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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

CRADA 376 Final Report Development of Protective Coatings for 1 kW Hot Zone

Pacific Northwest National Laboratory (PNNL) has extensive experience in the development, fabrication, and evaluation of surface treatments and protective coatings for metallic solid oxide fuel cell (SOFC) components. For example, modified (Mn,Co)3O4 spinel coatings and coating/metal interfaces have been shown to substantially improve oxidation resistance, electrical performance, and oxide scale adhesion of ferritic stainless steel interconnects in planar SOFC stacks. At the time of the establishment of this CRADA, Protonex Technology Corporation had been working in the field of SOFC development for over 12 years and had demonstrated more than 250 thermal cycles with a less than 15 minutes start time and more than 2000 hours of continuous operation on a 250W tubular solid oxide hot zone module as part of a program for the Office of the Secretary of Defense (OSD). An industrial version of the military system, denoted P200i, had been developed that was launched at the 2015 Fuel Cell Expo in Tokyo. Feedback during beta testing of this unit was very positive. However, Protonex recognized that to transition from military markets, the commercial system would require longer life time and higher power. Leveraging their novel thermal management strategy from the tubular hot zone that allowed for rapid and repeated thermal cycling, Protonex developed a planar 1kW module aimed at the industrial and commercial market. However, more robust interconnect coatings were needed to bring the system into the 1000+ hour life time requested by customers. Therefore, PNNL’s experience and technology were engaged to enable the 1kw system to transition from military applications to commercial and industrial applications. In this CRADA, PNNL teamed with Protonex to leverage PNNL’s expertise in protective coating techniques for solid oxide fuel cell (SOFC) applications. As the first step in the collaboration, protective spinel coatings were fabricated at PNNL onto ten AISI 440 stainless steel bus bars provided by Protonex. A precursor slurry containing spinel powder was applied to the steel surfaces via an ultrasonic spray process. The coated bars were then subjected to a reducing atmosphere heat treatment (i.e., heated to 850°C at 3°C/min in a hydrogen atmosphere and held at that temperature for five hours). Five of the bars were left in this reduced condition; the other five bars were subjected to an oxidizing heat treatment (i.e., heated to 1000°C at 3°C/min in air and held at that temperature for one hour). The bars were then sent to Protonex for testing. Subsequently, Protonex decided to discontinue their SOFC development activities, so they had no further interest in continuing the collaboration with PNNL, and the CRADA activities were terminated.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2019

LANL Accelerator Activities for C-band

LANL has a range of accelerator activities that would benefit from improvements in RF resonator performance. XFEL (presently using a SRF baseline similar to LCLS-II) would benefit from much higher gradient and long-pulse operation of copper structures. Higher gradient RF structures for lower energy accelerators (~100 MeV) would also provide a path to transportable systems, such as ICS sources. Lastly, the utilization of dielectrics could be exploited for increased efficiency and compactness, e.g. for accelerator in space efforts. A LANL R&D effort aims at systematic improvement of copper structures employing material science simulations to explain and improve breakdown effects, combined with highly optimized designs, integration of cryo-cooling and the use of dielectric insertions. The work is integrated into a High-Gradient collaboration between SLAC, UCLA and LANL.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Review of V&V Documentation

Consortium for Advance Simulation of Light Water Reactors (CASL) is a Department of Energy Innovation Hub whose mission is the following, "CASL is a collaboration of the nation's leading scientists, institutions, and supercomputers, with an aggressive 10-year mission to confidently predict the performance of existing and next-generation commercial nuclear reactors through comprehensive, science-based modeling and simulation." The CASL program to date has focused on developing the necessary predictive capability. Rightly so, it is characterized by many as a research project. As a matter of intent, the first 6 years of CASL focused on developing and demonstrating the prediction capability of a suite of independent physics codes: MPACT (neutronics), CTH (thermal hydraulics in the core), BISON (fuel performance), and MAMBA (CRUD and boron uptake on fuel rod surfaces) The last 4 years focused on initial attempts to couple the codes and to demonstrate those capabilities through a series of challenge problems aligned to 3 key issues of interest to the nuclear power industry.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Building a CO 2 Economy in the Four Corners Region [Script plus Slides]

