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GradeIT (Road Grade Inference Tool)

The National Renewable Energy Laboratory (NREL) has developed the Road Grade Inference Tool, "GradeIT". This tool is a modular Python package the leverages the United States Geological Survey’s (USGS) 1/3 arc-second Digital Elevation Model (DEM), an open and free public dataset. Roadway gradient (slope) has a strong influence on vehicle energy consumption behavior and longitudinal dynamics. Therefore, any tools, models, or analyses that consider vehicle energy consumption or driving profiles is incomplete without accurate elevation and grade information. Despite the acute need for this data, it is rarely collected alongside GPS (latitude and longitude) data, and tools to post-process GPS data to append elevation and grade are difficult to come by. GradeIT satisfies this significant need in the research community. Utilization of the USGS DEM makes the underlying data available to any potential user and ensures continuous data anywhere in the continental United States. The USGS DEM is a great resource; however, in order to be useful for automotive and traffic engineering applications, significant interpolation and filtering is required to achieve an accurate representation of gradient on the roadway. GradeIT employs a two-dimensional interpolation to approximate elevation at a point on the road from the nearest nodes in the DEM. Then, GradeIT applies multiple filtering techniques to smooth the elevation profile to a realistic road topology. Finally, road grade is derived from the elevation profile and returned as the primary output.

Holden, Jacob↗

Integrated Proteomic and Glycoproteomic Characterization of Human High-Grade Serous Ovarian Carcinoma

Many gene products exhibit great structural heterogeneity because of an array of modifications. These modifications are not directly encoded in the genomic template but often affect the functionality of proteins. Protein glycosylation plays a vital role in proper protein functions. However, the analysis of glycoproteins has been challenging compared with other protein modifications, such as phosphorylation. Here, we perform an integrated proteomic and glycoproteomic analysis of 83 prospectively collected high-grade serous ovarian carcinoma (HGSC) and 23 non-tumor tissues. Integration of the expression data from global proteomics and glycoproteomics reveals tumor-specific glycosylation, uncovers different glycosylation associated with three tumor clusters, and identifies glycosylation enzymes that were correlated with the altered glycosylation. In addition to providing a valuable resource, these results provide insights into the potentialroles of glycosylation in the pathogenesis of HGSC, with the possibility of distinguishing pathological outcomes of ovarian tumors from non-tumors, as well as classifying tumor clusters.

Hu, Yingwei↗

Characterization of vacuum conductance in commercially available (sintered) and additively manufactured porous structures

This report documents the work performed in characterizing the vacuum conductance of porous structures made by conventional sintering (purchased as commercially available products from Mott Corporation ranging from 20 to 100 media grade) and additive manufacturing (powder bed fusion). The additively manufactured structures described in this report were originally intended to be the first iteration of several in an effort to produce desirable conductance characteristics. While resources were not available to link the experimental results to a modeling effort to better understand why certain characteristics were observed, the author hopes that this report may provide a useful set of data for future use, especially as sintered porous structures are not uncommonly procured from Mott corporation for research and development purposes. For that reason, all of the raw data is tabulated in the Appendix: it is possible to reproduce all of the figures shown in this report independently. For a quick order-of magnitude scan of the conductances, refer to Figures 5, 6, 8 and 9.

36 MATERIALS SCIENCE↗

Austin Sustainable and Holistic Integration of Energy Storage and Solar PV [Austin SHINES]. Final Report, Version 2

