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At least 19 records

Utility Finder (U-Finder) Tool

U-Finder allows users to search for and identify local utility partners and electric vehicle charger incentives by state or ZIP code. U-Finder pulls from the Homeland Infrastructure Foundation-Level Database of Electric Retail Service Territories to identify utility service territories. Utility incentive listings are provided by utility associations, and state government incentive listings are pulled from the Alternative Fuels Data Center Laws and Incentives website. ![U Finder landing page](ufinder-landing.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Southern Company Services: Project 2: Tall Tower Wind Technical Potential for the Southeast (Modifications 4, 5), Project 4: Offshore Wind Potential for Southern Company Services (Modifications 7, 8)

Project 2: The National Laboratory of the Rockies (NLR) and Southern Company Services (SCS) seek to establish an agreement to assess the technical potential for wind energy in the Southeastern U.S. SCS has requested that NLR conduct a detailed assessment of system performance, available capacity, transmission distance, and levelized cost of electricity (LCOE) at turbine hub heights of 100m to 160m within the SCS service territory. NLR will also provide an assessment of utility photovoltaic (PV) technical potential within the SCS service territory. NLR has unique modeling capabilities to assist SCS with high spatial and temporal resolution assessment of wind and PV technical potential, considering geospatial constraints. Project 4: NLR and SCS seek to develop a spatially explicit techno-economic assessment for offshore wind energy in the Southeastern U.S. The analysis aims to characterize the regional sensitivities of offshore wind plant costs and performance, underwater cabling, potential siting constraints, and landfall spur transmission costs.

17 WIND ENERGY↗

Advanced cogeneration research study: Executive summary

This study provides a broad based overview of selected areas relevant to the development of a comprehensive Southern California Edison (SCE) advanced cogeneration project. The areas studied are: (1) Cogeneration potential in the SCE service territory; (2) Advanced cogeneration technologies; and (3) Existing cogeneration computer models. An estimated 3700 MW sub E could potentially be generated from existing industries in the Southern California Edison service territory using cogeneration technology. Of this total, current technology could provide 2600 MW sub E and advanced technology could provide 1100 MW sub E. The manufacturing sector (SIC Codes 20-39) was found to have the highest average potential for current cogeneration technology. The mining sector (SIC Codes 10-14) was found to have the highest potential for advanced technology.

Bluhm, S. A.↗

State Technical Assistance - New Mexico Energy and Conservation Management Division Report [Slides]

The New Mexico Energy and Conservation Management Division (ECMD) sought technical assistance to enhance their ability to evaluate program impacts using the Low-Income Energy Affordability Data (LEAD) tool. NLR assisted ECMD in leveraging the LEAD tool to calculate and analyze energy burden across electric utility service areas, enabling them to assess program outcomes more effectively. To meet ECMD's goals, NLR developed a customized methodology to calculate utility-specific energy burden metrics using census tract data and available utility service area information from the Energy Information Administration (EIA). While acknowledging some limitations in the EIA dataset, NLR estimated the percentage of households within each service territory and incorporated relevant filters such as income, housing characteristics, and other demographics from the LEAD tool. The analysis provided ECMD with a new capability to evaluate program success based on energy savings, reductions in energy burden, and other performance indicators. The data and methodology also support discussions with utilities to improve the accuracy of service territory datasets. ECMD can use the outputs to track program effectiveness and plan future initiatives. NLR offered the possibility of follow-on work, including capacity-building for ECMD to repeat the analysis independently and the option to refine the analysis with updated service.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Climate Adaptation Approaches for Water and Electric Utilities: A compendium of existing strategies in a changing climate

Report analyzes plans developed by water and electric utilities to address the impacts of changes in the climate within their service territories. The analysis identifies the main types of changes that utilities address, such as sea level rise, extreme heat, and compound events such as freezing rain/show and extreme wind events. It then identifies adaptation approaches utilities have proposed or adopted to address the changes that are anticipated in their service territories. The report also identifies the mechanisms utilities (and in some cases the governments which the utilities are part of) use to ensure that energy or environmental equity is increased as a result of the resilience program. In summary, the report provides a compendium of adaptation strategies that can be used by others as they review their own need to increase climate resilience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Factorization Machine Learning for Disaggregation of Transmission Load Profiles with High Penetration of Behind-the-Meter Solar