This project will assess options in the Four Corners region relative to developing a CO₂-based economy, considering both CO₂ supply (via capture) and CO₂ demand (utilization and storage). The assessment will consider a spectrum of opportunities at various stages of technology readiness, including their magnitude and regional distribution. An additional component (via a collaboration TBD) will evaluate the regional implications relative to economy and job growth.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Dataset Repository for Investigating Suicide Risk Using Social and Environmental Determinants of Health

Suicide is frequently modeled as a function of genetics and environment, where the latter refers to factors other than direct biological consequences, such as air quality, financial level, social connectivity, transportation and food access, and homelessness status. According to the World Health Organization, clean air, a stable climate, adequate water, sanitation and hygiene, safe chemical use, radiation protection, healthy and safe workplaces, sound agricultural practices, health-supportive cities and built environments, and a preserved natural environment are all prerequisites for good health. Understanding the relationships between these determinants and mental health outcomes requires standardized data that can be included in healthcare programs and health outcome models. There is a wealth of publicly available data on social and environmental factors provided by various US organizations that can benefit the design of health care systems and public health interventions, as well as improve our comprehension of factors that impact health. Such information would not only help improve the understanding of individual and community risk but also identify new risk factors that have not previously been therapeutically targeted, especially in terms of their impact on mental health. However, curating and standardizing such datasets is challenging because they are often recorded at numerous geographical and temporal resolutions and with varying spatial and temporal granularities. To address this challenge, we launched an endeavor in conjunction with the Veterans Health Administration to collect publicly available socioeconomic and environmental determinants of health statistics in the US. In this manuscript, we describe a social and environmental determinants of health (SEDH) datasets repository, data curation documentation, and a pipeline framework for data generation; This effort started in 2020, when we began constructing a scalable pipeline to automate the download, extraction, preparation, analysis, and production of datasets. These datasets have been made available to the VHA and may be shared upon agreement with collaborating organizations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

FAIR Framework for Physics-Inspired Artificial Intelligence in High Energy Physics (Final Report)

The FAIR4HEP project was a collaboration between Argonne National Laboratory, University of Illinois Urbana-Champaign, Massachusetts Institute of Technology, University of Minnesota, and University of California San Diego funded by the US Department of Energy, Office of Science, Office of Advanced Scientific Research (ASCR) from 2020 to 2024. The primary focus of the FAIR4HEP project was to advance our understanding of the relationship between data and artificial intelligence (AI) models by exploring relationships among them through the development of findable, accessible, interoperable, and reusable (FAIR) frameworks. Using high-energy physics (HEP) as the science driver, this project developed a FAIR framework to advance our understanding of AI, provide new insights to apply AI techniques, and provide an environment where novel approaches to AI can be explored. This final report summarizes the accomplishments of the University of Illinois group.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

A Scientist-in-the-Loop Data Analytics Framework for Intelligent Simulation Model Tuning and Validation

This project developed a scientist-in-the-loop data analytics framework for intelligent simulation model tuning and validation, targeting the Weather Research and Forecasting (WRF) model and its solar energy variant, WRF-Solar-BNL. Domain experts, such as climate scientists, depend on large-scale numerical simulations for knowledge discovery and decision-making, yet the complexity of parameter tuning and the disconnect between automated optimization and domain expertise pose significant challenges. We extended an interactive visual analytics framework that enables domain experts to observe and intervene in the computational steering process by identifying disagreements between the simulation model, surrogate model, and the expert’s domain knowledge. Using Bayesian Optimization with Gaussian Process Regression as the surrogate model, our system allows users to probe parameter relationships, analyze correlation patterns, and adjust tuning parameters in real time. We developed use cases for solar irradiance forecasting through sustained collaboration with Brookhaven National Laboratory, resolving critical model configuration challenges and achieving meaningful reductions in prediction error. The project supported one PhD student, one MS student, and eight undergraduate students across three Data Science Capstone projects, resulting in one master’s thesis.

