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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

NASA Perspective and Modeling of Thermal Runaway Propagation Mitigation in Aerospace Batteries

NASA has traditionally sought to reduce the likelihood of a single cell thermal runaway (TR) in their aerospace batteries to an absolute minimum by employing rigorous screening program of the cells. There was generally a belief that TR propagation resulting in catastrophic failure of the battery was a forgone conclusion for densely packed aerospace lithium-ion batteries. As it turns out, this may not be the case. An increasing number of purportedly TR propagation-resistant batteries are appearing among NASA partners in the commercial sector and the Department of Defense. In the recent update of the battery safety standard (JSC 20793) to address this paradigm shift, the NASA community included requirements for assessing TR severity and identifying simple, low-cost severity reduction measures. Unfortunately, there are no best-practice guidelines for this work in the Agency, so the first project team attempting to meet these requirements would have an undue burden placed upon them. A NASA engineering Safety Center (NESC) team set out to perform pathfinding activities for meeting those requirements. This presentation will provide contextual background to this effort, as well as initial results in attempting to model and simulate TR heat transfer and propagation within battery designs.

safety↗
DOE OSTI2024

Artificial Intelligence/Machine Learning Technology in Power System Applications

The primary purpose of this report is to provide an overview of the advancement in artificial intelligence and machine learning (AI/ML) technologies and their applications in power systems. It offers a foundation for understanding the transformative role of AI/ML in power systems and aims to stimulate further research and development in this area. This report begins with a historical perspective of AI/ML technologies, then explores their advancement to today’s prominence. The document highlights key contributors to the success of AI/ML technologies, including increased computational power, greater data availability, innovative algorithms, and advanced tools. It further introduces various AI/ML techniques, including supervised, unsupervised and reinforcement learning, graph neural networks, and generative AI. It also emphasizes the critical importance of ensuring the safety, security, and trustworthiness of these AI/ML techniques within this sector. The report reviews the recent representative advancements in various power system applications enhanced by AI/ML techniques, underscoring key developments and their transformative impact as evidenced by numerous studies. It also explores both the opportunities and challenges associated with the application of AI/ML technologies to improve power system applications. While the report extensively covers AI/ML applications in power systems, focusing primarily on the technical and operational aspects, it may not thoroughly explore the sociopolitical, economic, and broader regulatory implications of AI/ML integration in power systems. AI/ML techniques hold significant potential for enhancing power system applications; however, they are not omnipotent. It is crucial to acknowledge their limitations and understand that they may not be able to address all challenges in the power system domain. Various factors must be considered that influence the implementation, adoption, and effectiveness of AI/ML solutions, including but not limited to safety, security, transparency, and trustworthiness. Additionally, the incorporation of advanced human–machine interfaces is essential, as it enables humans to validate the effectiveness of AI/ML solutions while remaining actively engaged, fostering trust in AI/ML deployment. Finally, the report summarizes AI/ML research activities supported by the Department of Energy (DOE) Office of Electricity (OE) through the Advanced Grid Modeling (AGM) program. The work aligns with the interests and mission of DOE-OE AGM, with the report serving as a resource for identifying existing progress and for pinpointing future applications within AI/ML that need further exploration and support.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Learning to Solve Large-Scale Security-Constrained Unit Commitment Problems

Security-constrained unit commitment (SCUC) is a fundamental problem in power systems and electricity markets. In practical settings, SCUC is repeatedly solved via mixed-integer linear programming (MIP), sometimes multiple times per day, with only minor changes in input data. In this work, we propose a number of machine learning techniques to effectively extract information from previously solved instances in order to significantly improve the computational performance of MIP solvers when solving similar instances in the future. Based on statistical data, we predict redundant constraints in the formulation, good initial feasible solutions, and affine subspaces where the optimal solution is likely to lie, leading to a significant reduction in problem size. Computational results on a diverse set of realistic and large-scale instances show that using the proposed techniques, SCUC can be solved on average 4.3 times faster with optimality guarantees and 10.2 times faster without optimality guarantees, with no observed reduction in solution quality. Out-of-distribution experiments provide evidence that the method is somewhat robust against data-set shift. Summary of Contribution. The paper describes a novel computational method, based on a combination of mixed-integer linear programming (MILP) and machine learning (ML), to solve a challenging and fundamental optimization problem in the energy sector. The method advances the state-of-the-art, not only for this particular problem, but also, more generally, in solving discrete optimization problems via ML. We expect that the techniques presented can be readily used by practitioners in the energy sector and adapted, by researchers in other fields, to other challenging operations research problems that are solved routinely.

