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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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DOE OSTI2022

The Net Zero World Initiative

The U.S. is committed to working with countries all over the globe to accelerate clean climate goals from ambition to action, and the Net Zero World Initiative is the latest example of our dedication. The Net Zero World Initiative is uniquely positioned to achieve rapid global energy decarbonization. It will partner with countries to help them implement climate ambition pledges and accelerate global transitions to net zero, resilient, and inclusive energy systems. The Net Zero World Initiative Will Harness Unique USG and Lab Assets in Partnership with Philanthropies. Scale-up and goals listed.

accelerate↗

DOE OSTI2018

(Invited) HydroGEN: An AWSM Energy Materials Network

The HydroGEN (https://www.h2awsm.org/) energy materials network (EMN) aims to accelerate the research and development (R&D) of advanced water splitting (AWS) technologies for clean, sustainable hydrogen production. Announced in October 2016, the HydroGEN EMN comprises six core National Laboratories and focuses on four AWS pathways: low- and high-temperature electrolysis, photoelectrochemical, and solar thermochemical water splitting. The HydroGEN consortium offers an extensive collection of materials research capabilities for addressing R&D challenges in discovery and design, efficacy and efficiency, durability and cost. Leveraging the HydroGEN Consortium's technical experts and broad collection of unique resource capabilities is expected to advance the maturity and technology readiness levels in each advanced water splitting technology pathway.

08 HYDROGEN↗

DOE OSTI2011

Capturing the Sun, Creating a Clean Energy Future (Brochure)

Through partnerships with industry academia, and national laboratories, the DOE Solar Energy Technologies Program sponsors research and development (R&D) in addition to activities designed to accelerate solar market development and reduce the cost of solar power.

14 SOLAR ENERGY↗

DOE OSTI2011

Capturing the Sun, Creating a Clean Energy Future (Brochure)

sunshot, solar, solar energy technologies, pv, csp↗

DOE OSTI2023

Hydrogen Consortium: Technical Progress on Renewable Hydrogen Production R&D

HydroGEN (https://www.h2awsm.org/) Energy Materials Network (EMN) is an U.S. Department of Energy (DOE) EERE Hydrogen and Fuel Cell Technologies Office (HFTO)-funded consortium that aims to accelerate the discovery and development of advanced water splitting materials (AWSM) for clean, low-cost hydrogen production. This is in line with the H2@Scale initiative (https://www.energy.gov/eere/fuelcells/h2-scale), with the goal to meet U.S. DOE's Hydrogen Shot production cost target of $1/kg H2 within 1 decade. Materials innovations are key to enhancing performance, durability, and cost of hydrogen generation technologies. Large scale, low cost hydrogen from diverse domestic resources can enable an economically competitive and environmentally beneficial future energy system across multiple sectors. HydroGEN is focused on low technology readiness level AWS technologies, including low- (alkaline exchanged membrane electrolysis) and high-temperature electrolysis (proton-conducting solid oxide electrolysis), photoelectrochecmical (PEC) and solar thermochemical (STCH) water splitting. This presentation will provide an overview of the HydroGEN EMN and technical highlights of a few lab-led and FOA-awarded R&D projects. HydroGEN continues to grow its community of industry, university, and national laboratories, forming a national innovation ecosystem focused on renewable hydrogen production.

clean hydrogen↗

DOE OSTI2024

HydroGEN Overview: A Consortium on Advanced Water Splitting Materials

clean hydrogen↗

DOE OSTI2013

High contrast ion acceleration at intensities exceeding 10{sup 21} Wcm{sup −2}

Ion acceleration from short pulse laser interactions at intensities of 2×10{sup 21}Wcm{sup −2} was studied experimentally under a wide variety of parameters, including laser contrast, incidence angle, and target thickness. Trends in maximum proton energy were observed, as well as evidence of improvement in the acceleration gradients by using dual plasma mirrors over traditional pulse cleaning techniques. Extremely high efficiency acceleration gradients were produced, accelerating both the contaminant layer and high charge state ions from the bulk of the target. Two dimensional particle-in-cell simulations enabled the study of the influence of scale length on submicron targets, where hydrodynamic expansion affects the rear surface as well as the front. Experimental evidence of larger electric fields for sharp density plasmas is observed in simulation results as well for such targets, where target ions are accelerated without the need for contaminant removal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Sustainable Energy in Remote Indonesian Grids. Accelerating Project Development