Dasgupta, Aritra [New Jersey Institute of Technolo↗
DOE OSTI2019

EFRC 10@10: More Efficient, Low-Cost Solar Cells

Silicon solar cells have dominated industrial solar energy facilities, but they convert only about a quarter of the sunlight that reaches them to electric power. To explore alternative approaches, the U.S. Department of Energy’s Office of Science funded an Energy Frontier Research Center (EFRC) that is now called Light Energy Activated Redox Processes. Two of the Center’s principal investigators, Mercouri Kanatzidis and Robert Chang, both at Northwestern University, collaborated on the project. Many research groups were investigating a type of thin-film solar cell that combines a photo-sensitized material that could efficiently absorb light and generate electrons with a liquid that could capture and conduct the electrons. When Chang investigated these solar cells more carefully, however, he concluded they were not a promising solution because the liquid was corrosive and would eventually lead to cell failure. He suggested finding a different material to pair with the photo-sensitized thin-film layer. As it happened, Kanatzidis knew of a class of materials called perovskites that might work and proposed that Chang try it as the substitute material. Perovskites combine several different elements, have a unique structure, and are easy to make. A prototype cell combining a thin layer of perovskite and a photo-sensitized material not only worked, but the thin layer of perovskite also absorbed additional sunlight, boosting efficiency. Additional research improved performance to 10 percent efficiency.

14 SOLAR ENERGY↗
DOE OSTI2026

SuperLab 2.0 Showcase: Connecting Five Labs to Tackle Grid Complexity and Unlock Unique Grid Asset Potential

SuperLab 2.0 (5-Lab Demo) is a collaborative, national-scale experiment showcasing the coordination of geographically distributed energy assets in real time. The demonstration integrates 25 physical and digital assets, spanning wind, PV, batteries, electrolyzers, DC fast chargers, microgrid controllers, building automation systems, small modular reactor (SMR), control centers, and gas turbines, across five DOE national laboratories-NLR, INL, NETL, LBNL, and SNL. These assets are unified using Energy Sciences Network (ESnet), a low-latency, high-performance U.S. Department of Energy's (DOE) network, and controlled via a centralized energy controller hosted at NLR's ARIES facility. The demonstration validates the ability to stress-test hybrid energy systems under dynamic scenarios to de-risk advanced control strategies for greater resilience and flexibility. SuperLab 2.0 (5-Lab Demo) showcased a major advancement in federated national laboratory collaboration, enabling real-time, cross-laboratory experimentation to coordinate geographically dispersed distributed energy resources (DERs) using various communication protocols and networks. SuperLab 2.0 (5-Lab Demo) built on previous demonstrations conducted between NLR-PNNL and NLR-INL connecting diverse assets including distant protection devices, a SMR simulator, and a high temperature electrolyzer (HTE). Previous demos were based on a single connection between two labs with minimal coordination challenges. The 5-Lab demo with a centralized controller, distributed testbeds across different geographical locations, and use of protocols-based communication represents a scenario closer to real-world grid operations that coordinate resources across a region to meet system needs. This experiment studied how local DER controllers interact with a centralized energy controller during normal and abnormal events to maintain reliability. The SuperLab team across the five labs implemented a notional power system model equivalent of transmission and distribution lines, represented by the data networks interconnecting the labs. Each lab continuously exchanged local parameters (such as P and Q) from its Hardware-In-Loop (CHIL) and Power Hardware-In-Loop (PHIL) assets through centralized energy controller at NLR, enabling real-time interaction and coordination across sites. By leveraging ESnet as the communication backbone, the team successfully operated the distributed assets as a unified power system, with each bus represented by a different laboratory. This setup mirrors how assets interact in real-world power systems across dispersed locations with various protocols and latencies. At each lab site, assets were operated using their own local controllers which were coordinated through an overarching operation and control layer of centralized energy controller, equivalent to how an energy management system (EMS) orchestrates assets across a regional or national grid. SuperLab's federated connectivity utilized a Digital Real-Time Simulators (DRTS)-type gateway to connect Controller Hardware-In-Loop (CHIL) and PHIL assets between labs. To enable this federated connection through ESnet, a deterministic network was established where latency variations were consistent. This consistency allowed the development of digital filters for the power system assets across CHIL and PHIL interfaces to avoid unstable and unreliable grid conditions. This report provides an overview of the cross-laboratory configuration and offers insights into interconnecting geographically distributed research assets to test them as if they were co-located. This experiment represents a step toward linking nine DOE national laboratories, enabling nation-wide simulations that can address utility-driven challenges with grid resilience, flexibility, and modernization.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