The Austin SHINES project and solution is a software management platform, for an electric grid with a high penetration of dispersed photovoltaic (PV) solar generation sites, which maintains the traditional power quality and reliability associated with grid service. This project developed and deployed the platform as a Distributed Energy Resource Management System (DERMS), engaging multiple advanced controls, to evaluate operation and optimization of a fleet of diverse DER assets, installed at several locations among Austin Energy’s customers and distribution system. The project also produced a methodology to create a replicable DERMS template, adaptable to other regions and market structures. Last, Austin SHINES aimed to demonstrate the solution’s methodology would enable the DER grid ecosystem to serve load at a technical cost (System Levelized Cost of Electricity, or System LCOE) of less than the U.S. Department of Energy SHINES program metric of $0.14/kWh, in a defined boundary, while enabling a high penetration of distributed PV. Research was categorized in 6 reports (Final Deliverables = FD) listed below, with titles and descriptions indicating which area of understanding was investigated: FD-1: System Levelized Cost of Electricity (System LCOE) Methodology The creation and use of the System LCOE to Serve Load metric that encompasses the holistic, system-level costs and benefits of all resources, and enables them to be evaluated based on their ability to support an efficient and low-cost integrated grid ecosystem. FD-2: Software Platform Product Description The creation of new DER control methodologies deployable within a utility-grade software platform that enable DER's to maximize their benefit within a grid, that is capable of serving load enabling a high penetration of distributed PV generation. FD-3: Optimal Design Methodology Optimal design methodologies for individual DER installations that enable utilities to determine the optimal combinations and sizing for individual DER sites. FD-4: Austin SHINES Ownership and Operation Models for DER System Performance A comparison of multiple DER aggregation and ownership methodologies including direct utility control, third-party aggregator, and autonomous. FD-5: Economic Modeling & Optimization A comparison of multiple DER technology mixes and configurations within the distribution system, providing insight into an optimal blend of technologies that best enable the distribution system to serve load at the lowest cost at high penetrations of solar. FD-6: Fielded Assets Deployed DER assets within the Austin Energy SHINES circuits. Austin SHINES provided an opening for state-of-the-art technology products to be deployed, providing a rich opportunity for improving how each of the products perform as stand-alone products, and in concert with other complementary products. The Austin SHINES project comprised of two key metrics for System LCOE: SystemLCOE_SHINES<$0.14/kWh Modeled ΔSystemLCOE_SHINES/ΔSystemLCOE_Base≥20% at same solar penetration The System LCOE calculation uses the costs of the utility-owned infrastructure as it exists today, the cost of the DERs that exist in the system today, and the cost of the purchase of energy from ERCOT wholesale markets over the course of the calendar year. All costs are on an annualized basis. The capital and operating costs are derived from the rate case, which produces a yearly cost. The net cost of energy and services imported to the system is integrated over the test year, as is the load served and solar penetration. The first metric was easily achieved by every scenario considered. The goal was set when the Department of Energy’s SHINES Funding Opportunity Announcement was written in 2015 and was a more difficult target at the time. Due mostly to rapidly declining costs for DERs and the significant decrease in the Electric Reliability Council of Texas (ERCOT) energy market prices, which results in lower net cost of energy purchases, the System LCOE is well below this target for all scenarios considered. A fleet of DERs can assume different mixtures, each of which serves the load at a different LCOE. The optimal mixture of DERs serves load at the smallest System LCOE. The second metric (hereinafter %delta metric) asks that the holistic DERMS controls reduce the incremental cost above the baseline of going to a high solar penetration future by at least 20% as compared to the case of a DER deployment with no sophisticated controls (autonomous). Many comparison sets were created throughout this project. Physical technology was installed for informing utility engineering and testing several types of operational control schemes, through the DERMS. The types of operational control which were compared for valuation of the System LCOE Metric were: Holistic control = using the full suite of the DERMS platform to decide and optimize how/why the systems operate depending on weather, market, and reliability signal input. Autonomous control = a local mode at the asset site, wherein a schedule operates the asset, with visibility into performance only No control = the baseline for comparing value against the other two types of control The types of ownership control included: Direct Utility control = the utility dispatches a signal to each asset Third-Party Aggregator = a third party aggregates a fleet of assets and the utility dispatches one signal for all Autonomous = a local mode is set for operation at the asset site, wherein a schedule operates the asset, with visibility into performance only The types of control methodologies deployable within a utility-grade software platform included: Utility Peak Load Reduction = Lower transmission cost obligation Day-Ahead Energy Arbitrage = Realize economic value through price differential Real-Time Price Dispatch = Realize economic value from real-time price spikes Voltage support = Reduce losses and increase solar generation Distribution Congestion Management = Increase local grid reliability Demand Charge Reduction = Lower customer bills and realize system benefit The fielded assets deployed for the project were: Utility Scale Kingsbery Energy Storage System: 1.5 MW / 3 MWh Li-Ion battery storage Mueller Energy Storage System: 1.75 MW / 3.2 MWh Li-Ion battery storage, 7 Energy Storage Units (250 kW each) La Loma Community Solar: 2.6 MW Commercial Scale Aggregated storage installations at 3 sites, with existing solar (300+ kW): One 18 kW / 36 kWh Li-Ion battery storage Two 72 kW / 144 kWh Li-Ion battery storage Residential Scale Aggregated storage installations: -Six stationary battery storage systems (10 kWh each) at homes with existing solar -One Electric Vehicle installed as Vehicle-to-Grid (V2G) Utility-Controlled Solar via Smart Inverters at 12 homes Autonomously-Controlled Smart Inverters at 6 homes Over the course of the project, Austin SHINES undertook installing more than 3 MW of distributed battery energy storage, smart PV inverters, a DER control platform, and other enabling technologies utilizing customer and utility locations and aggregation models. All of these resources were to be integrated and optimized at the utility level. DER assets and control methodologies were designed to achieve a credible pathway to a System LCOE for energy delivered to load of $0.14//kWh or less by 2020, while maximizing distributed solar generation and maintaining acceptable standards of power quality. The project also established a template for other regions to follow, to maximize the adoption of distributed solar PV in support of an economic and efficient grid. In total, the Austin SHINES project added value to the DER subject area in each layer of integration. From utility, to commercial to residential scales, the sheer hierarchy of communication and coordination was a significant accomplishment in addition to learnings from what these communications revealed was unique to each. Economically, the most effective method demonstrated was the criticality of planning phases. Contingencies and multiple projection scenarios helped guide the project to deploy optimal design as close as feasible, in real world conditions. The project and reports will serve public benefit by outlining specific areas of DER strategy and installation where many stakeholders and needs can be addressed with improved efficiency. Overall, communities and utilities should use the results to guide the increasing options available for powering the grid with DER, renewables, and carbon considerate energy.