The ever-growing high penetration of ubiquitously distributed energy resources, especially behind-the-meter solar (BTM) generations, has significant impacts on nodal load (i.e., net injection) profiles and consequently caused imperative operational challenges to system operators such as regional transmission organizations (RTOs). Illustrated by real-world nodal data and examples at PJM Interconnection, this paper first discusses the application and necessity of effectively extracting daily nodal load profiles in a non-intrusive manner. More importantly, a novel bi-level architecture, including Factorization Machines (FM) learning procedure has been proposed to effectively disaggregate not only one node but every node in an RTO service territory. Specifically, FM leaning is adopted to capture the interconnections between related features to better utilize the correlation between buses in the same region and between a single bus and the zonal load. The proposed bi-level technique is numerically validated using real-world, minute-level, normalized, and anonymized nodal data at PJM service territory.

behind the meter solar, load disaggregation, load ↗

Offshore Wind Project Study (Final Technical Report)

Within the Long Island electric service territory and throughout New York State there is increasing interest in and mandate for increasing clean energy technologies and renewable energy generation while reducing dependency on fossil fuels for electric production with goal of a carbon free system by 2040. This report discusses the implications of the reduction of forecasted load in the Long Island electric service territory and the impact of energy efficiency; increasing reliance of wind and other renewable resources on the transmission system; opportunities for interconnecting these resources; and reductions on the reliance of baseload fossil fueled power facilities over the coming years.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Scaled Implementation of Smart Charge Management for Electric Vehicles

Smart charge management (SCM) has become a critical strategy for mitigating potential grid impacts and reducing electricity costs for all customers. This study will evaluate the economics of implementing light-duty EV SCM at scale across the United States. This work will enhance distribution system analysis by estimating SCM implementation costs, exploring viable business cases, and developing a framework for national-level applications. The primary methodology involves leveraging detailed grid modeling from a specific service territory and using spatial extrapolation techniques to generalize findings to other regions. The analysis will develop key metrics to quantify the costs and benefits of SCM, including implementation costs relative to strategy and scale, the cost of distribution system upgrades with and without SCM, and the percentage of peak-load reduction. The objective is to produce a comprehensive report and a parameterized framework that enables utilities to self-assess the value of SCM in their own service territories. This will support the development of cost-effective charging strategies, accelerate the energization of new EV chargers, and facilitate the seamless integration of EVs into the nation's power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

ICE Calculator 2.0: Final Report for Phase 1 of the National Initiative to Update the Interruption Cost Estimate (ICE) Calculator

In 2021, Berkeley Lab and Resource Innovations, Inc. launched the “ICE 2.0 Initiative” – a national study to refresh the underlying data and enhance the functionality of the ICE Calculator. The Initiative involves Berkeley Lab contracting with sponsoring utilities to administer identical, updated and comprehensive interruption cost surveys to statistically representative samples of each utility’s customers. Berkeley Lab and Resource Innovations then pool the survey results across the utilities and use them to update the analytical engines that drive the ICE Calculator. The ICE 2.0 Initiative is being conducted in phases. Each phase involves the administration of interruption cost surveys to the customers of sponsoring utilities, followed by an update to the ICE Calculator based on analysis of the pooled survey results. This report describes the activities and findings from Phase 1 of the ICE 2.0 Initiative. Phase 1 was sponsored by eight utilities: American Electric Power, Commonwealth Edison, Dominion Energy, Duke Energy, DTE Electric, Exelon, National Grid, and Puget Sound Energy. Phase 1 involved 11 customer interruption cost survey activities representing a total of 24 electricity distribution service territories, 23 of them located in the Eastern and Midwestern regions of the U.S. and one located in the Pacific Northwest. ICE 2.0 vs. 1.0 Comparison This memorandum compares customer power interruption costs estimated using the recently updated Interruption Cost Estimate (ICE) Calculator (“ICE 2.0”) to the original ICE Calculator (“ICE 1.0”). ICE 1.0 was developed in 2009 based on 15 independent power interruption cost surveys conducted by 10 electric utilities between 1989 and 2012. ICE 2.0 was developed in 2025 through a national initiative based on a consistent set of power interruption cost surveys and 11 surveying efforts conducted across 24 electric utility service territories between 2022 and 2024.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Assessment of Low-Cost Minisplit Heat Pump Connection System