Machine Learning↗
DOE OSTI2023

Safer Foundation Solar Demands Skill Collaborative

The milestones and accomplishments achieved in Safer’s Solar Demands Skill Training program required a collective effort of stakeholders. The ability to achieve the desired results and impact lives of the population we serve works best when collaborating with community stakeholders such as community-based organizations, faith-based organizations, community activists, local law enforcement, community residents, employers, and elected and appointed officials. We are working harder than ever to place clients in-demand careers and high-growth industry sectors. Our employer engagement with high growth sectors continues to increase, we have been able to deepen our relationships in this space by providing in demand stackable credential training. Launched our initiative in the green job space by partnering with organizations like ComEd, the Department of Energy, community-based organizations, faith-based organizations, and manufacturers that helped to train clients in the green jobs and renewable energy space. By the end of the year, we will have completed our tenth cohort of photovoltaic solar installation training. The training has been used as a foundation for solar panel installers to acquire new skills in in the green jobs career pathways, such as sales and customer service. It has also served as a pipeline to union-level trade positions through the skills participants obtained through partnership engagement. Safer Foundation's policy and advocacy team plays a major role in expanding opportunities for people with records to over one hundred occupations, including the trades. This reform has allowed many to secure living wage employment, reducing the high recidivism rate within Illinois. Safer continues to build our social enterprise with Reconstructive Technology Partners (RTP). RTP is introducing people with records to the construction trades such as solar, carpentry and electrical through residential remodeling of homes on smaller construction projects. Understanding the need to have a greater community presence, outreach was extended to a boots on the ground model, including, but not limited to door-to-door engagement, DE-EE0008571 Safer Foundation Page 4 of 29 local radio broadcasting and print ads in local newspapers. We continue to seek innovative ways to increase Safer Foundations' presence in the renewable energy space. Outreach efforts gave us an opportunity to share critical reentry information and opportunities about our PV installer program. Giving us reach with local and national audiences alike. We launched a systematic approach to improving client data and client tracking through an evidence-based practices initiative. That implemented an agency wide cross-functional data management system. The system supported our goal of reviewing, evaluating, and making recommendations to improve operational processes, program delivery, information sharing, and more. Played a significant part in the success of the solar program. Finally, economists around the nation agree that there is a significant labor shortage. The shortage directly threatens our ability to sustain our economic growth; if employers do not have access to the workers they need, it can lead to a shutdown in the economic recovery. The demand for Safer Foundation services is more important and impactful than ever. We will continue to build upon our 50 years of experience to address the challenges ahead and serve more people in a better way. We are confident we will accomplish beautiful things that benefit everyone involved because together, we are powerful.

14 SOLAR ENERGY↗
DOE OSTI2024

Large Ensemble Exploration of Global Energy Transitions Under National Emissions Pledges

Global climate goals require a transition to a deeply decarbonized energy system. Meeting the objectives of the Paris Agreement through countries' nationally determined contributions and long-term strategies represents a complex problem with consequences across multiple systems shrouded by deep uncertainty. Robust, large-ensemble methods and analyses mapping a wide range of possible future states of the world are needed to help policymakers design effective strategies to meet emissions reduction goals. This study contributes a scenario discovery analysis applied to a large ensemble of 5,760 model realizations generated using the Global Change Analysis Model. Eleven energy-related uncertainties are systematically varied, representing national mitigation pledges, institutional factors, and techno-economic parameters, among others. The resulting ensemble maps how uncertainties impact common energy system metrics used to characterize national and global pathways toward deep decarbonization. Results show globally consistent but regionally variable energy transitions as measured by multiple metrics, including electricity costs and stranded assets. Larger economies and developing regions experience more severe economic outcomes across a broad sampling of uncertainty. The scale of CO 2 removal globally determines how much the energy system can continue to emit, but the relative role of different CO 2 removal options in meeting decarbonization goals varies across regions. Previous studies characterizing uncertainty have typically focused on a few scenarios, and other large-ensemble work has not (to our knowledge) combined this framework with national emissions pledges or institutional factors. Our results underscore the value of large-ensemble scenario discovery for decision support as countries begin to design strategies to meet their goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2009