14 SOLAR ENERGY↗

Using the Shallow Strain Tensor to Characterize Deep Geologic Reservoirs

Abstract Storing and recovering water, carbon, and heat from geologic reservoirs is central to managing resources in a changing climate. We tested the hypothesis that the strain tensor caused by injecting or producing fluids can be measured at shallow depths and interpreted to advance understanding of underlying deep aquifers or reservoirs. Geodetic‐grade strainmeters were deployed at 30 m depth overlying the Bartlesville Formation, a 500‐m‐deep sandstone near Tulsa, OK. The strainmeters are 220 m east of injection well 9A completed in a permeable lens at the base of the Bartlesville Formation. Water was injected into well 9A at approximately 1.0 L/s during four tests that ranged in duration from a few hours to a few weeks. The horizontal strain increased (tension) and the circumferential strain was a few times larger than the radial strain. The vertical strain decreased (compression) during injection. Strain rates were approximately 100 nε/day during the first few hours, but the rates decreased and were approximately 10 nε/day during most of the tests. Four independent methods of poroelastic simulation and inversion predict reservoir properties and geometries that are similar to each other and consistent with independent information about the reservoir. All strain interpretations predict that a boundary to the permeable lens occurs beneath the vicinity of the strainmeters, which is consistent with core data from the site. The boundary of the permeable lens is located by matching the vertical, radial and circumferential strains, which demonstrates the value of measuring the strain tensor.

Murdoch, Lawrence C.↗

Determining the Appropriate Emergency Planning Attributes for Microreactors

Micro-reactor designs incorporate design features that provide very low reactor decay heat power at 24 hours after shutdown that is manageable in comparison with larger reactors. This attribute translates into a low probability of core damage negligible offsite dose. This paper provides the conceptual framework for appropriately structuring emergency planning requirements for micro-reactors while ensuring the U.S. Nuclear Regulatory Commission’s (NRC) commitment to safety is met. Due to the diversity in reactor designs comprising the micro-reactor community, this paper identifies the necessary concepts that should be considered to ensure emergency plans for micro-reactors are appropriate for the risk. This paper does not mandate specific design features for micro-reactors but provides reactor designers a conceptual framework for a scalable, graded approach to Emergency Planning Standards that should be considered in their individual designs in order to support simplified emergency plans. Given that accident source terms associated with micro-reactors are essentially negligible when compared with those for large light water reactors, revisions to emergency planning standards are justified. A graded approach to implementing emergency planning guidance can be used to appropriately structure micro-reactor emergency plans and reduce the size of the emergency planning zone and plume exposure pathway. Appropriately structuring emergency planning requirements will better optimize licensee and offsite agencies emergency planning resources and reduce the resources associated with emergency planning.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Toward Sustainable Lithium Recovery: A Universal Hydrothermal Approach for Lithium Extraction