Sustainable Energy for Remote Indonesian Grids (SERIG) is a U.S. Department of Energy (DOE) funded initiative to support Indonesia’s efforts to develop clean energy and increase access to electricity in remote locations throughout the country. With DOE support, the SERIG implementation team consists of the National Renewable Energy Laboratory (NREL) and Winrock International’s Jakarta, Indonesia office. Through technical assistance that includes techno-economic feasibility evaluation for selected projects, government-to-government coordination, infrastructure assessment, stakeholder outreach, and policy analysis, SERIG seeks to provide opportunities for individual project development and a collective framework for national replication office.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2018

Consequences of neglecting the interannual variability of the solar resource: A case study of photovoltaic power among the Hawaiian Islands

The interannual variability of the solar irradiance and meteorological conditions are often ignored in favor of single-year data sets for modeling power generation and evaluating the economic value of photovoltaic (PV) power systems. Yet interannual variability significantly impacts the generation from one year to another of renewable power systems such as wind and PV. Consequently, the interannual variability of power generation corresponds to the interannual variability of capital returns on investment. The penetration of PV systems within the Hawaiian Electric Companies' portfolio has rapidly accelerated in recent years and is expected to continue to increase given the state's energy objectives laid out by the Hawaii Clean Energy Initiative. We use the National Solar Radiation Database (1998-2015) to characterize the interannual variability of the solar irradiance and meteorological conditions across the State of Hawaii. These data sets are passed to the National Renewable Energy Laboratory's System Advisory Model (SAM) to calculate an 18-year PV power generation data set to characterize the variability of PV power generation. We calculate the interannual coefficient of variability (COV) for annual average global horizontal irradiance (GHI) on the order of 2% and COV for annual capacity factor on the order of 3% across the Hawaiian archipelago. Regarding the interannual variability of seasonal trends, we calculate the COV for monthly average GHI values on the order of 5% and COV for monthly capacity factor on the order of 10%. We model residential-scale and utility-scale PV systems and calculate the economic returns of each system via the payback period and the net present value. We demonstrate that studies based on single-year data sets for economic evaluations reach conclusions that deviate from the true values realized by accounting for interannual variability.

14 SOLAR ENERGY↗

DOE OSTI2025

Data-Enabled Fusion Technology (Final Scientific/Technical Report)

Advancing Scientific Understanding in Fusion Energy and Machine Learning This research represented a significant step forward in machine learning (ML) applications for fusion energy experiments. The project integrated advanced data-driven modeling, optimization techniques, and artificial intelligence to enhance the predictive capabilities and operational efficiency of plasma-based fusion systems. Specifically, tasks focused on ML-enhanced diagnostics, operator guidance tools, and predictive modeling helped improve the ability to interpret complex fusion experiments. Key areas of advancement included: 1) data-driven plasma control, i.e., using ML algorithms to optimize experimental conditions and classify plasma behaviors based on historical data; 2) spectroscopy and diagnostics, i.e., applying AI models to extract previously inaccessible insights from experimental spectroscopy data; and 3) configuration mapping and operator guidance, i.e., developing a predictive framework to assist scientists in identifying the most effective experimental parameters, reducing reliance on manual adjustments. By refining these ML-driven techniques, the project contributed to the broader scientific community’s understanding of plasma dynamics and fusion energy viability. Technical Effectiveness and Economic Feasibility The methods investigated demonstrated high technical effectiveness, as reflected in milestones assessing the predictive accuracy, performance, and optimization of fusion configurations. The development of an Operator Guidance Tool (OGT), for example, led to more precise control of plasma conditions by learning from experimental data and offering real-time adjustments. From an economic standpoint, DeFT provided: 1) the ability to reduce trial-and-error experimentation, which lowered operational costs; 2) improved data interpretation methods, which enabled more efficient resource allocation in large-scale fusion research projects; and 3) the automation of key diagnostic tasks, which reduced manual labor and human error, increasing overall efficiency. 13 The final assessments of predictive models and optimization strategies demonstrated that these approaches were scalable and could be implemented across multiple fusion energy research programs. Public Benefit and Societal Impact This project contributed directly to the broader goal of achieving sustainable and commercially viable fusion energy, which had profound implications for clean energy production and climate change mitigation. The integration of AI-driven solutions into fusion research: 1) sped up scientific discovery, accelerating progress towards achieving energy breakthroughs; 2) reduced the cost of experimentation, making fusion research more accessible; and 3) provided a framework for future AI applications in high-energy physics, benefiting adjacent fields like space exploration, material science, and renewable energy. Additionally, by fostering collaborations between AI researchers and plasma physicists, this project promoted interdisciplinary innovation that could lead to broader applications beyond fusion research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2011

