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U.S. Department of Energy: National Virtual Biotechnology Laboratory (Technical Report)

With funding from the CARES Act, the U.S Department of Energy (DOE) established the National Virtual Biotechnology Laboratory (NVBL) in March 2020 to address key challenges associated with the COVID-19 crisis. The NVBL brought together the broad scientific and technical expertise and resources of DOE’s 17 national laboratories to help tackle medical supply shortages, discover potential drugs to fight the virus, develop and validate COVID-19 testing methods, model disease spread and impact across the nation, and understand virus transport in buildings and the environment. National laboratory resources leveraged for this effort include a suite of world-leading user facilities broadly available to the research community, such as light and neutron sources, nanoscale science research centers, sequencing and biocharacterization facilities, and high-performance computing facilities. As part of the NVBL framework, DOE rapidly assembled five project teams to (1) identify new targets for medical therapeutics; (2) develop innovations in testing capabilities; (3) provide epidemiological and logistical support; (4) understand viral fate and transport in the environment; and (5) address supply chain bottlenecks by harnessing extensive additive manufacturing capabilities. Each research team was charged with defining high-impact projects that could be completed in a 6-month sprint while coordinating their developments with academia, other government agencies, and the private sector. Within months, NVBL teams used DOE’s high-performance computers and light and neutron sources to identify promising candidates for antibodies and antivirals that universities and drug companies are now evaluating. NVBL researchers also developed new diagnostic targets and sample collection approaches, and supported efforts by the U.S. Food and Drug Administration, Centers for Disease Control and Prevention, and U.S. Department of Defense to establish national guidelines used in administering millions of tests. Researchers used artificial intelligence and high-performance computing to produce near-real-time data analysis to forecast disease transmission, stress on public health infrastructure, and economic impact, which supported decision-makers at the local, state, and national levels. To minimize virus uptake and protect human health, NVBL teams studied how to control indoor virus movement. Researchers also produced innovations in materials and advanced manufacturing that mitigated shortages in test kits and personal protective equipment, creating nearly 1,000 new jobs. Through its NVBL framework, DOE has contributed significantly to the nation’s COVID response, demonstrating in only a few months the critical impact of its national laboratories. NVBL’s accomplishments demonstrate not only the powerful resource represented by DOE’s national laboratories working together to meet national needs, but also the effectiveness of the integrated NVBL framework for rapidly responding to emergencies with research and development solutions. Going forward, the NVBL is poised to apply the unique capabilities and expertise of the national laboratory complex to future national and international emergencies, both natural and engineered. Through this framework, DOE will continue to be an integral component of agency-wide efforts to prepare for and respond to biorisks and other crises. This technical report describes the goals, progress, and results of NVBL’s five project teams—Molecular Design for COVID-19 Therapeutics, COVID-19 Testing, Epidemiological Modeling, Viral Fate and Transport, and Materials and Manufacturing of Critical Supplies—and lists each team’s publications and research output.

42 ENGINEERING↗

Examining United States Nuclear Weapon Educational Initiatives_A Quantitative Research Study on the Satisfaction of Participants Within the Nuclear Weapons Community

This study focused on a few United States nuclear weapons educational initiatives exploring six classroom environment factors that may or may not influence Satisfaction in a virtual or live classroom environment within the nuclear weapons community. The research explored Personalization, Involvement, Student Cohesiveness, Task Orientation, Innovation, and Individualization. The United States nuclear weapons community needed to attract new and talented individuals to the nuclear weapons profession. This study added to the nuclear weapons community by researching factors that may aid academic instructors, and curriculum developers create new and inventive ways of incorporating these factors into existing or new nuclear weapons educational courses. Convenience sampling was the data collection method used to gather quantitative research data. One hundred and seven voluntary participants utilized the College and University Classroom Environment Inventory with the Los Alamos National Laboratory's consent. There is not much concurrent research on Satisfaction within the live and virtual classroom environment. This research was vital for future research into how to increase participant satisfaction. The study provided the nuclear weapons community with grounded analysis to help create and guide new classes and course creation, possibly increasing Satisfaction in a live and virtual classroom environment. According to binary logistic regression, there was a statistically significant relationship among the dependent variable, Satisfaction, and two independent variables, Involvement, and Task Orientation in the classroom environment within the nuclear weapons community. Future nuclear educational programs may increase Satisfaction in the classroom environment by increasing participant Involvement and Task Orientation within a class using the CUCEI as a reference.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Improving Solar and Solar+Storage Screening Techniques to Reduce Utility Interconnection Time and Costs (Final Technical Report)