The rapid growth of lithium-ion battery (LIB) deployment presents critical challenges in sustainable end-of-life management and raw material recovery. Conventional pyrometallurgical and hydrometallurgical methods suffer from high energy demand, lithium loss, and complex wastewater treatment. This study established a universal, highly efficient, and sustainable hydrothermal route for lithium extraction and material recovery from various spent lithium-ion battery cathodes using 1,2,4,5-benzenetetracarboxylic acid (BTCA). The optimized process achieved over 99% lithium leaching efficiency for lithium iron phosphate (LFP) and LiNi x Mn y Co 1–x–y O 2 (NMC), with transition metal coleaching below 1%. It was also broadly applicable to lithium manganese oxide, lithium cobalt oxide, and black mass, achieving 98.5%, 98.95%, and 94.06% leaching efficiencies, respectively. The extracted lithium was directly converted into battery-grade lithium sources, while transition metals were recovered as oxides. Unreacted BTCA was efficiently regenerated and reused without degradation. Electrochemical evaluation confirmed that cathode materials synthesized with recovered lithium exhibit comparable performance to commercial products. Compared to conventional hydrometallurgy, the BTCA-based process increased revenue by over 40% and reduced greenhouse gas emissions by up to 39%. This closed-loop, chemistry-agnostic strategy offered a scalable and economically viable solution for industrial LIB recycling, enabling resource circularity and reducing dependency on primary critical materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SPECs Early-Stage Decision Model: User Manual

The SPECs Early-Stage Decision (ESD) model is central to the SPECs procurement solutions toolkit. The ESD model is an Excel-based spreadsheet model, which provides information about the economic and strategic value of a proposed battery-storage project or solar-plus-storage (solar-plus) project. The model can be used to explore combinations of storage-related project value streams in order to define a potential project, while educating co-op decision-makers about project benefits and costs. A sensitivity analysis function speeds the development of "what-if" scenarios. A gap analysis function solves for top-priority metrics and supports the inclusion of hard-to-monetize strategic values, such as the value of storage to defer costly system upgrades in light of increasing distributed solar and other distributed energy resources (DERs). Model outputs include the utility data, assumptions, and use-case scenarios that are recommended content for the requests for proposals (RFPs). The model may also provide an initial "sanity check" for RFP responses, supporting further discussions among utility staff, vendors and stakeholders. The ESD is not a "finance-grade" modeling tool, and users are cautioned to be mindful of its limitations, but the model has been reviewed by users, who recommend it as a way to drive faster and better project design and planning, as well as to facilitate better communications with vendors, grid partners, and stakeholders.

14 SOLAR ENERGY↗

Cultivation and Use of Acidithiobacillus ferrooxidans in Tellurium Biorecovery

The use of Acidithiobacillus ferrooxidans, Thiobacillus thiooxidans, and other chemoautotrophic microbes in bioleaching have been implemented in a variety of processes.1 In industry, bioleaching has been studied for its potential to extract valuable metals from low grade ores that would otherwise be cost prohibitive to recover.2 Other applications of bioleaching include the ability of certain microbes to detoxify waste products and even heavy metal contaminated soils.3 Another potential application for such bio-oxidative microbial activity is the extraction of tellurium (Te) from mine tailings, a low-cost abundant resource. Tellurium is one of the least common elements on Earth; it is found in the planetary crust at about 1 µg/kg, a rarity most comparable to that of platinum.4 A major use of Te in the U.S. is in cadmium-telluride (CdTe) solar panels5. Te is primarily imported into the U.S. from Canada, and it is usually recovered as a byproduct of copper refining.6 Since CdTe photovoltaic (PV) cells are the most efficient, cost-effective, and environmentally friendly PV chemistry, the renewables market has seen an increased demand for CdTe PV cells causing some concerns about sustainability and the limited global availability of Te. Acidithiobacillus ferroxidans is a microorganism that can oxidize iron and sulfur to produce ferric iron and sulfuric acid, and it is possible that it could also solubilize Te from sulfidic mine tailings. In this project, different media for growth of A. ferroxidans were evaluated, and a plan for testing the ability of A. ferroxidans to leach Te from mine tailings was developed. Initial characterization of A. ferroxidans cultures grown in the presence of copper tailings suggests that conditions suitable for Te bioleaching can be established.