This project was funded by SCE's Emerging Technologies Program, and evaluates the feasibility of a connection system that can pave the path to accelerated, cost-effective adoption of high-efficiency Minisplit Heat Pump (MSHP) systems. This report details the characterization of this connection system and a heat pump enabled with this technology in a laboratory setting, and assesses the energy and cost impact applicable to residential buildings in SCE service territory. The energy and economic analysis leverages NREL's ResStock TM modeling approach based on the EnergyPlus ® hourly simulation platform. The connection system can be incorporated into existing MSHP architectures. This reduces installation time from 10 to 20 man hours to approximately one hour or less, dramatically lowering total installation costs without adversely impacting heat pump performance. This report characterizes the connection system's leakage performance while connected and disconnected, as well as leakage over several connection/disconnection cycles, commensurate with manufacturer specifications for the individual components. The connector was incorporated into an off-the-shelf MSHP. Performance was compared to an identical unmodified heat pump. The connector had no impact on performance. Large-scale hourly energy simulations were performed for 22,574 homes across 15 counties in SCE service territory. The analysis was performed using baseline assumptions about the penetrations of window air conditioners (~18%) and six upgrade scenarios for these air conditioners. All scenarios assumed 100% adoption of the Connector-Supported Heat Pump (CSHP) in place of window air conditioners: MSHPs at Seasonal Energy Efficiency Ratio (SEER) 17, 25, and 33, and CSHPs at SEER 17, 25, and 33. Results show the increased adoption of high-efficiency heat pumps can result in up to 29% air conditioning energy savings for homes with window air conditioners.

42 ENGINEERING↗

Region-Specific Merchant Hydrogen Market Assessment and Techno-Economic Assessment of Electrolytic Hydrogen Generation: Cooperative Research and Development Final Report, CRADA Number CRD-18-00751

Utilities need to recover value from baseload and some renewable assets even when the electricity is curtailed. The declining cost of renewables (particularly solar), the persistently low-cost of natural gas, and the declining electricity demand, have all worked to lower the price of electricity. Furthermore, the baseload assets have a high turndown cost, which is not reflected in the low market electricity prices. One option for utilizing the curtailed electricity is hydrogen generation. One important aspect of this project will be to provide a “go/no-go” recommendation on the economic feasibility of pursuing hydrogen generation vs. other markets that could offtake curtailed electricity or nuclear steam. This project will specifically assess the opportunities for hydrogen production and use in the service territories of Southern Company Services (SCS), Exelon SBC, and Xcel Energy. Each utility partner represents a different mix of generation fleets: Exelon has significant nuclear assets, Xcel is primarily renewables (wind) with some nuclear, and SCS represents both a renewables fleet and a heavily baseload fleet, which includes significant nuclear. The Contractors will conduct the study of hydrogen market opportunities by first considering the approximate electricity demand and price profiles for the year, and power generation capacity that can be used to produce hydrogen. Therefore, a profile for hydrogen generation will also be developed to better understand the quantity and timing of hydrogen production. Once the hydrogen production schedule is estimated, hydrogen storage requirements can be determined. This effort will provide sufficient information to make a go/no-go decision on moving ahead with a detailed regional case study for hydrogen production in any of the three utility areas.

08 HYDROGEN↗

Survey and Gap Prioritization of U.S. Electric Vehicle Charge Management Deployments

The goal of this study was to survey and characterize the scope of current technical and programmatic knowledge pertaining to EV charge management technologies and practices in the US and relevant international jurisdictions. This characterization of existing field demonstrations and knowledge derived were used to determine gaps in the SCM demonstration landscape. Addressing these gaps through research and demonstration could increase confidence in the U.S. that load management and EV charge control could achieve overarching societal benefits. A survey of charge management deployments and input from stakeholders was completed to determine the state-of-the-art of smart charge management (SCM) where SCM is defined as controlling the amount of power exchanged between chargers and EVs to meet customers' charging needs while also responding to external power demand or pricing signals to provide load management, resilience, or other benefits to the customer and electric grid. The survey was the basis of the gap analysis in this report and determines which areas are well understood, with high confidence, and which areas need further investigation. Existing examples of EV charge management are characterized here to determine aspects that are ready for widespread deployment and have been demonstrated in the field. These include demonstration studies, pilots, programs, and EV-specific tariffs. In all, 110 examples of charge management were characterized. The data sources were public literature and utility filings as well as targeted interviews. In addition, 43 interviews with stakeholders were conducted with a consistent set of questions used in each interview. This study prioritized gaps in demonstrated SCM capabilities based on 1) Urgency of the particular use-case to offset traditional grid assets, 2) Impact, extensibility, and scaling of results across the entire spectrum of 3000+ utility service territories including projected technical and market potential for a given grid service, and 3) Value of federal funding in addressing the gap, including potential to leverage and/or add scope to existing field demonstrations funded by other non-federal funding mechanisms.