Advanced virtual energy simulation training and research: IGCC with CO2 capture power plant

In this presentation, we highlight the deployment of a real-time dynamic simulator of an integrated gasification combined cycle (IGCC) power plant with CO{sub 2} capture at the Department of Energy's (DOE) National Energy Technology Laboratory's (NETL) Advanced Virtual Energy Simulation Training and Research (AVESTARTM) Center. The Center was established as part of the DOE's accelerating initiative to advance new clean coal technology for power generation. IGCC systems are an attractive technology option, generating low-cost electricity by converting coal and/or other fuels into a clean synthesis gas mixture in a process that is efficient and environmentally superior to conventional power plants. The IGCC dynamic simulator builds on, and reaches beyond, conventional power plant simulators to merge, for the first time, a 'gasification with CO{sub 2} capture' process simulator with a 'combined-cycle' power simulator. Fueled with coal, petroleum coke, and/or biomass, the gasification island of the simulated IGCC plant consists of two oxygen-blown, downward-fired, entrained-flow, slagging gasifiers with radiant syngas coolers and two-stage sour shift reactors, followed by a dual-stage acid gas removal process for CO{sub 2} capture. The combined cycle island consists of two F-class gas turbines, steam turbine, and a heat recovery steam generator with three-pressure levels. The dynamic simulator can be used for normal base-load operation, as well as plant start-up and shut down. The real-time dynamic simulator also responds satisfactorily to process disturbances, feedstock blending and switchovers, fluctuations in ambient conditions, and power demand load shedding. In addition, the full-scope simulator handles a wide range of abnormal situations, including equipment malfunctions and failures, together with changes initiated through actions from plant field operators. By providing a comprehensive IGCC operator training system, the AVESTAR Center is poised to develop a workforce well-prepared to operate and control commercial-scale gasification-based power plants capable of 90% pre-combustion CO{sub 2} capture and compression, as well as low sulfur, mercury, and NOx emissions. With additional support from the NETL-Regional University Alliance (NETL-RUA), the Center will educate and train engineering students and researchers by providing hands-on 'learning by operating' experience The AVESTAR Center also offers unique collaborative R&D opportunities in high-fidelity dynamic modeling, advanced process control, real-time optimization, and virtual plant simulation. Objectives and goals are aimed at safe and effective management of power generation systems for optimal efficiency, while protecting the environment. To add another dimension of realism to the AVESTAR experience, NETL will introduce an immersive training system with innovative three-dimensional virtual reality technology. Wearing a stereoscopic headset or eyewear, trainees will enter an interactive virtual environment that will allow them to move freely throughout the simulated 3-D facility to study and learn various aspects of IGCC plant operation, control, and safety. Such combined operator and immersive training systems go beyond traditional simulation and include more realistic scenarios, improved communication, and collaboration among co-workers.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Collimation Systems for the PSR

This note provides a review of collimator systems being used or considered in high-intensity proton accelerators like SNS, J-PARC, LHC, and PIP-II. These facilities use collimators to remove beam halo, restrict transverse size and momentum in the beam to constrain beam losses around collimators and minimize beam losses downstream, particularly losses arising from particles missing the design location at the stripping foil when injected into the proton storage ring. Collimators are placed either in the transport injection lines (single-pass collimators) or in the rings (multi-pass collimators). Collimators in the transport line are placed around stripping foils in H- accelerators, allowing the beamline optics to get rid of the unstripped protons into well localized absorbers. Rings and proton accelerators mostly rely on tungsten scrapers and collimators in a multi-stage configuration to clean the scattered beam particles mainly responsible for heavy losses at high energies. Placement of the collimators is carefully chosen in terms of the right phase advance to maximize the collimating efficiency, whether the collimation is intended to match an injection stripping foil or a downstream acceptance. Collimation systems are designed with the specific concerns of each facility in mind, although all of them prioritize the minimization of activation due to beam losses to enable hands-on access during maintenance periods. At LANSCE, there are no high-energy collimators, although pairs of horizontal and vertical jaws are routinely used in the LEBT to clean and control the transverse beam profile delivered downstream. This report will help in understanding, together with the beam dynamics simulations, which collimation schemes would be most effective for the PSR upgrade. For example, SNS designed off-momentum collimators to be placed in a 90° arc bend, a high-dispersion region in the beam injection line, very similar to the bend at Line D in LANSCE. This system was very effective at minimizing losses during injection into the SNS accumulator ring and is being re-designed for future operation.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