60 APPLIED LIFE SCIENCES↗

Finding of Adverse Effect and Mitigation Documentation for the Stormwater Drainage and Street Systems, Substation Foundations, and the Bus Parking Lot in Mercury, Area 23, Nevada National Security Site, Nye County, Nevada

The U.S. Department of Energy, National Nuclear Security Administration Nevada Field Office (NNSA/NFO) proposes to grade the block on the southeast corner of Mercury Highway and Ranger Avenue and demolish an adjacent street segment in the town of Mercury at the Nevada National Security Site (NNSS) in Nye County, Nevada. The purpose of this letter report is to submit documentation related to the finding of effect for the undertaking and mitigation of four resources on and adjacent to the block that will be affected by planned activities to modernize parking and infrastructure in central Mercury. Two of these resources are portions of the street system and the stormwater drainage system, which are elements of the town’s infrastructure. The foundations of an old electrical substation and the bus parking lot will also be replaced by new parking or landscaping. This submission is intended to comply with the stipulations in the Programmatic Agreement between the National Nuclear Security Administration Nevada Field Office and the Nevada State Historic Preservation Officer Regarding Modernization and Operational Maintenance of the Nevada National Security Site, at Mercury in Nye County, Nevada, hereafter referred to as the Mercury PA. The town of Mercury and the immediate surrounding area have been designated the Mercury Historic District (SHPO Resource #D230), which is a property eligible to the National Register of Historic Places under Criteria A and C for its importance in supporting nuclear testing and scientific research from 1951 through 1992. During the initial architectural survey (Reno et al. 2018), all four resources were identified as contributing to the eligibility of the district.

54 ENVIRONMENTAL SCIENCES↗

Smart connected worker edge platform for smart manufacturing: Part 1—Architecture and platform design

Abstract The challenge of sustainably producing goods and services for healthy living on a healthy planet requires simultaneous consideration of economic, societal, and environmental dimensions in manufacturing. Enabling technology for data driven manufacturing paradigms like Smart Manufacturing (a.k.a. Industry 4.0) serve as the technological backbone from which sustainable approaches to manufacturing can be implemented. Unfortunately, these technologies are typically associated with broader and deeper factory automation that is often too expensive and complex for the small and medium sized manufacturers (SMMs) that comprise the majority of manufacturing business in the USA and for whom their most valuable asset are the people whose jobs automation while replace. This paper describes an edge intelligent platform to integrate internet‐of‐things technologies with computing hardware, software, computational workflows for machine learning, and data ingestion, enabling SMMs to transition into smart manufacturing paradigms by leveraging the intelligence of their people. The platform leverages consumer grade electronics and sensors (affordable and portable), customized software with open source software packages (accessible), and existing communication network infrastructures (scalable). The software systems are implemented via Kubernetes orchestration of Docker containerization to ensure scalability and programmability. The platform is adaptive via computational workflow engines that produce information from data by processing with low‐cost edge computing devices while efficiently accessing resources of cloud servers as needed. The proposed edge platform connects workers to technological resources that provide computational intelligence (i.e., silicon‐based sensing and computation for data collection and contextualization) to enable decision making at the edge of advanced manufacturing.

