nuclear Security Administration as part of its Stockpile Stewardship Program (SSP). “As a center for exploring the interaction of intense radiation with matter, LLE is a unique national resource for research and education in science and technology,” says Goncharov. “Our current research includes exploring fusion for the SSP program and as a future source of energy, developing new laser and materials technologies, and pursuing a better understanding of high-energy-density phenomena.”

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Addressing the data and real-time challenges in large scale particle physics experiments through AI and in situ computing technologies

Modern high energy physics experiments are faced not only with the challenge of having to deal with extremely high data rates but with the need to process data quickly to meet real time constraints. At Fermilab, we explore the use of novel computing technologies and techniques to address these challenges. I will discuss my R&D efforts in applying such computing solutions to enhance the multi-messenger astronomy capabilities and improve the overall physics performance of large-scale LArTPC based neutrino experiments. These efforts offer excellent opportunities for fruitful collaboration.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Human Factors in Discovery Phase of TRLs and HRLs

With rapid growth in technology, there has been a corresponding growth in research focused on the ways that human-machine interactions can be improved. As part of that work, researchers have explored how human expertise can inform technology design and evaluation. For example, interaction with subject matter experts (SMEs) or end users can help to design and enhance a machine. The human factors of technology release can be divided into five steps: discovery, planning, development, evaluation, and deployment. This framework is a higher-level abstraction of the Human Readiness Levels for technology use and adoption (See, et al., 2018). In this exposition, we discuss how human factors methodologies, principles, and practices can be realized in the first phase, Discovery, of the technology development process.

Jefferson, Brett A.↗
DOE OSTI2024

Correlation of Band Bending and Ionic Losses in 1.68 eV Wide Band Gap Perovskite Solar Cells

Abstract Perovskite solar cells (PSCs) are promising for high‐efficiency tandem applications, but their long‐term stability, particularly due to ion migration, remains a challenge. Despite progress in stabilizing PSCs, they still fall short compared to mature technologies like silicon. This study explores how different piperazinium salt treatments using iodide, chloride, tosylate, and bistriflimide anions affect the energetics, carrier dynamics, and stability of 1.68 eV bandgap PSCs. Chloride‐based treatments achieved the highest power conversion efficiency (21.5%) and open‐circuit voltage (1.28 V), correlating with stronger band bending and n‐type character at the surface. At the same time, they showed reduced long‐term stability due to increased ionic losses. Tosylate‐treated devices offered the best balance, retaining 96.4% efficiency after 1000 h (ISOS‐LC‐1I). These findings suggest that targeted surface treatments can enhance both efficiency and stability in PSCs.

14 SOLAR ENERGY↗
DOE OSTI2022

Derivation and assessment of regional electricity generation emission factors in the USA

Electricity production is one of the largest sources of environmental emissions - especially greenhouse gases (GHGs) - in the USA. Emission factors (EFs) vary from region to region, which requires the use of spatially relevant EF data for electricity production while performing life cycle assessments (LCAs). Uncertainty information, which is sought by LCA practitioners, is rarely supplied with available life cycle inventories (LCIs). To address these challenges, we present a method for collecting data from different sources for electricity generation and environmental emissions; discuss the challenges involved in agglomerating such data; provide relevant suggestions and solutions to merge the information; and calculate EFs for electricity generation processes from various fuel sources for different spatial regions and spatial resolutions. The EFs from the US 2016 Electricity Life Cycle Inventory (eLCI) are analyzed and explored in this study. We also explore the method of uncertainty information derivation for the EFs. We explore the EFs from different technologies across Emissions & Generation Resource Integrated Database (eGRID) regions in the USA. We find that for certain eGRID regions, the same electricity production technology may have worse emissions. This may be a result of the age of the plants in the region, the quality of fuel used, or other underlying factors. Region-wise life cycle impact assessment (LCIA) ISO 14040 impacts for total generation mix activities provide an overview of the total sustainability profile of electricity production in a particular region, rather than only global warming potential (GWP). We also find that, for different LCIA impacts, several eGRID regions are consistently worse than the US average LCIA impact for every unit of electricity generated. Here this work describes the development of an electricity production LCI at different spatial resolutions by combining and harmonizing information from several databases. The inventory consists of emissions, fuel inputs, and electricity and steam outputs from different electricity production technologies located across various regions of the USA. This LCI for electricity production in the USA will prove to be an enormous resource for all LCA researchers - considering the detailed sources of the information and the breadth of emissions covered by it.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