Radial Halbach Magnetic Bearings

Radial Halbach magnetic bearings have been investigated as part of an effort to develop increasingly reliable noncontact bearings for future high-speed rotary machines that may be used in such applications as aircraft, industrial, and land-vehicle power systems and in some medical and scientific instrumentation systems. Radial Halbach magnetic bearings are based on the same principle as that of axial Halbach magnetic bearings, differing in geometry as the names of these two types of bearings suggest. Both radial and axial Halbach magnetic bearings are passive in the sense that unlike most other magnetic bearings that have been developed in recent years, they effect stable magnetic levitation without need for complex active control. Axial Halbach magnetic bearings were described in Axial Halbach Magnetic Bearings (LEW-18066-1), NASA Tech Briefs, Vol. 32, No. 7 (July 2008), page 85. In the remainder of this article, the description of the principle of operation from the cited prior article is recapitulated and updated to incorporate the present radial geometry. In simplest terms, the basic principle of levitation in an axial or radial Halbach magnetic bearing is that of the repulsive electromagnetic force between (1) a moving permanent magnet and (2) an electric current induced in a stationary electrical conductor by the motion of the magnetic field. An axial or radial Halbach bearing includes multiple permanent magnets arranged in a Halbach array ("Halbach array" is defined below) in a rotor and multiple conductors in the form of wire coils in a stator, all arranged so the rotary motion produces an axial or radial repulsion that is sufficient to levitate the rotor. A basic Halbach array (see Figure 1) consists of a row of permanent magnets, each oriented so that its magnetic field is at a right angle to that of the adjacent magnet, and the right-angle turns are sequenced so as to maximize the magnitude of the magnetic flux density on one side of the row while minimizing it on the opposite side. The advantage of this configuration is that it makes it possible to approach the theoretical maximum force per unit area that could be exerted by a given amount of permanent-magnet material. The configuration is named after physicist Klaus Halbach, who conceived it for use in particle accelerators. Halbach arrays have also been studied for use in magnetic-levitation ("maglev") railroad trains. In a radial Halbach magnetic bearing, the basic Halbach arrangement is modified into a symmetrical arrangement of sector-shaped permanent magnets mounted on the outer cylindrical surface of a drum rotor (see Figure 2). The magnets are oriented to concentrate the magnetic field on their radially outermost surface. The stator coils are mounted in a stator shell surrounding the rotor.

Eichenberg, Dennis J.↗
DOE OSTI2025

A method for assessing economic, environmental, and reliability tradeoffs of interregional transmission connecting ERCOT (the Texas grid) to the eastern and western grids

Reliable development of the power grid is an evolving concern for humanity due to extreme weather that frequently threatens power sector infrastructure. The state of Texas is a uniquely structured testbed for grid planners to study when looking for solutions to development, innovation, and overcoming such challenges. Because of its size and islanded structure, Texas is small enough to model, but big enough to matter. Texas is a global leader in energy production, energy consumption, and maintains an unusually diverse fuel mix. In addition, the state has experienced winter freezes, heat waves, wind storms, droughts and floods that have threatened power sector infrastructure or caused recent blackouts and calls for demand side conservation. One of the most devastating of these events was the North American winter storm, dubbed “Winter Storm Uri” by the Weather Channel, that froze the region in February 2021 and led to an extended power outage event that put the majority of Texan residents in darkness for days. While preparing to avoid such outage events in the future, various tools have been proposed to improve grid reliability, including energy efficiency, demand response, and distributed energy resources. An additional option would be to develop interregional transmission that connects the Texas grid to other national grids. To assess the merits of this idea, we developed a novel, universally-applicable and internationally-relevant framework to study how the Texas grid would evolve alongside access to various interregional ties. This method allows us to stress the synthetic grid structure and analyze how it would respond to the shock of a simulated winter storm event. Our method leverages open-source modeling tools, such as PowerGenome, pyGRETA, and GenX to synthesize unique zonal grid data, construct a consolidated network of model regions, and simulate different developmental pathways of capacity expansion and operational dispatch. We demonstrate our method with an analysis connecting the Electric Reliability Council of Texas (ERCOT), the grid that serves most of Texas, the Western Electricity Coordinating Council (WECC), the grid that serves the western half of the contiguous U.S., and the Eastern Interconnect, the grid that serves the eastern half of the contiguous U.S. Our results indicate that the cost-optimal capacity of interregional transmission connecting the ERCOT grid to other grids lies between 9–13 GW assuming baseline conditions. Building this amount of connecting capacity in one or multiple directions lowers the costs and emissions of development and operation by up to $16 billion and 257 million metric tonnes (MMT) respectively. Additionally, our results show that the interregional connections between ERCOT and other national grids reduce the amount of total load shed required through mild winter storm events. However, our results also show that there is a threshold of very extreme winter storm conditions, spanning multiple service areas, above which the connections exacerbate resource adequacy problems. Therefore, the results indicate that the connections need to be carefully planned alongside the rest of the grid infrastructure to avoid over-reliance on specific resources or technology options.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Measurement of the axial vector form factor from antineutrino–proton scattering