AMES: MS and MENG in Advanced Manufacturing for Energy at the University of Connecticut (Final Technical Report)

The objective of the project is to develop and implement an advanced degree program (MS and MENG in Advanced Manufacturing for Energy Systems, AMES) responding to the long-term workforce and technology requirements of the nation’s advanced energy products manufacturing industry. The program provided an industry relevant research experience by leveraging existing energy (e.g. fuels, power electronics, electrochemical power sources) and advanced manufacturing (e.g. additive manufacturing, composites, sensing) research at UConn funded by federal and state agencies, and industry, as well as through our industry partnerships. The trainees have joined research teams, advised by faculty with relevant research interests and expertise and were co-advised by industrial mentors. The AMES program have developed a truly interdisciplinary curriculum, first graduate degree program at UConn School (now College) of Engineering not housed in an academic department, with concentrations focusing on various challenges in advanced manufacturing for energy systems, e.g. advanced materials and processing. The project also developed new courses focusing on common technical and professional skills, and integrated various components for an industry relevant training. The program has admitted 29 Master of Science (MS) students since inception in January 2019. Twenty six of these students were AMES fellows, who have received partial funding from DoE through this project. The program far exceeded the goal of admitting at least five new MS (with thesis) students. All students were required to complete a thesis (M.S.) or a capstone (M.Eng.) project that are defined in collaboration with industry partners to ensure industrial relevancy, addressing a current industrial challenges. Industrial mentors also participated in advising the students in their research. AMES fellows, in addition were also required to complete an industrial internship for further industrial experience.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nuclear Science for the Manhattan Project and Comparison to Today’s ENDF Data

Nuclear physics advances in the United States and Britain from 1939 to 1945 are described. The Manhattan Project’s work led to an explosion in our knowledge of nuclear science. A conference in April 1943 at Los Alamos provided a simple formula used to compute critical masses and laid out the research program needed to determine the key nuclear constants. In short order, four university accelerators were disassembled and reassembled at Los Alamos, and methods were established to make measurements on extremely small samples owing to the initial lack of availability of enriched 235U and plutonium. I trace the program that measured fission cross sections, fission-emitted neutron multiplicities and their energy spectra, and transport cross sections, comparing the measurements with our best understanding today as embodied in the Evaluated Nuclear Data File ENDF/B-VIII.0. The large nuclear data uncertainties at the beginning of the project, which often exceeded 25% to 50%, were reduced by 1945 often to less than 5% to 10%. Uranium-235 and plutonium-239 fission cross-section assessments in the fast mega-electron-volt range were reduced following more accurate measurements, and the neutron multiplicity $\overline{v}$ increased. By a lucky coincidence of canceling errors, the initial critical mass estimates were close to the final estimated masses. Some images from historical documents from our Los Alamos archives are shown. Many of the original measurements from these early years have not previously been widely available. Through this work, these data have now been archived in the international experimental nuclear reaction data library (EXFOR) in a collaboration with the International Atomic Energy Agency and Brookhaven National Laboratory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