Kim, Yoon G.↗

Primer to SWIFt 2.0 Technical Information Sheets

More than 16,000 publicly owned municipal wastewater treatment plants (WWTPs) in the U.S. treat a wide range of wastewater (WW) flows ranging from <0.5 to >200 MGD. Municipal WWTPs act as the last barrier before exposure to water-borne diseases and contaminants, thus serving as a critical infrastructure protecting human health and the environment. A recent survey by the American Society of Civil Engineers assigned the U.S.’s WW infrastructure a grade of D+ because of the number of improvements needed for end-of-life infrastructure with operating conditions being over or under design capacities. With increasing population growth and urbanization, the municipal WW sector needs to grow resiliently and sustainably to accommodate increasing sewer flows in the wake of new infrastructure needs and global priorities. In addition, this growth will be affected by rising concerns over constrained resources (e.g., electricity, energy, and water) and regulations. This necessitates molding the WW sector toward sustainability- and resiliency-related planning and innovations to address current and future needs while simultaneously producing profitable by-products.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Upgraded Coal and Coal Waste to Graphite for Lithium-Ion Battery Applications

Presentation to the Fortieth Annual International Pittsburgh Coal Conference, Istanbul, Turkiye, October 4–6, 2023. To assist in meeting the global graphite supply limitations, this study aims to investigate efficient ways to synthesize high-quality graphite from abundant coal and coal waste resources that exist in many areas around the world. A recently developed upgraded coal-to-products (UCP) process has shown great promise in the ability to reduce coal-borne impurities and produce a graphitizable product that yields good quality graphite for LIB applications. Preliminary results show that the quality of coal-derived graphite obtained by the UCP process is similar to that of commercial LIB-grade graphite. Available results are presented and discussed as well as maturation plans and flexibility of the UCP technology.

01 COAL, LIGNITE, AND PEAT↗

Upgraded Coal to High-Quality Graphite for Lithium-Ion Battery Applications

Presentation for the World Conference on Carbon 2023, Cancun, Mexico, July 16–21, 2023. To assist in meeting the global graphite supply limitations, this study aims to investigate efficient ways to synthesize high-quality graphite from abundant coal resources that exist in many areas around the world. A recently developed upgraded coal-to-products (UCP) process has shown great promise in the ability to reduce coal-borne impurities and produce a graphitizable product that yields good-quality graphite for LIB applications. Preliminary results show that the quality of coal-derived graphite obtained by the UCP process is close to that of commercial LIB-grade graphite. Results are presented and discussed as well as maturation plans and flexibility of the UCP technology.

01 COAL, LIGNITE, AND PEAT↗

Model America - data and models of every U.S. building

The 5-year goal of the 'Model America' concept was to generate a model of every building in the United States. This data repository delivers on that goal. Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM). There were 125,714,640 buildings detected in the United States and this dataset contains 122,930,327 (97.8%) buildings which resulted in a successful simulation. Future, annual updates have been proposed that may include additional buildings, data improvements, or other algorithmic enhancements. This dataset of 122.9 million buildings includes: Models (state_county.zip) - OpenStudio (v3.1.0) and EnergyPlus (v9.4) building energy models. Please note that the download requires the free Globus Connect Personal (https://www.globus.org/globus-connect-personal); Each model has approximately 3,000 building input descriptors that can be extracted. Please see the EnergyPlus(v9.4) 2,784-page Input/Output Reference Guide (https://energyplus.net/sites/all/modules/custom/nrel_custom/pdfs/pdfs_v9.4.0/InputOutputReference.pdf) for everything that can be retrieved or simulated from these models. These models were derived from the following metadata, which is not included in this dataset: 1. ID - unique building ID 2. County - county name 3. State - state name 4. CZ - ASHRAE Climate Zone designation 5. Clim_Zone - text label of climate zone 6. est_year - estimated year of construction 7. est_commercial - estimated building type (0=residential, 1=commercial) 8. Centroid - building center location in latitude/longitude (from Footprint2D) 9. Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) 10. Height - building height (meters) 11. Area2D - footprint area (ft2) 12. BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards 13. WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) 14. NumFloors - number of floors (above-grade) 15. Area - estimate of total conditioned floor area (ft2) 16. Standard - building vintage. These models are made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD), U.S. Dept. of Energy's (DOE) Building Technologies Office (BTO), Office of Electricity (OE), Biological and Environmental Research (BER), and National Nuclear Security Administration (NNSA). This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. Please cite as: New, Joshua R., Adams, Mark, Bass, Brett, Berres, Anne, and Clinton, Nicholas (2021). 'Model America - data and models of every U.S. building. [Data set].' Constellation, doi.ccs.ornl.gov/ui/doi/339, April 14, 2021