Scattering of high energy particles from nucleons probes their structure, as was done in the experiments that established the non-zero size of the proton using electron beams. The use of charged leptons as scattering probes enables measuring the distribution of electric charges, which is encoded in the vector form factors of the nucleon. Scattering weakly interacting neutrinos gives the opportunity to measure both vector and axial vector form factors of the nucleon, providing an additional, complementary probe of their structure. The nucleon transition axial form factor, F A , can be measured from neutrino scattering from free nucleons, ν μ n → μ – p and ν¯ μ p → μ + n , as a function of the negative four-momentum transfer squared (Q 2 ). Up to now, FA(Q 2 ) has been extracted from the bound nucleons in neutrino–deuterium scattering, which requires uncertain nuclear corrections. Here we report the first high-statistics measurement, to our knowledge, of the ν¯ μ p → μ + n cross-section from the hydrogen atom, using the plastic scintillator target of the MINERvA experiment, extracting F A from free proton targets and measuring the nucleon axial charge radius, r A , to be 0.73 ± 0.17 fm. The antineutrino–hydrogen scattering presented here can access the axial form factor without the need for nuclear theory corrections, and enables direct comparisons with the increasingly precise lattice quantum chromodynamics computations. Finally, the tools developed for this analysis and the result presented are substantial advancements in our capabilities to understand the nucleon structure in the weak sector, and also help the current and future neutrino oscillation experiments to better constrain neutrino interaction models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Quantifying Impacts of Renewable Electricity Deployment on Air Quality and Human Health in Southeast Asia Based on Aims III Scenarios

Exposure to outdoor air pollution is the largest environmental risk factor for death and disease worldwide, associated with millions of cases of excess deaths (mortality) each year. Although there are many pollutants in the air that affect our health, the most important class of pollutants is fine particulate matter, PM 2.5 , which are airborne particles of diameter ≤2.5 micrometers (µm). These particles are small enough to deposit deep in the respiratory system where they can then enter the bloodstream, traveling and causing damage to other bodily systems. Exposure to outdoor (ambient) PM 2.5 has been found to be the most important environmental risk factor for mortality in Southeast Asia, associated with 130,000 - 320,000 excess deaths in Association of Southeast Asian Nations (ASEAN) member countries in 2019. Southeast Asia, especially its mega-cities, but also other areas, has some of the worst air quality in the world. Almost all human activity emits air pollutants. Fine particulate matter is both directly emitted and formed in the atmosphere through chemical reactions, the latter of which requires modeling to predict. Power generation is one of the major sources of air pollutants that lead to elevated concentrations of fine particulate matter, including in Southeast Asia. Fossil fuel combustion for power generation, especially coal but also diesel, is the main source of air pollutant emissions from power generation. While natural gas burns cleaner than coal or diesel, in the quantities combusted for power generation in Southeast Asia, it is also a significant emitter. This study augments the ASEAN Interconnection Masterplan Study III (AIMS III) by quantifying changes to air quality and human health that result from its renewable integration and transmission interconnection scenarios. Performing this analysis requires translation of the changes in projected generation from different power sector fuel sources in the AIMS III scenarios to changes in air pollutant emissions, developing what's known as an emissions inventory for each scenario and year evaluated. We then use for the first time a new global, reduced-complexity air quality model to transform the changes in emissions to changes in air pollutant concentration of the deadliest air pollutant for human health, fine particulate matter (or PM 2.5 ). The air quality model, Global InMAP, then utilizes the location of human population in ASEAN countries to calculate exposure to PM 2.5 concentration changes and translates that to estimates of excess mortality attributable to the AIMS III scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Mechanistic origins of corrosion protection of aluminum alloys by graphene/polyetherimide nanocomposite coatings

Light-weighting vehicular components through adoption of light-metal structural alloys holds promise for reducing the fuel consumption of internal combustion engine vehicles and increasing the range of battery electric vehicles. However, the alloyed microstructure and surface precipitates of aluminum alloys render these materials susceptible to corrosion under modest excursions from neutral pH. Traditional chromium-based anodic passivation layers are subject to increasingly stringent environmental regulations, whereas options for sacrificial cathodic films are sparse for electropositive metals. While hybrid nanocomposite coatings have shown initial promise, mechanistic underpinnings remain poorly understood. Here, a fully imidized polyetherimide (PEI) resin is utilized as the continuous phase with inclusion of unfunctionalized exfoliated graphite (UFG). A comprehensive investigation of the mechanisms of corrosion protection reveals key fundamental design principles underpinning corrosion inhibition. First, strong interfacial adhesion, which for PEI is facilitated by binding of imide carbonyl moieties to Lewis acidic sites on Al surfaces. Second, the miscibility of ion-impervious nanoscopic UFG fillers and stabilization of a substantial interphase region at UFG/PEI boundaries that result in minimizing the free volume at the filler/polymer interface. Finally, extended tortuosity of ion diffusion pathways imbued by the below-percolation-threshold 2D fillers. These three design principles help govern and modulate ion transport from electrolyte/coating interfaces to the coating/metal interface and are crucial for the extended preservation of barrier properties. The results suggest an approach to systematically activate multiple modes of corrosion inhibition through rational design of hybrid nanocomposite coatings across hard-to-abate sectors where light metal alloys are likely to play an increasingly prominent role.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Coal as Value-Added for Lithium Battery Anodes (Final Report)