CoolPINNs: A physics-informed neural network modeling of active cooling in vascular systems

Emerging technologies like hypersonic aircraft, space exploration vehicles, and batteries avail fluid circulation in embedded microvasculatures for efficient thermal regulation. Modeling is vital during the design and operational phases of these engineered systems. However, many challenges exist in developing a modeling framework. What is lacking is an accurate framework that (i) captures sharp jumps in the thermal flux across complex vasculature layouts, (ii) deals with oblique derivatives (involving tangential and normal components), (iii) handles nonlinearity because of radiative heat transfer, (iv) provides a high-speed forecast for real-time monitoring, and (v) facilitates robust inverse modeling. Here, this paper addresses these challenges by availing the power of physics-informed neural networks (PINNs). We develop a fast, reliable, and accurate Scientific Machine Learning (SciML) framework for vascular-based thermal regulation—called CoolPINNs: a PINNs-based modeling framework for active cooling. The proposed mesh-less framework elegantly overcomes all the mentioned challenges. The significance of the reported research is multi-fold. First, the framework is valuable for real-time monitoring of thermal regulatory systems because of rapid forecasting. Second, researchers can address complex thermoregulation designs since the approach is meshless. Finally, the framework facilitates systematic parameter identification and inverse modeling studies, perhaps the most significant utility of the current framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

AI-Based Analytics and Energy Modeling Framework for Characterizing Urban Energy Systems

Developing location-specific district energy models is essential for understanding energy patterns and supporting efficient management and planning decisions. However, accurately characterizing these models remains challenging due to gaps in building characteristics and labor-intensive traditional modeling workflows. To address these challenges, we develop an AI-based framework that integrates top-down and bottom-up building energy data to automate urban energy model characterization. The framework trains multimodal deep learning models using heterogeneous ResStockTM datasets to infer missing building characteristics from varying levels of known information and generate simulation-ready inputs for district-scale energy modeling. It also employs a conditioning-based injection approach to generate ”what-if” scenarios, enabling users to explore retrofit, efficiency, and technology-upgrade pathways. Integrated within URBANoptTM, a bottom-up district energy modeling platform for simulating co-located buildings, the framework infers detailed building-level inputs required for bottom-up simulations. Both localized and generalized AI models are developed to learn relationships across categorical, numerical, and time-series data, enabling reconstruction of missing attributes and generation of targeted upgrade scenarios. We demonstrate this methodology on a residential neighborhood in Baltimore, MD, assessing internal consistency against ResStock reference data and URBANopt simulation, and comparing selected attributes against real-world building characteristics. Results show strong overall predictive accuracy in data completion and scenario generation, with localized and generalized models offering complementary trade-offs between precision and scalability. Overall, our automated framework streamlines energy modeling and provides a reliable framework for urban building energy characterization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Cooling performance of an active-passive hybrid composite phase change material (HcPCM) finned heat sink: Constant operating mode