33 ADVANCED PROPULSION SYSTEMS↗

Safely Exploring Solar: A Guide for Austin Energy Customers

It's easy to get overwhelmed as you start to explore your solar options. There is a wealth of information available out there, particularly online, and it can be hard to know who to trust. This informational guide has been adapted from Austin Energy's Solar Education Course and other national best practice resources, as of May 1, 2023. It will help you understand some of the key concepts and resources available to help you on your solar journey if you have a home in Austin Energy's service territory and are considering installing solar. This document includes: (1) Austin Energy Programs and Services Related to Solar; (2) Tips for Spotting a Solar Scam; (3) Things to Know When Designing Your System; (4) Key Considerations When Shopping for a Solar Contractor; and (5) Final Takeaways.

14 SOLAR ENERGY↗

Impact of Connected Communities

Buildings account for 35% of CO 2 emissions and almost 40% of the United States’ energy use. High-performance homes and neighborhoods play an important role in supporting efforts to decarbonize the US power system by 2035. Significant reductions in CO 2 emissions within the residential sector can be realized through electrification of loads paired with the flexibility created by leveraging smart Internet of Things (IoT) capabilities to shift energy use based on grid signals, thus improving generation/distribution efficiency and maximizing the use of renewable generation capacity. All of this can be achieved while allowing smart home appliances and equipment to meet homeowner needs – including reducing power bills - while optimizing operation in conjunction with the grid using novel control techniques. The Grid-Interactive Efficient Buildings Roadmap by the US Department of Energy’s (DOE’s) Building Technologies Office (BTO) notes that implementing grid-interactive efficient building (GEB) technology has the potential to reduce CO 2 emissions by 80 million tons/year—roughly equivalent to 17 million cars. To achieve this vision, the US Department of Energy’s Oak Ridge National Laboratory (ORNL)—in collaboration with Southern Company Research & Development, Alabama Power, Georgia Power, BTO and the US DOE’s Office of Electricity (OE) —is developing and demonstrating novel connected communities at two locations. Southern Company in turn engaged with industry partners, including design firms, residential developers, and residential HVAC and appliance manufacturers because their participation would be critical to the success of the initial research project, as well as the future scaling to the Southern Company service territory and beyond. Impacts of the Connected Communities projects in Alabama and Georgia are outlined including: energy, grid services and data management learnings; homeowner feedback; vendor engagement; adoption by utilities; technical, policy and business model challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Final Technical Report-WestSmart EV: Western Smart Plug-in Electric Vehicle Community Partnership

The WestSmartEV (WSEV) project has accelerated adoption of plug-in electric vehicles (PEV) throughout the PacifiCorp/Rocky Mountain Power’s (RMP) service territory in the intermountain west by developing a large-scale, sustainable PEV charging infrastructure network with coordinated PEV adoption programs. The project objectives have strategically deployed 79 DC fast charging to create two primary electric interstate highway corridors along I-15 and I-80; incentivized installation of Level 2 AC chargers at workplace locations; incentivized the purchase of PEVs; provided all electric solutions for first-mile and last-mile trips, including electrified mobility service; provided centralized data collection, analysis, modeling, and tool development to inform investment and policy decisions; and developed education outreach materials and conducted workshops across the WSEV region.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Residential Vehicle-to-Home Backup Power Capabilities: Key Findings from a ComEd Beneficial Electrification R&D Pilot