Graphite is a basic material used for energy storage in lithium-ion (Li-ion) batteries. More than 70% of worldwide graphite production and nearly 50% of the annual graphite supply for the United States comes from China. Potential economic and national security concerns exist because Li-ion batteries are used not only for the fast-growing electrical vehicle market (15.6% compound annual growth rate [CAGR] from 2018 to 2028 in North America), but also for defense applications including unmanned aerial and ground vehicles. Development of an alternative formulation for Li-ion batteries is key. Building upon previous research confirming the ability of silicon alloys to improve the energy density of anodes, Semplastics developed a novel material based on our X-MAT® polymer-derived ceramic (PDC) technology. The X-MAT anode material is a composite of chemically tailored silicon oxycarbide (SiOC) and domestically sourced coal powder, designed to be a drop-in replacement for graphite within Li-ion battery anodes. Preliminary tests of this material showed more than twice the reversible capacity of graphite anodes (1,000 mAh/g vs. 372 mAh/g), with excellent stability and capacity retention, almost 100% coulombic efficiency, low voltage potential, and low thermal expansion. At full adoption in 2024, we expect the coal utilization to reach 27,300 tons. Through this project, Semplastics proposed to complete development and begin commercialization of this material. The objective was to determine the best formulation for technical performance and economic viability. At the end of the project, the X-MAT anode material is ready for implementation into existing battery manufacturing processes and can have a significant impact on the utilization of coal, with positive effects for the mining sector and the mitigation of carbon dioxide (CO 2 ) emissions.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Integrating environmental understanding into freshwater floatovoltaic deployment using an effects hierarchy and decision trees

Abstract In an era of looming land scarcity and environmental degradation, the development of low carbon energy systems without adverse impacts on land and land-based resources is a global challenge. ‘Floatovoltaic’ energy systems—comprising floating photovoltaic (PV) panels over water—are an appealing source of low carbon energy as they spare land for other uses and attain greater electricity outputs compared to land-based systems. However, to date little is understood of the impacts of floatovoltaics on the hosting water body. Anticipating changes to water body processes, properties and services owing to floatovoltaic deployment represents a critical knowledge gap that may result in poor societal choices and water body governance. Here, we developed a theoretically-derived hierarchical effects framework for the assessment of floatovoltaic impacts on freshwater water bodies, emphasising ecological interactions. We describe how the presence of floatovoltaic systems may dramatically alter the air-water interface, with subsequent implications for surface meteorology, air-water fluxes and physical, chemical and biological properties of the recipient water body. We apply knowledge from this framework to delineate three response typologies—‘ magnitude’ , those for which the direction and magnitude of effect can be predicted; ‘ direction’ , those for which only the direction of effect can be predicted; and ‘ uncertain’ , those for which the response cannot be predicted—characterised by the relative importance of levels in the effects hierarchy. Illustrative decision trees are developed for an example water body response within each typology, specifically, evaporative water loss, cyanobacterial biomass, and phosphorus release from bed sediments, and implications for ecosystem services, including climate regulation, are discussed. Finally, the potential to use the new understanding of likely ecosystem perturbations to direct floatovoltaic design innovations and identify future research priorities is outlined, showcasing how inter-sectoral collaboration and environmental science can inform and optimise this low carbon, land-sparing renewable energy for ecosystem gains.

Environmental Sciences & Ecology↗
NASA NTRS1994

Ground and satellite observations of postdawn aurorae near the time of a sudden storm commencement

Meridian scanning photometer measurements taken in the magnetic postdawn sector at Longyearbyen, Svalbard, between 0300 and 0630 UT on December 29, 1981, are analyzed in conjunction with particle and field data retrieved during two near passes of the Dynamics Explorer 2 (DE 2) satellite. The interval included a sudden storm commencement (SSC) at 0455 UT. Pre-SSC optical and particle measurements showed a system of arcs that are spaced at approximately 1.1 deg intervals in magnetic latitude, embedded within the region 1 current system and span the convection reversal. The softer particle precipitation appears to have a source near the flanks of the magnetotail while the harder, more equatorward precipitation originates closer to Earth. During the SSC period the entire sky brightened, with enhanced 630.0-nm emissions extending from the northern horizon to south of magnetic zenith; intense but spatially separated 557.7-nm emissions dominated the southern horizon. DE 2 detected more than an order of magnitude increase and near isotropization of ring current electron fluxes, enhanced precipitation from the plasma sheet and significantly decreases auroral zone convection. Region 1/region 2 currents remained, with wavelike structures superposed. A dual timescale response to the SSC is consistent with ground and satellite measurements. On few minute travel timescales for hydromagnetic waves to pass through the system, magnetospheric particles accelerate and precipitate to increase the ionospheric conductivity. Global, field-aligned currents change more slowly. To maintain similar field-aligned currents with higher ionospheric conductances requires reduced electric fields. After 0520 UT the optical emissions settled into stable, but latitudinally separated bands of 630.0- and 557.7-nm emissions characteristic of cleft and plasma sheet precipitation, respectively.