Residential PV installations have increased rapidly over the last decade, and the increased application volume has caused permitting delays and lower overall adoption rates. In this project, we developed and evaluated whether data-driven secondary modeling and screening techniques can help utilities assess customer applications more accurately than traditional screening shortcuts. Secondary topologies are predicted using decision trees and commonly available information, such as service transformer, customer, and street locations. Conductors were predicted using a logistic regression method based on real world object (RWO) types, service transformer ratings, conductor length, and distance to transformer. After developing the combined primary and secondary distribution network model, hosting capacity results were used to train a random forest model to predict the pass/fail likelihood of a customer application. Powerflow based models with predicted secondaries and data-driven methods both increased the screening success rate, relative to common utility heuristics, by as much as 55 percentage points. Data-driven screening techniques were described by one utility as a "right-sized" approach for residential customers given the low-risk of small errors and the high-cost of accurate modeling.

14 SOLAR ENERGY↗

Automated System-wide Event Detection and Classification Using Machine Learning on Synchrophasor Data

As the number of phasor measurement units (PMUs) deployed in a power system increases, and their data volume streamed to the control canter intensifies, operators are facing challenges related to the analysis of such data, which need to be observed and responded to as the measurements are displayed in the Control Room. Humans are generally unable to process such large amount of data efficiently and rapidly. There is an apparent need for automated ways to analyze the data, extract actionable information about occurrence of specific events, and characterize the events quickly and cost effectively. This paper discusses the use of machine learning (ML) to facilitate such tasks by providing automated, highly computationally efficient, and cost-effective ways of extracting actionable information from synchrophasor big data in real-time. We developed Big Data Smart (BDSmart) ML-based prototype tool for the Control Room use that automatically analyses data properties from synchrophasor system measurements taken across the three grid Interconnections in the USA (Western, Eastern and ERCOT). The data collected from several hundreds of PMUs located across the Interconnections over a period of two years have been made available for our extensive study. As a result, we were able to identify a number of big data properties that influence how ML methodology is applied to select, develop, train and test the data models that can eventually be used for the tool implementation. The resulting set of candidate algorithms spans unsupervised, supervised, semi-supervised and transfer-learning approaches. Many ML techniques, such as decision trees, multinomial logistic regression, feed-forward neural networks, K-nearest neighbor, multiclass support vector machine, and single and multi-channel convolutional neural networks, are implemented, and their performance is examined. We offer the results from testing the data models. The novelty of our study is in the approaches for bad data detection and mitigation, selection of a simplified feature for event detection, and data label improvements. As a result, we came up with a list of recommendations for the utilities on how to improve the PMU recording practices to cater to the future ML applications aimed at automating the analysis of synchrophasor data.