All-Atom Simulation of 3D Hot Spot Formation in Shocked TATB Explosive

TATB is an insensitive high explosive (IHE) critical to the stockpile that is challenging to model at the continuum scale. Advanced detonation models in the Cheetah high explosive chemistry code require validation though subscale simulations. High explosive initiation is determined by micron-scale physics of hot spots formed a shock-collapsed pores. Pore sizes between 100 nm and 1 μm are believed to be the most important for determining the shock sensitivity of TATB. This range of pore sizes is difficult to access at the atomic scale through allatom molecular dynamics (MD) simulations, even with Sierra-class computers. Quasi-2D simulations are widely used and allow much larger pore sizes (up to 400 nm) to be studied, but the applicability of 2D simulations to the actual 3D pore response is not understood. Resolving these uncertainties through “full physics” MD modeling is key for generalizing, parameterizing, and validating the kinds of continuum models used to inform design, safety, and performance. This work was a continuation of FY20 efforts pushing simulations to full 3D with the largest-ever all-atom simulations of an explosive. These were the first all-atom full-3D simulations of large hot spots thought to govern explosive detonation and required over a billion atoms. Simulations were performed using LAMMPS, an open SNL science code. MD explosive models present unique challenges, even for established codes such as LAMMPS. Their model forms are more complex than typical models for metals, while simulating high temperature-pressure conditions is demanding and increases computational cost. Scaling problems in GPU-enabled MD algorithms initially limited simulations to <100 million atoms but were resolved through collaboration with SNL. An overall 24x speedup was obtained relative to CPU machines. Specialized analysis of these simulations required a bottom-up refactoring and algorithm parallelization of in-house codes and application of computer vision algorithms to extract meaningful information.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Science acceleration and accessibility with self-driving labs

In the evolving landscape of scientific research, the complexity of global challenges demands innovative approaches to experimental planning and execution. Self-Driving Laboratories (SDLs) automate experimental tasks in chemical and materials sciences and the design and selection of experiments to optimize research processes and reduce material usage. This perspective explores improving access to SDLs via centralized facilities and distributed networks. We discuss the technical and collaborative challenges in realizing SDLs’ potential to enhance human–machine and human–human collaboration, ultimately fostering a more inclusive research community and facilitating previously untenable research projects.

Canty, Richard B. [North Carolina State University↗
DOE OSTI2025

Privacy Preservation from High-Performance Computing to Autonomous Science [Industrial and Governmental Activities]

High-Performance Computing (HPC) and Leadership-Class Supercomputing are driving forces behind scientific advancements, enabling researchers to tackle complex challenges in physics, chemistry, biology, and engineering. These systems power vast simulations and data analyses, fueling discoveries in fields ranging from materials science to climate modeling. However, their use often involves processing sensitive data—such as proprietary industry simulations, biomedical records, and national security computations—posing significant privacy concerns. In conclusion, this issue is amplified in collaborative environments like Department of Energy (DOE) user facilities, where HPC resources are shared across institutions to foster innovation.