Egeland, A.↗
DOE OSTI2023

2023 Critical Materials Strategy

The global effort to curb carbon emissions is accelerating demand for clean energy technologies and the materials they rely on. Demand for these materials will only continue to grow, especially as some nations aim to achieve net zero emissions by 2050. While some major materials like steel, copper, and aluminum are already powering the fossil fuel economy, others are more minor materials with potential supply risks. These risks could jeopardize the ability to reduce greenhouse gas emissions within the desirable timeframe to avoid significant climate change. In some cases, it may be necessary to take action to improve the resilience of material supply chains and mitigate supply risks. Understanding the importance of individual materials to clean energy and the supply risks associated with them is necessary to identify which materials may serve as potential roadblocks to a clean energy future. The U.S. Department of Energy (DOE) issued a series of 13 supply chain deep dive assessment reports on various energy technologies in 2022 in response to President Biden’s Executive Order on America’s Supply Chains (E.O. 14017). These reports emphasized that supply chain bottlenecks can occur at any stage of the value chain from mining and refining to component and even sub-system manufacturing. The bottlenecks are a combination of factors such as material availability, equipment availability, work force availability and quality, logistics, regulatory framework, and market conditions. These bottlenecks were worsened during the global Covid-19 pandemic. Its lingering impacts have hindered capacity expansion for material supply chains and prevented product lead-time recovery. One approach to reduce supply chain risks for the United States is to have a strong domestic manufacturing sector with a diverse set of producers. Boosting responsible domestic production would require leveraging the latest science not only in material extraction but also in developing substitutes, recycling, reuse, and remanufacturing. This report is an updated analysis of previous Critical Materials Strategy (CMS) reports published by the DOE in 2010, 2011, and 2019 based on national and global priorities, technology advancement, and technology adoption trends. Like the CMS reports, this analysis presents the results of a formal material criticality assessment to identify which materials are critical to the continued deployment of clean energy technologies globally. The analysis in this report leveraged the DOE supply chain deep dive assessments to develop the initial list of materials to evaluate. This DOE Critical Materials Assessment (CMA) is conducted independently of criticality assessments performed by other U.S. government agencies, such as that conducted by the U.S. Geological Survey (USGS). This analysis complements the USGS critical minerals determination in three aspects. First, the DOE assessment is performed from a global perspective, while the USGS analysis focusses on the importance of minerals to the U.S. economy. Second, this report focuses on the importance of materials to clean energy technologies, rather than to the economy in general. Lastly, this study is forward looking to 2035 based on clean energy deployment scenarios, whereas the USGS assessment is retrospective. Materials evaluated in this report that do not appear in the USGS Critical Minerals List include copper, uranium, electrical steel, and SiC. A draft version of this report received ~80 public comments related to supporting data and methodological improvement. Those comments have been incorporated as much as possible where appropriate. Highlights of findings from this 2023 CMA include: Rare earth materials (neodymium, praseodymium, dysprosium, and terbium) used in magnets in electric vehicle (EV) motors and wind turbine generators continue to be critical. While dysprosium (Dy) and terbium (Tb) are both heavy rare earth elements that serve the same function in magnets, the criticality of Tb is slightly lower than that for Dy in the short term due to the widespread use of Dy in high-grade magnets and Tb’s present role as a substitute. Similarly, praseodymium (Pr) is critical in the medium term but only near critical in the short term because it is more substitutable in magnets than neodymium (Nd); Materials used in batteries for EVs and stationary storage are now considered to be critical. While cobalt (Co) was found to be critical in this and previous reports, lithium (Li) becomes critical in the medium term due to its broader use in various battery chemistries and the rampant growth of the EV industry. Natural graphite is a new addition in this assessment and is also found to be critical; Platinum group metals used in hydrogen electrolyzers, such as platinum (Pr) and iridium (Ir), are critical due to an increased focus on hydrogen technologies to achieve net zero carbon emissions, while those used in catalytic converters, such as rhodium (Rh) and palladium (Pd), were screened out due to the decreased importance of catalytic converters in the medium term; Gallium (Ga) continues to be critical due to its use in light-emitting diodes (LEDs). In addition, the use of Ga has increased in magnet manufacturing and in semiconductor in forms such as gallium arsenide (GaAs) or gallium nitride (GaN); Major materials like Aluminum (Al), copper (Cu), nickel (Ni), and silicon (Si) move from noncritical in the short term to near critical in the medium term due to their importance in electrification; Electrical steel is near critical due to its use in transformers for the grid and electric motors in EVs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Hamilton: Flexible, Open Source $10 Wireless Sensor System for Energy Efficient Building Operation