Synchrophasors, Machine Learning, System-wide Even↗

Pilot Study for Multifamily Building Ventilation and Indoor Air Quality

Weatherization Program Notice (WPN) 17-7 issued by the US Department of Energy (DOE) Weatherization Assistance Program (WAP) requires that buildings have ventilation in accordance with ASHRAE Standard 62.2-2016 (entitled Ventilation and Indoor Air Quality in Residential Buildings) in dwelling units weatherized under the program. The 2016 version of the standard expanded its scope of application to include all multifamily dwelling units. This has resulted in concerns for buildings where installing ventilation in individual units is costly or otherwise logistically difficult. Also, excessive ventilation rates could significantly increase energy costs, and may cause indoor air quality issues within the buildings. One deficiency that is noted is that the standard does not provide a credit for existing infiltration in multifamily buildings that reduces the required mechanical ventilation levels. This report details findings from a field study investigating envelope air-tightness, inter-unit connectivity, and indoor air quality in centrally ventilated high-rise multifamily buildings with central ventilation systems serving individual units in the state of New York. As allowed under WPN 17-7, the State of New York has a variance in the application of ASHRAE Standard 62.2-2016 in select types of multifamily buildings to provide time to determine how best to implement the standard. The purpose of this pilot study is to characterize the impact that weatherization and feasible ventilation improvements have on the indoor air quality of large, multifamily buildings with centrally ventilated apartments, as currently performed under WAP in the State of New York under their variance request (i.e., to implement ASHRAE Standard 62.2-2016 “to the greatest extent possible” in this type of multifamily building). A major goal is to determine if these practices improve or at least “do no harm” to the indoor air quality of the weatherized multifamily buildings and to the occupants themselves.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Continuous fiber malleable thermoset composites with sub-1-minute dwell times; validation of impact performance and evaluation of the efficacy of the compression forming process. CRADA Final Report

Mallinda is developing polyimine malleable thermoset prepreg composite materials which have excellent mechanical properties (100 GPa tensile modulus, 2 GPA tensile strength, 2.4% elongation at break) and high operating temperatures (Tg>200°C). At scale, polyimine resins are commensurate in price with commodity epoxy resins. What distinguishes malleable thermoset prepreg from traditional thermoset prepreg materials, is that they are fully cured during Mallinda’s roll-to-roll production of prepreg laminate. This results in 5 key value-differentiating benefits. First, it simplifies manufacturing logistics by enabling ambient transportation and storage, and by significantly extending out-life and shelf-life almost indefinitely. Second, elimination of autoclave curing reduces the economic and energy costs to the customer. Third, scrap rates can be reduced as malleable thermoset prepreg materials are directly reusable. Fourth, the manufacturing consolidation step can be roughly 10x faster than traditional thermosets, because the resin is already cured. Parts can be made via compression forming by the application of heat and pressure to quickly vitrify and consolidate a multilayer part – easily leading to sub 3-minute cycle times (at lab scale we have demonstrated a 20 second dwell time, with room for further optimization). Finally, the closed-loop cradle-to-cradle solution-based recyclability of malleable thermoset composites can also contribute significantly to the future of sustainable lightweight materials. The focus of this project was the development, optimization and validation of malleable thermoset composite materials which exhibit manufacturing cycle times of 3-minute or less, high speed impact performance on par with incumbent technologies, and defect-free consolidation of 3 dimensional parts.

36 MATERIALS SCIENCE↗

Woody Feedstocks 2021 State of Technology Report

The U.S. Department of Energy promotes production of advanced liquid transportation fuels from lignocellulosic biomass by funding fundamental and applied research that advances the state of technology (SOT). As part of its involvement with this overall mission, Idaho National Laboratory completes annual SOT reports for n th -plant biomass feedstock logistics. The purpose of the SOTs is to provide the status of feedstock supply system technology development for biomass to biofuels, based on actual data and experimental results relative to technical targets and cost goals from specific design cases.

09 BIOMASS FUELS↗

First Ever Field Pilot on Alaska's North Slope to Validate the Use of Polymer Floods for Heavy Oil EOR a.k.a Alaska North Slope Field Laboratory (ANSFL)