Here, the present study explores a hybrid thermal management technology based on air cooling and hybrid composite phase change material (HcPCM) filled finned heat sink for cooling performance of lower to medium heat flux dissipating electronic devices. Two-dimensional numerical simulations are conducted to study the conjugate heat transfer effects of three types of finned heat sink: air-cooled finned heat sink, HcPCM-cooled finned heat sink, and hybrid (air-HcPCM) cooled finned heat sink. A heat sink with a constant volume faction of plate-fins is designed in all cases and simultaneous effects of hybrid nanoparticles and air are investigated to keep the heat sink temperature at safe operating conditions between 40–60°C. The effect of air is incorporated into the heat sink by applying the convective heat transfer coefficient of h c = 10–100W /m 2 .K which tends to create the natural convection and forced convection heat transfer characteristics. The heat flux is varied from 25–40kW /m 2 in the current study. The hybrid nanoparticles of carbon additives (GO and MWCNTs) are dispersed into the RT-35HC, used as a PCM, with a volume fraction of 0% to 6%. Transient simulations are carried out using COMSOL Multiphysics to solve the governing equations for PCM based conjugate heat transfer model. The results showed that forced convection heat transfer improved the cooling performance of the hybrid heat sink compared to natural convection heat transfer. The addition of nanoparticles further enhanced thermal enhancement and uniform melting distribution of PCM inside the finned heat sink. The h c between 30 to 50W/m 2 .K shows optimized values for forced convection heat transfer operating conditions. The volume fraction of 2% of GO+MWCNTs nanoparticles in recommended or optimum concentration for uniform melting of PCM inside the finned heat sink.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A data-driven operational model for traffic at the Dallas Fort Worth International Airport

Airports are on the front line of significant innovations, allowing the movement of more people and goods faster, cheaper, and with greater convenience. As air travel continues to grow, airports will face challenges in responding to increasing passenger vehicle traffic, which leads to lower operational efficiency, poor air quality, and security concerns. This paper evaluates methods for traffic demand forecasting combined with traffic microsimulation, which will allow airport operations staff to accurately predict traffic and congestion. Using two years of detailed data describing individual vehicle arrivals and departures, aircraft movements, and weather at Dallas-Fort Worth (DFW) International Airport, we evaluate multiple prediction methods including the Auto Regressive Integrated Moving Average (ARIMA) family of models, traditional machine learning models, and DeepAR, a modern recurrent neural network (RNN). We find that these algorithms are able to capture the diurnal trends in the surface traffic, and all do very well when predicting the next 30 minutes of demand. Longer forecast horizons are moderately effective, demonstrating the challenge of this problem and highlighting promising techniques as well as potential areas for improvement. Traffic demand is not the only factor that contributes to terminal congestion, because temporary changes to the road network, such as a lane closure, can make benign traffic demand highly congested. Combining a demand forecast with a traffic microsimulation framework provides a complete picture of traffic and its consequences. The result is an operational intelligence platform for exploring policy changes, as well as infrastructure expansion and disruption scenarios. To demonstrate the value of this approach, we present results from a case study at DFW Airport assessing the impact of a policy change for vehicle routing in high demand scenarios. This framework can assist airports like DFW as they tackle daily operational challenges, as well as explore the integration of emerging technology and expansion of their services into long term plans.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Embracing the Intersections of Environmental Science, Engineering, and Geosciences to Solve Grand Challenges of the 21st Century

The U.S. National Academies report on Environmental Engineering for the 21st Century identified five grand challenges of sustainably supplying food, water, and energy; curbing climate change and adapting to its impacts; designing a future without pollution and waste; creating efficient, healthy, resilient cities; and fostering informed decisions and actions. (1) Addressing many of the grand challenges will require embracing the intersections of environmental science, engineering, and geosciences. These three fields are inherently interdisciplinary, and they naturally intersect with each other (Figure 1). Geosciences, or Earth sciences, study the dynamics of different spheres of Earth. One of its missions is to detect the availability of mineral, water, and fuel resources, for sustainable development, and new research opportunities were identified in “coevolution of life, environment, and climate” and “biogeochemical and water cycles in terrestrial environments and impacts of global change” by the U.S. National Research Council. (2) Environmental science and engineering focus on the spheres that intersect with human activities. Environmental science puts an emphasis on understanding the migration of naturally occurring and anthropogenic contaminants in the environment and their impact on ecosystem and human health, and environmental engineering centers on developing technologies for water supply, mineral exploration, and environmental remediation to mitigate adverse impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Vortex Domain Walls in Ferroelectrics