Kotevska, Olivera [Oak Ridge National Laboratory (↗
DOE OSTI2017

Quantum Dot Sensitized Solar Cells Based on Ternary Metal Oxide Nanowires

In Phase I of this project we investigate quantum dot sensitized solar cells (QDSSCs) based on ternary metal oxide nanowires and study the physical and chemical mechanisms that govern device operation. Our research has the following five objectives: (1) synthesis of ternary metal oxide nanowires, (2) synthesis of QDs and exploration of non-solution based QD deposition methods, (3) physical and electro-optical characterizations of fabricated solar devices, (4) device modeling and first-principle theoretical study of transport physics, and (5) investigation of long-term stability issues of QD sensitized solar cells. In Phase II of this project our first major research goal is to investigate magnetically doped quantum dots and related spin polarization effect, which could improve light absorption and suppress electron relaxation in the QDs. We will utilize both physical and chemical methods to synthesize these doped QDs. We will also study magnetically modified nanowires and introduce spin-polarized transport into QDSSCs, and inspect its impact on forward electron injection and back electron transfer processes. Our second goal is to study novel solid-state electrolytes for QDSSCs. Specifically, we will inspect a new type of polymer electrolytes based on a modified polysulfide redox couple, and examine the effect of their electrical properties on QDSSC performance. These solid-state electrolytes could also be used as filler materials for in situ sample fracturing in STM and enable cross-sectional interface examination of QD/nanowire structures. Our third research goal is to examine the interfacial properties such as energy level alignment at QD/nanowire interfaces using the newly developed Cross-sectional Scanning Tunneling Microscopy and Spectroscopy technique for non-cleavable materials. This technique allows a direct probing of band structures and alignment at device interfaces, which could generate important insight into the mechanisms that govern QDSSC operation. These investigations will be carried out through a close collaboration between our experimental and theoretical efforts in this project. This project initiates an important research direction in the jurisdiction of Wyoming. It brings together researchers from different academic disciplines including physics, chemistry, materials science, and engineering to work on one common scientific theme, and is a vital step towards the establishment of an nationally competitive research program in energy-related nanomaterials in the state of Wyoming.

14 SOLAR ENERGY↗
DOE OSTI2022

Polar Cloud Microphysics and Surface Energy Budget from AWARE (Final Technical Report)

This was a collaborative project between the Scripps Institution of Oceanography at the University of California San Diego (SIO), Byrd Polar and Climate Research Center at The Ohio State University (BPCRC), The Department of Meteorology and Atmospheric Science at The Pennsylvania State University (Penn State), and Brookhaven National Laboratory (BNL). The project’s over-arching objectives involved maximizing the scientific potential of the ARM West Antarctic Radiation Experiment (AWARE) data set, in two respects: (1) application of polar-optimized climate models to test the most current and comprehensive cloud microphysical parameterizations; and (2) analysis of the most advanced ARM Mobile Facility sensors (e.g., cloud radar, spectroradiometer, and aerosol observing system data) to advance understanding of Antarctic cloud microphysical and radiative properties, particularly on a climatological basis with emphasis on contrasts with the high Arctic. The team’s efforts have resulted in 16 peer-review publications, in addition to an overview of the AWARE campaign in the Bulletin of the American Meteorological Society. Our emphasis throughout this program was to go beyond the traditional “case study” approach to model evaluation, in which a “classical” or otherwise well-characterized surface-atmosphere-cloud system of short duration is simulated by several climate models. Instead, we attempted analysis of longer time series in the AWARE data, both climatologically and with models. We have numerous successful results from both AWARE locations: The main AMF-2 deployment at McMurdo Station on Ross Island (13 months duration), and the extended facility at the West Antarctic Ice Sheet (WAIS) Divide Ice Camp (40 days during austral summer 2015-16).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

DOE Final Report on Virginia Tech’s contribution to “Tokamak Disruption Simulation”

This work was performed by Virginia Tech in collaboration with multiple institutions led by Los Alamos National Laboratory as a part of the Tokamak Disruption Simulation SciDAC (Scientific Discovery through Advanced Computing) project supported jointly by the Department of Energy Office of Science and Ad- vanced Scientific Computing Research. This report summarizes Virginia Tech’s contributions to the Sci- DAC project. Virginia Tech researchers (presently University of Washington researchers) focused on the fundamental role of plasma-material interaction on transport, which could then have macroscopic effects on simulations of tokamak disruptions. The plasma sheath, which regulates plasma particle and energy fluxes to the wall, is an essential component in the study of plasma-material interaction (PMI). Understanding sheath theory by accounting for finite sheath thickness and transport in the vicinity of the sheath entrance can sig- nificantly modify typical assumptions that are made in the Bohm speed analysis, where the Bohm speed provides the lower bound of the plasma exit flow speed. Our work provides a modified Bohm speed formu- lation that accounts for the critical role of transport and for applications that are away from the asymptotic limits that are typically assumed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