Alaska’s high viscosity oil resources that range between 20–30+ billion barrels represent about a third of known North Slope original oil in place (OOIP). These resources are primarily concentrated in the Schrader Bluff formation (also called West Sak on the Western North Slope) and Ugnu reservoirs and are categorized as “viscous oils” and “heavy oils” owing to their in-situ viscosities between 5–10,000 cP and up to a million+ cP respectively. The viscous oil deposits are relatively deeper (2,000 – 5,000 ft), whereas the heavy oils are somewhat shallower (2,000 – 4,000 ft). The typically shallow depths and the proximity to the continuous permafrost results in relatively lower formation temperatures and pressures, and consequently higher viscosities. The vertical depth vs. viscosity delineated in Paskvan et al. (2016) differentiates the viscous and heavy oils. As depicted in Paskvan et al. (2016), currently the main focus (referred to as “developing”) is on the viscous oils in the Schrader Bluff formation in the Milne Point Unit (MPU). Notwithstanding this Alaska North Slope (ANS) specific categorization, we use the industry adopted, all-inclusive term “heavy oil” for all high viscosity oils. Resource characterization and additional details can be found in topical publications of Paskvan et al. (2016) and Targac et al. (2005). Despite the vast resource base, the development pace, vis-à-vis the production of heavy oils has been very slow and limited due to multiple factors such as cost, logistics, challenging arctic environment, poor waterflood sweep efficiency due to mobility contrasts, and significantly high minimum miscibility pressures (MMP). Most importantly, typical or standard thermal methods that are commonplace elsewhere (Canada, California) are inapplicable due to the continuous permafrost. As a consequence, cumulative production of heavy and viscous oils is a little over 1% of OOIP slope wide and currently, there is hardly any production from Ugnu. However, on a broader level, these unfavorable factors are outweighed by the fact that (1) these resources, within the established infrastructure, are too large to ignore because of their strategic importance to the Nation and the State of Alaska and (2) Prudhoe Bay type diluent crude oil is still available for heavy oil transport through the Trans Alaska Pipeline System (TAPS). Similarly, from a reservoir standpoint, the following factors also are important offsets: (1) favorable rock characteristics of Schrader Bluff; (2) the promise demonstrated by the initial scoping studies (Seright 2010, 2011) suggesting significant increase of heavy oil recovery using polymer flooding; (3) successful field implementation in Canada, China and elsewhere in the world, and (4) availability of the existing pairs of horizontal injector-producer in Schrader Bluff The foregoing was recognized as the best readily available opportunity for significant investment by the US Department of Energy and the field operator Hilcorp Alaska LLC to conduct the first ever field scale experiment to test the polymer flooding technology to unlock the vast heavy oil resources on ANS. With this primary goal in mind, the research team embarked on a ~4.5 years long project that focused on the field polymer pilot complemented by supporting laboratory and simulation studies. As documented in this final report, over the course of the project, many lessons have been learned and valuable field and supporting laboratory data has been collected, which also is complemented by numerical reservoir simulations. We have been able to establish the injectivity of polymer solution, evidence of significant reduction in the water cut of previously waterflooded pattern, effective propagation of a hydrolyzed polyacrylamide (HPAM), benefits of low salinity water, provide practical guidance on handling of produced fluids containing breakthrough polymer, fit-for-purpose forecast-worthy history matched simulation model, polymer EOR benefit of 700-1000 bopd over waterflood, and most importantly a low polymer utilization factor of ~1.7 lb/stb. In summary this project is deemed as a scientific, technical and economic success, having met all objectives, fulfilled deliverables and within budget, providing impetus to apply polymer EOR throughout the Milne Point Field paving the way for even heavier viscosity oils in the Ugnu area, eventually extending the economic life of TAPS.