HydroGEN Consortium

HydroGEN Energy Materials Network (EMN) is an U.S. Department of Energy (DOE) EERE Hydrogen and Fuel Cell Technologies Office (HFTO)-funded consortium that aims to accelerate the discovery and development of advanced water splitting materials (AWSM) for clean, low-cost hydrogen production. Materials innovations are key to enhancing performance, durability, and cost of hydrogen generation technologies. HydroGEN is focused on low technology readiness level AWS technologies, including low- (alkaline exchanged membrane electrolysis) and high-temperature electrolysis (proton-conducting solid oxide electrolysis), photoelectrochecmical (PEC) and thermochemical (TCH) water splitting. The AWS technologies in this consortium study proton conduction in solid oxide electrolysis and hydroxide conduction in polymer electrolysis, and proton transport in photoelectrochemical water splitting. This presentation will provide an overview of the HydroGEN EMN and technical highlights of a few lab-led and DOE-awarded "seedling" R&D projects. HydroGEN continues to grow its community of industry, university, and national laboratories, forming a national innovation ecosystem focused on renewable hydrogen production.

08 HYDROGEN↗

NASA NTRS1995

CO2 (dry ice) cleaning system

Tomco Equipment Company has participated in the dry ice (solid carbon dioxide, CO2) cleaning industry for over ten years as a pioneer in the manufacturer of high density, dry ice cleaning pellet production equipment. For over four years Tomco high density pelletizers have been available to the dry ice cleaning industry. Approximately one year ago Tomco introduced the DI-250, a new dry ice blast unit making Tomco a single source supplier for sublimable media, particle blast, cleaning systems. This new blast unit is an all pneumatic, single discharge hose device. It meters the insertion of 1/8 inch diameter (or smaller), high density, dry ice pellets into a high pressure, propellant gas stream. The dry ice and propellant streams are controlled and mixed from the blast cabinet. From there the mixture is transported to the nozzle where the pellets are accelerated to an appropriate blasting velocity. When directed to impact upon a target area, these dry ice pellets have sufficient energy to effectively remove most surface coatings through dry, abrasive contact. The meta-stable, dry ice pellets used for CO2 cleaning, while labeled 'high density,' are less dense than alternate, abrasive, particle blast media. In addition, after contacting the target surface, they return to their equilibrium condition: a superheated gas state. Most currently used grit blasting media are silicon dioxide based, which possess a sharp tetrahedral molecular structure. Silicon dioxide crystal structures will always produce smaller sharp-edged replicas of the original crystal upon fracture. Larger, softer dry ice pellets do not share the same sharp-edged crystalline structures as their non-sublimable counterparts when broken. In fact, upon contact with the target surface, dry ice pellets will plastically deform and break apart. As such, dry ice cleaning is less harmful to sensitive substrates, workers and the environment than chemical or abrasive cleaning systems. Dry ice cleaning system components include: a dry ice pellet supply, a non-reactive propellant gas source, a pellet and propellant metering device, and a media transport and acceleration hose and nozzle arrangement. Dry ice cleaning system operating parameters include: choice of propellant gas, its pressure and temperature, dry ice mass flow rate, dry ice pellet size and shape, and acceleration nozzle configuration. These parameters may be modified to fit different applications. The growth of the dry ice cleaning industry will depend upon timely data acquisition of the effects that independent changes in these parameters have on cleaning rates, with respect to different surface coating and substrate combinations. With this data, optimization of cleaning rates for particular applications will be possible. The analysis of the applicable range of modulation of these parameters, within system component mechanical constraints, has just begun.