Controlling the domain formation in ferroelectric materials at the nanoscale is a fertile ground to explore emergent phenomena and their technological prospects. For example, charged ferroelectric domain walls in BiFeO 3 and ErMnO 3 exhibit significantly enhanced conductivity which could serve as the foundation for next-generation circuits. In this work, we describe a concept in which polar vortices perform the same role as a ferroelectric domain wall in classical domain structures with the key difference being that the polar vortices can accommodate charged (i.e., head-to-head and tail-to-tail) domains, for example, in ferroelectric PbTiO 3 /dielectric SrTiO 3 superlattices. Such a vortex domain wall structure can be manipulated in a reversible fashion under an external applied field.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Extreme Temperature Cryptography Based On Nitrogen-Incorporated Ultrananocrystalline Diamond

Physical entropy sources that remain stable under extreme temperatures are essential for cryptography in emerging technological frontiers in deep space exploration, geothermal energy harvesting, and nuclear energy. However, conventional semiconductor platforms fail to generate stable and reliable cryptographic keys above 200 degrees C due to performance degradation. Here, we report a diamond-based cryptographic primitive that exploits the defect-rich sp 2 -bonded grain boundary network in nitrogen-incorporated ultrananocrystalline diamond (n-UNCD) film as a robust entropy source to generate cryptographic keys that remain operationally stable even after enduring extreme temperatures of 700 degrees C for 54 h while also surviving thermal cycling between room temperature and 700 degrees C for 48 h. The strength of the generated keys is assessed through several cryptographic metrics such as bit uniformity, entropy, hamming distances, and correlation coefficients, all of which are found to be near their respective ideal values. Moreover, the generated keys pass the NIST SP 800 and SP 800-90B tests and are also resilient to supply bias variations and a regression-based machine learning attack model based on the Fourier series. The robustness of the keys is attributed to the better thermal stability and chemical inertness of the n-UNCD film. This is supported by high-resolution energy-dispersive X-ray spectroscopy (EDS), which shows no significant lateral diffusion of metal atoms into the n-UNCD layer, and by Raman spectroscopy, which reveals no significant changes in the bonding configuration of the n-UNCD structure. Our findings highlight the remarkable potential of n-UNCD film for extreme environment cryptography by expanding the operational limits of conventional hardware security platforms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Non-equilibrium states and interactions in the topological insulator and topological crystalline insulator phases of NaCd4As3

Topological materials are of great interest because they can support metallic edge or surface states that are robust against perturbations, with the potential for technological applications. Here, we experimentally explore the light-induced non-equilibrium properties of two distinct topological phases in NaCd4As3: a topological crystalline insulator (TCI) phase and a topological insulator (TI) phase. This material has surface states that are protected by mirror symmetry in the TCI phase at room temperature, while it undergoes a structural phase transition to a TI phase below 200 K. After exciting the TI phase by an ultrafast laser pulse, we observe a leading band edge shift of >150 meV that slowly builds up and reaches a maximum after ∼0.6 ps and that persists for ∼8 ps. The slow rise time of the excited electron population and electron temperature suggests that the electronic and structural orders are strongly coupled in this TI phase. It also suggests that the directly excited electronic states and the probed electronic states are weakly coupled. Both couplings are likely due to a partial relaxation of the lattice distortion, which is known to be associated with the TI phase. In contrast, no distinct excited state is observed in the TCI phase immediately or after photoexcitation, which we attribute to the low density of states and phase space available near the Fermi level. Our results show how ultrafast laser excitation can reveal the distinct excited states and interactions in phase-rich topological materials.