02 PETROLEUM↗

Office of Nuclear Verification FY 2023 Quarterly Report TSVT Q1

This project encompasses the continued development and training of a U.S. operational team, the Test Site Verification Team (TSVT), supporting verification of nuclear testing activities. TSVT builds on decades of U.S. nuclear testing history and nuclear explosion monitoring experience. The Team maintains readiness to deploy internationally on short notice to provide field-based support of verification of declared or undeclared nuclear testing and associated activities, as well as follow-on activities including monitoring and capability disablement and dismantlement, as established by negotiated agreement or treaty. The roles and structure of the TSVT are integrated with other NA-243 deployable verification teams and the interagency. FY23 TSVT activities focus on continued capability buildup within the team, including Team trainings and exercises with a focus on missions in confined spaces (e.g., tunnels, mines, other underground facilities), increased familiarity with foreign nuclear weapons testing programs, demonstration of Team capacity to deploy, train, and practice sustained OPSEC in non-western locations, establishment of sustainable storage and maintenance of equipment, specification and procurement of additional equipment to support field observations, further evolution of concepts of operation documents (CONOPs), and mission coordination with Headquarters and associated Stakeholders. Activities will culminate with a full-scale domestic team exercise at the end of FY23 focusing on underground activities signatures/observations and safety including advanced outdoor safety and familiarity in working around explosive test environments. In addition, we will be further articulating approaches and capacity relevant to the identification of nuclear tests, as well as monitoring of nuclear testing activities and/or dismantlement of nuclear test sites and anticipate developing additional equipment requests in support of this evolution. The TSVT Team Leads will also coordinate with its Senior Advisor, the TSVT Logistics and Readiness (L&R) Training Lead, and NNSA Headquarters to draft a five-year TSVT training and exercise plan, that strategically and incrementally builds capacity and expertise in key areas of significance for the continuum of nuclear and nuclear-related testing activities that fall within the team’s mission space.

42 ENGINEERING↗

Applying novel analytical tools for analyzing multidimensional secondary organic aerosol measurements

In the atmosphere, secondary organic aerosols (SOA) are often the major components of fine particulate matter and interact with clouds and radiation. SOA comprises a mixture of thousands of organic compounds. There is tremendous complexity and uncertainty in understanding SOA formation, since it is formed by oxidation and gas to particle conversion of a variety of sources: natural biogenic, anthropogenic (vehicles, cooking coal combustion) and biomass burning. The Aerosol Mass Spectrometer (AMS) produces multidimensional chemical information about SOA but analyzing this data to understand SOA sources relies on time consuming analyses (~months to years) such as the positive matrix factorization (PMF). PMF also becomes difficult for aircraft data where signal to noise ratio is weaker. There is a critical need to develop fast machine learning techniques that can analytically provide information about SOA sources using AMS data on the same timescales as the data is being collected (~minutes). We apply a machine learning supervised classification approach: the multinomial logistic regression to rapidly classify AMS data obtained from aircraft measurements.

47 OTHER INSTRUMENTATION↗

Glass Property-Composition Models for Support of Hanford WTP LAW Facility Operation

Current plans for the River Protection Project envision starting to vitrifying low-activity waste (LAW) by 2023 using a Direct Feed Low-Activity Waste (DFLAW) approach and subsequently using a full-pretreatment approach. The Hanford Tank Waste Treatment and Immobilization Plant (WTP) LAW Facility will be operated and controlled using a LAW glass formulation algorithm (GFA), which requires several inputs based on research and development results. LAW glass property-composition models for several product quality and processing properties are key inputs for the LAW GFA. It is envisioned that the preliminary LAW GFA discussed by Kim and Vienna (2012) will be used for commissioning and initial radioactive operations of the WTP LAW Facility under Bechtel National, Inc. using the DFLAW approach. Then, an updated LAW GFA will be developed for implementation by the WTP operating contractor that takes over after WTP LAW Facility commissioning. This report documents the enhanced LAW glass property-composition models developed for use in the updated LAW GFA. The properties for which models were developed include Product Consistency Test (PCT) response, Vapor Hydration Test (VHT) response, viscosity at 1150 °C, electrical conductivity at 1150 °C, melter SO3 tolerance at 1150 °C, and K-3 refractory corrosion at 1208 °C. Table S.1 lists the tables in this report that contain the recommended models for each of these properties. The model types recommended include partial quadratic mixture (PQM) models for viscosity, electrical conductivity, melter SO 3 tolerance and K-3 corrosion, bias corrected PQM model (bcPQM) for PCT, and logistic PQM model for VHT. The fits of model and validation subsets were found to be well predicted by the recommended models.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Operational Uncrewed Aircraft Systems Development for Meteorology and Atmospheric Physics Field Campaign Report