Barnett, Donald M.↗

DOE OSTI2026

HydroGEN Consortium: Advancements in Hydrogen Production

08 HYDROGEN↗

DOE OSTI2018

Phase I Microgrid Cost Study: Data Collection and Analysis of Microgrid Costs in the United States

The U.S. Department of Energy (DOE) Office of Electricity Microgrid Cost Study project is looking at identifying the costs of components, integration and installation of U.S. microgrids and project cost improvements and technical accelerators over the next 5 years and beyond. This information could then be used by the DOE among others, to develop R&D agendas for the development of the next generation microgrids that provide cost effective, reliable and clean energy solutions. Microgrids are gaining in popularity because of their adaptability and flexible expandability, the need for increased electricity reliability, the increased affordability of distributed energy resources (DERs) and grid intelligence devices, goals to reduce greenhouse gas emissions, and other factors. The U.S. Department of Energy commissioned the National Renewable Energy Laboratory to complete a microgrid cost study and develop a microgrid cost model. The goal is to elucidate the variables that have the highest impact on costs as well as potential areas for cost reduction. This study consists of two phases. Phase I comprises the collection and analysis of data from microgrid projects built in the United States and is the subject of this report. In Phase II, NREL will assess current barriers facing the industry and identify potential solutions with help from industry representatives. Microgrid components are classified as follows in the form used to collect cost data from industry representatives for NREL's microgrid cost database: DERs: diesel, natural gas, combined heat and power (CHP), biofuel, solar photovoltaic (PV), wind, and fuel cell and energy storage; microgrid controller: primary, secondary, or tertiary; additional infrastructure: distribution system infrastructure, information technology communications upgrades, metering, etc.; soft costs: engineering, construction, commissioning, and regulatory. The purposes of Phase I are to better determine the contribution of individual components to total project size and to identify cost differences in projects within the same market segment. Phase II will use the results of Phase I to have an initial indication of the costs that might be driving the cost of development the most.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Transforming Energy through Computational Science: Computing for Clean Energy

This fact sheet discusses the opportunity space for NREL's computational science capabilities to address national clean energy objectives. Achieving a carbon-free power sector by 2035 as a step towards a decarbonized U.S. energy economy in 2050 will require major advances in power generation, autonomous energy systems, transportation, and buildings/communities. Development of integrated modeling approaches for complex energy systems will be essential for deployment. Success requires developments in optimization and control theory, complemented by machine learning (ML) and artificial intelligence (AI), all of which in turn need targeted investments in breadth and scale of computing. This document defines an opportunity space where: embracing computing can link established research and development (R&D) to a decarbonization agenda; pursuing emerging approaches can accelerate the pace of technology advancement across the portfolio; and leading by example could reduce the carbon footprint of computing worldwide.

advanced computing↗

DOE OSTI2014

Pit 9 Category of Transuranic Waste Stored Below Ground within Area G

A large wildfire called the Las Conchas Fire burned large areas near Los Alamos National Laboratory (LANL) in 2011 and heightened public concern and news media attention over transuranic (TRU) waste stored at LANL’s Technical Area 54 (TA-54) Area G waste management facility. The removal of TRU waste from Area G had been placed at a lower priority in budget decisions for environmental cleanup at LANL because TRU waste removal is not included in the March 2005 Compliance Order on Consent (Reference 1) that is the primary regulatory driver for environmental cleanup at LANL. The Consent Order is an agreement between LANL and the New Mexico Environment Department (NMED) that contains specific requirements and schedules for cleaning up historical contamination at the LANL site. After the Las Conchas Fire, discussions were held by the U.S. Department of Energy (DOE) with the NMED on accelerating TRU waste removal from LANL and disposing it at the Waste Isolation Pilot Plant (WIPP).This report summarizes available information on the origin, configuration, and composition of the waste containers within Pit 9, their physical and radiological characteristics, and issues that may be encountered in their retrieval and processing. Review of the available information indicates that Pit 9 should present no major issues in retrieval and processing, and most drums contain TRU waste that can be shipped to WIPP. The primary concern in retrieval is the integrity of containers that have been stored below-ground for 35 to 40 years. The most likely issue that will be encountered in processing containers retrieved from Pit 9 is the potential for items that are prohibited at WIPP such as sealed containers greater than four liters in size and free liquids that exceed limits for WIPP.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