Angle-resolved photoemission spectroscopy↗
DOE OSTI2022

Direct visualization and control of antiferromagnetic domains and spin reorientation in a parent cuprate

Here, we report magnetic optical second-harmonic generation (SHG) polarimetry and imaging on Sr 2 Cu 3 O 4 Cl 2 , which allows direct visualization of the mesoscopic antiferromagnetic (AFM) structure of a parent cuprate. Temperature- and magnetic-field-dependent SHG reveals large domains with 90° relative orientations that are stabilized by a combination of uniaxial magnetic anisotropy and the Earth's magnetic field. Below a temperature T R ~ 97 K, we observe an unusual 90° spin reorientation transition, possibly driven by competing magnetic anisotropies of the two copper sublattices, which swaps the AFM domain states while preserving the domain structure. This allows deterministic switching of the AFM states by thermal or laser heating. Near T R , the domain walls become exceptionally responsive to an applied magnetic field, with the Earth's field sufficient to completely expel them from the crystal. Our findings unlock opportunities to study the mesoscopic AFM behavior of parent cuprates and explore their potential for AFM technologies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Narrowing down sources of high-frequency gravitational waves

Detecting gravitational waves above 100 kHz would constitute a major discovery, as any observable signal would have to arise from new physics within the late universe. Although many technologies have been identified to explore this high-frequency regime, the known landscape of promising sources remains extremely sparse. In this work, we aim to rectify this issue by providing model-independent arguments that highlight the most interesting parts of theory space, while remaining agnostic of the specific signal mechanism. For example, energy-conservation implies that gravitational waves detectable by future experiments well above a MHz would most likely have to originate from within the Solar System. Based on these arguments, we also constrain the physical properties of such sources.

Berlin, Asher [Fermilab] (ORCID:0000000211561482)↗
DOE OSTI2023

Cascaded Sapphire Fiber Bragg Gratings Inscribed by Femtosecond Laser for Molten Steel Studies

This research reports a distributed fiber optic high-temperature sensing system tailored for applications in the steel industry and various other sectors. Recent advancements in optical sensor technology have led to the exploration of sapphire crystal fibers as a solution for sensing in harsh environments. Utilizing a femtosecond (fs) laser, cascaded fiber Bragg gratings (FBGs) were meticulously fabricated within a multimode sapphire optical fiber. These FBGs endowed the system with distributed sensing capabilities and underwent rigorous testing under extreme temperatures, reaching up to 1800 °C. Here, the study delves into the investigation of the FBG reflection spectrum, facilitated by the development of a sophisticated multimode demodulation system, which contributed to the attainment of precise temperature measurements with a performance accuracy of 99.9%. Demonstrating exceptional thermal stability, the sapphire FBGs endured temperatures of 1600 °C for a sustained duration of 22 h. Furthermore, this article explores the application of distributed temperature sensing employing multiple sapphire FBGs, showcasing their utility in temperature measurements related to molten steel studies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

New Technologies for Axion and Dark Photon Searches

The search for dark matter and physics beyond the Standard Model has grown to encompass a highly interdisciplinary approach. In this review, we survey recent searches for light, weakly coupled particles—axions and dark photons—over the past decade, focusing on new experimental results and the incorporation of technologies and techniques from fields as diverse as quantum science, microwave engineering, precision magnetometry, and condensed matter physics. We also review theoretical progress that has been useful in identifying new experimental directions and identify the areas of most rapid experimental progress and the technological advances required to continue exploring the parameter space for axions and dark photons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

High efficiency glass-based VUV metasurfaces

Most advances in metaoptics have been made at visible wavelengths and above; in contrast, the vacuum ultraviolet (VUV) has barely been explored despite numerous scientific and technological opportunities. Creating metaoptic elements at this short wavelength is challenging due to the scarcity of VUV transparent materials and the small sizes of the required nanostructures. Here, we present the first transmissive VUV (175 nm) metalens. By using UV-grade silica and trading off the Nyquist requirement for subwavelength structures against feasibility of the fabrication process, we achieve a step-change in diffraction efficiencies for wavelengths shorter than 300 nm. Our large numerical aperture (NA = 0.5) metalens shows an average diffraction efficiency of (53.3 ± 1.4)%. This demonstration opens up new avenues for compact flat optic systems operating in the VUV range.

Martins, Augusto [Univ. of York (United Kingdom)] ↗