The overarching goal of the project is to develop integrated small, unmanned aircraft systems (SUAS) capabilities for enhanced atmospheric physics measurements. This team included atmospheric scientists, meteorologists, engineers, computer scientists, geographers, and chemists necessary to evaluate the needs and develop the advanced sensing and imaging, robust autonomous navigation, enhanced data communication, and data management capabilities required to use SUAS in atmospheric physics. The flight campaigns at the Southern Great Plains (SGP) U.S. Department of Energy Atmospheric Radiation Measurement (ARM) observatory were an integrated evaluation of the systems in coordinated field tests. This enabled sensor testing, and validation of SUAS technology and integration of unmanned aircraft into the airspace. The set of experiments enabled evaluation and progression of remote UAS deployment operations with observing atmospheric sensors. Each flight test endeavor was notable for the significant lessons learned during every deployment event. Team size and roles, equipment use, aircraft instruments, meteorological instruments, and deployment logistics, were all evaluated and improved at every flight-testing day. The details of these are further discussed in the Results section.

54 ENVIRONMENTAL SCIENCES↗

Electrochemical Acid Sequestration to Ease Ocean Acidification (EASE-OA) - CRADA 600 (Abstract)

The PNNL team will coordinate logistics involved with setting up the field trial on the PNNL Sequim campus in collaboration with Ebb Carbon. Facilities on the PNNL Sequim campus are capable of pumping raw or filtered seawater from Sequim Bay at a rate ~45,000 L hr -1 , which can accommodate the 4000 L hr -1 requirement of the 200 ton CO2 yr-1 Ebb Carbon marine carbon dioxide removal (mCDR) system. The primary tasks for the PNNL team are 1) laying out appropriate indoor and outdoor spaces for installing the Ebb Carbon’s mCDR system, 2) facilitating Ebb Carbon’s access to the PNNL’s seawater intake on the PNNL Sequim campus, 3) conducting mesocosm experiments within the PNNL Sequim campus laboratories to test how the brine and base discharged from the Ebb Carbon system affect marine life, and 4) facilitating Ebb Carbon access to the PNNL Sequim installation site and aiding in maintenance as needed. In addition to these tasks, the PNNL team will provide surface water quality data (e.g., salinity, temperature, pH, dissolved O2) from a monitoring station located on the pier to contextualize starting conditions of the seawater used in the mCDR process. Finally, the PNNL team will also consult with Ebb Carbon on strategies for improving overall system performance and next steps for further scaling and/or monitoring the effectiveness of the mCDR system.

54 ENVIRONMENTAL SCIENCES↗

ASME Code Qualification Plan for LPBF 316 SS

This report describes a plan to qualify laser powder bed fusion (LPBF) 316 stainless steel for use with the American Society of Mechanical Engineers (ASME) Boiler & Pressure Vessel Code Section III, Division 5 rules for metallic components in high temperature nuclear reactors. Accomplishing this goal would make the material and manufacturing process available to vendors for inclusion in the next generation of advanced, high temperature reactors. The general approach adopted here is to treat LPBF 316 as if it was a completely new material and to develop a plan to qualify the material according to the current ASME practices. One key goal of this work is to explore and develop accelerated qualification approaches that might reduce the time required to qualify new materials by reducing the need for long term testing. However, the qualification plan here does not employ any accelerated qualification approaches to provide a limiting, bounding description of the number, duration, and types of testing required to qualify LPBF 316 without such techniques and to describe a comprehensive dataset that could be used to explore and validate accelerated qualification approaches in the future. The report addresses the fundamental challenges to qualifying Advanced Manufacturing (AM) materials for high temperature applications and summarizes the ASME Section III qualification process as well as current efforts to qualify LBPF and DED 316 for low temperature applications. The report then discusses specific issues, both material and logistical, related to qualifying PBF 316 steel. The final chapters of the report describe a complete test plan designed to generate sufficient data to qualify the material as well as a data management plan for how to store and manage the data to eventually provide the test data packaged needed to qualify the material with ASME.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