This report summarizes key findings from a collaborative technical study of residential, non-grid-tied vehicle-to-home (V2H) backup power systems in Commonwealth Edison’s (ComEd’s) service territory. The work integrates (1) a feeder-level technoeconomic analysis (TEA) using historical outage-event data and simulated electric-vehicle (EV) driving/charging profiles to estimate potential reliability and customer interruption-cost impacts under V2H and vehicle-to-grid (V2G) adoption scenarios; (2) controlled laboratory performance testing of a representative V2H backup ecosystem to characterize transfer-to-backup behavior, sustained power delivery, efficiency trends, and repeatable reliability limitations; and (3) a cybersecurity assessment aligned with NIST Cybersecurity Framework (CSF) 2.0 and ISO/SAE 21434 to evaluate interface-level risk drivers and identify program-relevant mitigations. Results indicate that V2H can provide measurable resilience value, but outcomes are strongly context dependent on outage patterns and the share of events that are “V2H-applicable.” Typical transfer-to-backup behavior clustered on the order of minutes, but rare long-delay edge cases were observed (including an event approaching 30 minutes) and should be treated as a reliability risk. High-power testing showed that peak-rated output is not necessarily continuously deliverable; stable operation may require operation below nameplate ratings and attention to thermal and installation constraints. The cybersecurity assessment highlights a broad attack surface spanning commissioning, home networks, embedded services, and cloud/OTA pathways, motivating minimum controls for secure onboarding, signed updates, patch cadence, and coordinated vulnerability response for any scaled deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Review of Value of Solar Studies In Theory and In Practice

This brief summarizes a collection of state- and utility-commissioned value-of-solar (VoS) studies and related literature, with a focus on who commissioned the study, which value and cost categories were discussed and/or quantified, and the methods used. Our objective is to compile information on prior VoS studies to inform state regulators and other stakeholders that may pursue related studies or integrate findings into rate design. The brief is organized into three parts: 1) an introduction to distributed solar photovoltaic (DPV) compensation; 2) a review of theoretical research on VoS; and 3) a review of VoS studies. The vast majority of VoS studies have served an informational role of quantifying the net benefits of PV. Three studies were commissioned in states or utility service territories that subsequently implemented VoS tariffs in California, New York, and Austin, Texas. When applied as a tariff, VoS aims to compensate PV output as efficiently as possible by doing so at rates that reflect the marginal benefits and costs of PV through value and cost categories that may vary temporally and/or geographically. This could lead to higher compensation in locations and times where more PV output is more valuable and consequently drive adoption in those locations to provide more societal benefits. Value and cost factors can be broadly grouped into five categories: generation, transmission, distribution, other utility, and other social categories. Those conducting VoS studies must weigh various tradeoffs when deciding which categories to include and quantify. Tradeoffs include prioritizing values based on their magnitude of value or cost impact, as well as taking into account the feasibility of data collection and accurate quantification. Values of higher magnitude and estimation feasibility are quantified in the majority of studies, including the earliest of studies conducted in the 2000s and 2010s. Additionally, some values of higher magnitude but low feasibility in the earliest of studies have become quantifiable in recent years. There are some values with low average system-wide levels but very high magnitude in specific locations or hours. The value magnitude in some cases can be tied to DPV penetration with low value in areas with little congestion and/or low penetration and vice versa. In these cases, values that are easier to quantify are often incorporated, while those that are more difficult are often addressed via a placeholder value. The placeholder value is paired with a discussion around data needs and methods to improve future estimates, as well as a conversation about when these value categories may increase in magnitude and necessitate more rigorous quantification. This brief summarizes findings from two meta-analyses of VoS studies that took place between 2005 and 2018, as well as findings from four additional studies published from 2018 to 2023. Table ES-1 summarizes the various value and cost categories included in each respective study and whether they were quantified, discussed, or omitted. Values such as avoided energy, capacity, transmission capacity, line losses, and avoided environmental costs are quantified in every study. Some categories were deemed harder to quantify and less impactful at the time of the study, so they were discussed but not quantified (e.g., ancillary services). Other categories, including many at the distribution level, were very locationally and/or temporally specific and dependent on high DPV penetration. These were sometimes quantified and at other times discussed. Notably, when it came to utility costs, integration costs were discussed in all cases, though they were deemed to have a small impact. Other utility costs were omitted for the most part; however, the utility-commissioned study (by NorthWestern Energy in Montana) included both lost utility revenue and programmatic/administrative cost categories. While there are some similarities across studies, each had fairly unique methods that are detailed in the body of this brief.

14 SOLAR ENERGY↗

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