24 POWER TRANSMISSION AND DISTRIBUTION↗

Major element composition controls rare earth element solubility during leaching of coal fly ash and coal by-products

Coal combustion ash and pre-combustion coal refuse are currently under consideration as potential sources of rare earth elements. One of the early steps in recovering REEs from coal by-products is often acid leaching, which can result in low pH leachates with complex aqueous chemistry. The aim of this work was to understand the connection between REE solubility, pH, and major elemental components of leachates for coal by-products. To accomplish this, we investigated the effects of solids concentration (i.e., pulp density) and pH adjustment on REE solubility in acid leachates of coal fly ashes from the Powder River Basin (PRB) and Appalachian Basin in the United States, and a coal processing refuse from the Southwestern U.S. For PRB ashes, the concentrations of soluble REEs generally increased with increasing pulp density; however, at pulp density values above 80–100 g/L, the soluble REE concentrations in the leachates were markedly lower. Similarly, the soluble concentrations of other major solutes (Fe, Al, Si) that leached from PRB fly ashes were also non-linear with pulp density. These major elements tended to reach maximum concentration values at 60–70 g/L pulp density. In contrast, for the Appalachian fly ashes and the coal by-product, soluble concentrations of REE and major elements in leachates increased linearly with pulp density. Chemical equilibria calculations of mineral saturation indices indicated that trends in soluble REE concentrations could be explained by saturation conditions for Fe and Al-(hydr)oxides and possibly sulfate minerals, but not lanthanide hydroxides. Furthermore, pH adjustment of the acid leachates showed that REEs and many major solutes were removed from solution at pH values above 4.5, also consistent with Fe- and Al-(hydr)oxide precipitation. These results highlight the importance of understanding the chemical composition of leachates when designing REE recovery processes for low-grade geologic feedstocks and that precipitation of hydr(oxide) or sulfate minerals of major elements rather than discreet formation of REE mineral phases could be used for process optimization.

01 COAL, LIGNITE, AND PEAT↗

Fragility Functions Resource Report: Documented Sources for Electricity and Water Resilience Valuation

Fragility curves provide the vulnerability between hazard intensity and an asset. Federal installations may include many different electricity and water infrastructure types (or assets) such as generators, wind turbines, solar PV, switch yards, substations and power lines as well as water distribution systems that could be affected by different hazards. The vulnerability of each asset is a function of its age, type of materials and maintenance. In addition, the vulnerability changes with the hazards intensity and has a probability distribution function associated with it. The fragility functions are used in conjunction with hazard probability and consequence valuations to determine the values at risk for examination of investment grade analyses of alternative mitigation strategies. This document provides examples of fragility functions and links to their sources for different electricity and water infrastructure assets by hazard type.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Future material demand for automotive lithium-based batteries

The world is shifting to electric vehicles to mitigate climate change. Here, we quantify the future demand for key battery materials, considering potential electric vehicle fleet and battery chemistry developments as well as second-use and recycling of electric vehicle batteries. We find that in a lithium nickel cobalt manganese oxide dominated battery scenario, demand is estimated to increase by factors of 18–20 for lithium, 17–19 for cobalt, 28–31 for nickel, and 15–20 for most other materials from 2020 to 2050, requiring a drastic expansion of lithium, cobalt, and nickel supply chains and likely additional resource discovery. However, uncertainties are large. Key factors are the development of the electric vehicles fleet and battery capacity requirements per vehicle. If other battery chemistries were used at large scale, e.g. lithium iron phosphate or novel lithium-sulphur or lithium-air batteries, the demand for cobalt and nickel would be substantially smaller. Closed-loop recycling plays a minor, but increasingly important role for reducing primary material demand until 2050, however, advances in recycling are necessary to economically recover battery-grade materials from end-of-life batteries. Second-use of electric vehicles batteries further delays recycling potentials.

25 ENERGY STORAGE↗