Sensors for improving building performance are rapidly populating the market, driven in part by the drive to reduce greenhouse gas emissions resulting from energy production as well as improve the interior environment for healthy and more productive spaces. UC Berkeley has led wireless sensor development over the past 25 years (e.g., Telos mote), with the Hamilton (named after Alexander Hamilton on the US $10 bill) as the most recent. The Hamilton sensor was designed as a low-cost high-performance sensor that is modular and interoperable. The objective of the Hamilton project was to create, evaluate and establish the technological foundations for secure and easy to deploy building energy efficiency applications utilizing pervasive, low-cost wireless sensors integrated with traditional Building Management Systems (BMS), consumer-sector building components, and powerful data analytics. The project included iterative hardware design, incorporating a high-performance database (BTrDb, http://btrdb.io/), creating and iterating the development of secure data middleware (BOSSwave, WAVE/WAVEMQ), working with and pushing the development of an open-source tiny operating system RiotOS, and implementing and improving protocols such as Thread/OpenThread and TCP/IP. The hardware benefited from careful design to drive down the cost; the design included a System-on-a-Chip (SoC), chip antenna, single crystal and five passive components. Careful design of the operating system created a low-power design to enable a long life with small batteries. The hardware included several sensors: temperature, radiant temperature, relative humidity, magnetometer, accelerometer, and light, with an optional occupancy (Passive InfraRed) sensor. The project was the basis of several applications, both internal to the research team and other researchers and professionals at other institutions. Several applications used the sensor hardware as the basis for other complex devices. Other applications used the sensors to improve building performance through interoperating with the building Heating Ventilation and Air-Conditioning (HVAC) system, such as using occupancy and/or distributed temperature sensing to reduce HVAC zone energy while still providing thermal comfort and to reduce peak loads in small commercial buildings. We demonstrated cloud-based energy analytics, implemented a schedule and a Model Predictive Controller in a small commercial building to optimize HVAC energy, occupancy and electricity price. Initial integration of these technological innovations was performed through the creation of execution containers containing the WAVE agent and various driver, proxy, or building system function logic. The research added to the understanding of efficient sensor hardware, secure middleware, time-series data management (high performance database), efficient communication protocols, and interoperating with applications and building systems. The project showed the technical effectiveness and economic feasibility of creating a low-cost, modular, and easy-to-deploy sensor. Through conversations with multiple end users, the research team discovered that many customers wanted data management and services in addition to the sensors. HamiltonIOT developed packages of sensors, border router, and data services to provide a seamless “plug-and-play” sensor deployment. Some customers were willing to pay for higher quality sensors (such as light); some customers wanted a robust enclosure (waterproof).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Prioritizing ICS Beachhead Systems for Cyber Vulnerability Testing

Cyber Testing for Resilient Industrial Control Systems™ (CyTRICS™) is the Department of Energy’s (DOE’s) program for cybersecurity vulnerability testing, digital subcomponent enumeration, and forensic assessment. CyTRICS leverages best-in-class test facilities and analytic capabilities at six DOE National Laboratories and strategic partnerships with key stakeholders including technology developers, manufacturers, asset owners and operators, and interagency partners. During the program’s development, CyTRICS established a unique methodology for prioritizing digital components within operational technology (OT) and industrial control systems (ICS) in the Energy Sector Industrial Base (ESIB) for cyber vulnerability testing. The CyTRICS Prioritization Process leverages multiple characteristics of systems, components, and their contextual deployment to calculate a quantification of individual digital components for CyTRICS testing. The initial version of the CyTRICS Prioritization Process was premised largely upon the impact which could result to an industrial control system if the digital component under testing was compromised, either through malicious means, faulty engineering, or other modes. The worldwide compromise of the SolarWinds Orion platform, first reported in December 2020, through malicious interference with the digital patching cycle was a watershed event in cyber supply chain security. The SolarWinds compromised demonstrated the strategic importance of certain types of ubiquitous software, and the ability to generate widespread cybersecurity effects. To address this challenge and as a part of the Department of Energy’s response to the SolarWinds compromise, DOE’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER) directed the National Laboratories to evolve the CyTRICS Prioritization Process methodology to encompass additional factors related to the strategic importance of digital components. CESER directed CyTRICS researchers to identify, characterize, and append strategic factors to the CyTRICS Prioritization Process to provide additional weight to these characteristics. National Laboratory expert researchers identified functionality, distribution, and platform characteristics for digital components in ICS and OT that they assessed would be likely targeted in strategic initial-access cyber attack. CyTRICS has termed these factors “ICS Beachhead Systems,” leveraging a definition first advanced by Schneider Electric, which is intended as a blanket term to encompass digital components, products, and systems in OT. This paper describes the ICS Beachhead Systems identified and the rationale for inclusion. As a next step in the research and refinement process, the National Laboratories will validate this initial set of characteristics against digital components evaluated by the CyTRICS program and current implementation of the CyTRICS Prioritization Process. After validation, CyTRICS researchers will then develop a scoring methodology to generate a quantitative score to assess the degree to which a digital component is characterized as an ICS Beachhead System. Finally, the National Laboratories will append this scoring to the existing CyTRICS Prioritization Process algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Deployment Readiness Framework Subtask 1.1 (Literature Review)