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↗

Identification and Evaluation for Fueling of NRIC DOME Reactors Report

The National Reactor Innovation Center (NRIC) has designed a testbed for advanced microreactor experiments that enables and encourages technology developers to bring advanced designs closer to commercial availability. The test bed, Demonstration of Microreactor Experiments (DOME), will be used to facilitate much of the operation experimentation process of the each advanced microreactor including fueling and operational power experiments. This report identifies and evaluates the options for initial fueling the microreactors in DOME. This report also discusses the optional locations that were considered for the initial fueling of microreactor; namely the Transient Reactor Test (TREAT) reactor building, and an unspecified temporary location. But various logistical and construction issues essentially eliminated these other options from further consideration. A brief discussion in this report outlines potential equipment and protocol associated with fueling in DOME.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

2023 SAGE-Camp Report

The 7 th Summer Physics Camp for Young Women was successfully held in person in 2023 from June 5 th to 16 th at the New Mexico School for the Arts in Santa Fe, NM at Hilo Intermediate School in Hawaii. This year’s camp was dedicated to the topic of Energy Security and was made possible thanks to the strong collaboration of Los Alamos, Sandia and Hawaii teams and the logistical and financial support of Los Alamos and Sandia National Laboratories, New Mexico Consortium, SAGE- Moore Foundation, LANL Foundation, ACS, IEE, APS four corners, N3B, Hawaii Museum of Science and Technology, New Mexico School for the Arts (NMSA) and Tech Source. The camp mobilized more than 120 volunteers who made the camp a success. The camp is free of charge to the students and included free lunch and snacks for the busy brains to have plenty of energy, also included all materials needed for the hands-on activities (like drone building, crystal structure, solar panels, wind turbine fabrication, soldering, coding etc) and also a stipend for students who attended for the full two weeks and for two educators and two student mentors in NM. The camp offered 32 high school students from New Mexico and 8 from Hawaii a unique opportunity to explore science topics and meet a broad range of role model professionals across STEM fields including astrophysics, cybersecurity, Energy fields, space science, engineering, biophysics, environmental science, robotics, computer science, nuclear engineering, radiological science, physics and chemistry. With nearly 120 volunteers who came mainly from Los Alamos National Laboratory (66%) and Sandia national laboratories (18%), two funded educators from NM, Dr. Weldon Beauchamp and Dr. Ellee Cook, and two educators from Hilo, Dr. Pascale Creek Pinner and LeAnn Ragasa, the camp was educationally sound and extremely varied. The collaboration with school educators is critical for the goal of this camp to not only impact students' lives but also improve STEM education in NM and Hawaii. The ultimate goal of the camp is to increase higher education aspirations of students, empower them to consider careers in STEM and learn more about the opportunities available to them in our local colleges and DOE National Laboratories. In addition, the camp also hired 2 past students as student mentors, Megan Odom and Elisea Jackson, who currently attend NMSA and were students at the camp in 2022 when it was virtual. The in-person camp which aims at empowering under-represented minorities in STEM in our community received more than 52 applications this year from all over NM and 8 applications from Hawaii. Our selection criteria are based on diversity, equity and inclusion, and students for whom the camp can be a life-changing opportunity are given a chance to attend the camp. During COVID, the camp was held virtually and gave the opportunity to students from remote areas in NM and Hawaii to attend from their homes. This year, fantastic families supported students everyday even when home was in remote areas in NM like Lea county, Sandoval county, Bernalillo or Mora county. The organizers hope next year they can offer a residential option for students from remote areas.

99 GENERAL AND MISCELLANEOUS↗