Island and remote coastal communities face some of the most challenging environments for building, operating, and maintaining energy infrastructure, as well as the highest costs for electricity, fuels, and other essential energy sources. As sea-levels rise and storms become more intense and frequent, these communities and the energy infrastructure that supports coastal lives and livelihoods are also at increasing risk from natural hazards. To address these challenges, many coastal communities are envisioning energy solutions that will support the triple bottom line goals of the blue economy: economic growth, environmental sustainability, and social equity. Yet, island and remote coastal communities often face limited resources and capacity to tackle complex energy and coastal resilience issues. To support community-driven energy transitions in island and remote communities, and to better understand relationships between energy, community, and ecosystem resilience, the Department of Energy’s Water Power Technologies Office (WPTO) has initiated the development of a Deployment Readiness Framework (DRF). The objective of the work is to co-produce and test practical tools and approaches that assess the readiness of coastal communities for marine energy demonstration, deployment, and operation. The DRF aims to build on and support the Energy Transitions Initiative Partnership Program (ETIPP) and other community-oriented energy transition programs. This project is jointly led by Pacific Northwest National Laboratory (PNNL) and the National Renewable Energy Laboratory (NREL). The development of the DRF includes three main phases: 1) a learning phase involving stakeholder engagement and literature review to synthesize metrics of community readiness to advance through an energy transition and to understand the state of the research and practice of participatory science-policy processes in various sectors, 2) a design phase to define readiness approaches and tools that will be developed as part of the DRF, and 3) an implementation phase to create the applications and interfaces for WPTO and the national laboratories to interact with the DRF. All three phases include close collaboration with communities and end-users of the framework, first to identify gaps in the science and tools needed to achieve community-driven energy transition goals and second, to test and improve the framework iteratively. Through technical assistance programs like ETIPP and utilizing the completed DRF to understand the influencing factors which motivate or deter energy transitions, WPTO hopes to engage a number of near-term marine energy demonstration opportunities. Here we report on the results from the literature review (Subtask 1.1) to inform the stakeholder engagement (Subtask 1.2) and design phase (Task 2) of the project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

2022 GETEM Geothermal Drilling Cost Curve Update

The Geothermal Electricity Technology Evaluation Model (GETEM) is an essential tool for the U.S. Department of Energy's (DOE) Geothermal Technologies Office (GTO) to understand the performance and cost of technologies it is seeking to improve. This detailed model is used for supply curve analyses, assessing the current economic feasibility and levelized cost of energy (LCOE) of hydrothermal geothermal systems and enhanced geothermal systems (EGS), and evaluating the potential impact of advanced geothermal technologies. GETEM can be used to estimate the performance and costs of currently available U.S. geothermal power systems. It is also used to estimate the costs of technologies 5 to 20 years in the future, given the direction of potential research, development, and demonstration (RD&D) projects. The model is intended to help GTO determine which proposed RD&D programs and projects might offer the most efficient improvement when using taxpayer funding. The model requires annual updates as well as revisions to reflect the current state of the art. Drilling costs are a significant portion of total geothermal development costs. The current GETEM drilling cost inputs rely on drilling data from 2009 and require an updated analysis of more recent data to ensure they remain representative of current technologies. An updated, more accurate understanding of costs could help the geothermal industry secure project development financing and investment funding and better allow the oil and gas (O&G) industry (both operators and service companies) to weigh potential geothermal market participation and customization. This report details recent drilling improvements from the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) and the O&G sector, comparing drilling performance and costs with values in GETEM, particularly the baseline drilling cost curves. Although drilling performance at FORGE has improved significantly, we did not find associated cost decreases that would justify lowering the GETEM baseline cost curves at this time.

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