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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

EverGREEN 2045: An Energy Mix to Decarbonize Washington State

Washington State’s future resource mix is likely to be comprised of intermittent renewables and carbon-free generation including hydropower by 2045. Generation will likely be comprised of wind, solar photovoltaic (PV), batteries, pumped storage hydropower (PSH), existing nuclear power plants, and potentially enhanced geothermal systems and advanced nuclear reactor technologies. To assess the cost and stability of the future resource mix, we partner with X-energy (advanced reactor design) and AltaRock Energy (enhanced geothermal system) for proprietary cost data. After estimating the costs of these two new technologies, we design plausible future resource mix scenarios to meet Washington State’s Clean Energy Transformation Act which transitions the state to carbon-free generation by 2045. We assess the cost and stability of the future resource mix with power system analysis tools, finding revenues are sufficient to cover variable operating and maintenance costs for most technologies providing power in 2030 and 2045, but capacity payments or power purchase agreements will likely be necessary for flexible resources, including enhanced geothermal systems and advanced nuclear reactors, to participate in the future resource mix.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

System Integration of Rationally Designed Dilute Alloy Catalysts for Energy-Efficient Electrochemical CO 2 -To-Fuel Conversion

Energy effiecient electrochemical conversion of CO 2 to high-demand chemicals and transportation fuels using renewable solar and wind energy is a key technology needed for a high-productivity, low-carbon future. However, the development of scalable, low-cost, active, selective, and stable electrocatalysts remains a key challenge that needs to be overcome to enable high-volume conversion of CO 2 to feedstock chemicals for the chemical industry. In previous work, Lawrence Livermore National Laboratory (LLNL) has developed a rational design platform for dilute alloy transition metal electrocatalysts that promise to make electrochemical CO 2 conversion more energy efficient and selective. In this project, we worked with our industrial partners, Twelve and TotalEnergies, to improve scale up, integration, and stability of LLNL’s dilute alloy catalyst technology into an industry-relevant zero gap electrolyzer platform. Through virtual experiments and data analysis, we designed efficient and cost-effective copper-based catalysts. The catalyst was specifically designed to streamline the slowest and most energy-intensive step of the electrochemical chemical transformation of CO 2 to multi-carbon products – that is making the carbon-carbon bond by dimerization of the reaction intermediate carbon monoxide - resulting in up to 10% improvement in energy efficiency for C 2 products while simultaneously increasing the selectivity towards C 2 products. We tested two different scalable catalyst coating technologies and down-selected magnetron sputtering as the technique that provided the best control over catalyst loading, composition, and morphology. Using this technology, we successfully demonstrated integration of our dilute alloy catalysts into a 100 cm 2 electrolyzer platform with Faradaic efficiencies for ethylene production reaching 40% at a current density of 200 mA/cm 2 . We also developed the technology to integrate a well-defined nanoscale porosity by depositing alloy compositions that were compatible with dealloying, that is, selective leaching of an alloy component to generate nanoscale porosity. We observed that integration of the dealloying-derived nanoporosity improved catalyst performance and stability by leading to a more hydrophobic catalyst/anion exchange membrane interface. Unsolved problems that still need to be addressed are corrosion of the Cu catalyst -specifically if the used catalyst is exposed to air - as well as long term stability do to salt formation/deposition and flooding of the catalyst/electrolyzer flow channels, especially at higher current densities. As we only worked on optimization of catalyst composition, coating thickness, and morphology, further performance optimization will require a system level approach that includes optimization of electrolyzer design and membrane technology.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Novel Tools for Analyzing Life Cycle Energy Use, Carbon Emissions, and Cost of Additive Manufacturing

Decarbonizing industrial manufacturing is a significant challenge in the effort to limit the impacts of global climate change. Additive manufacturing (AM) is one pathway for reducing the impacts of manufacturing as it creates parts layer-by-layer rather than by removing (i.e., subtracting) material from solid stock as with conventional techniques. This reduces material inputs and generates less waste, which can substantially lower life cycle energy consumption and greenhouse gas emissions. However, AM adoption in the manufacturing sector has been slow, partly due to challenges in making a strong business case compared with more traditional and widely available techniques. This paper highlights the need for the development of simple screening analysis tools to speed the adoption of AM in the manufacturing sector by providing decision-makers easy access to important production life cycle emissions, and cost information. Details on the development of two Microsoft Excel software tools are provided: upgrades to an existing tool on the energy and carbon impacts of AM and a new tool for analyzing the major cost components of AM. A case study applies these two tools to the production of a lightweight aerospace bracket, showing how the tools can be used to estimate the environmental benefits and production costs of AM.

GHG emissions↗
DOE OSTI2024

Quantifying Investment Risk: Analysis of the Purchase Decision of a Nuclear Power Plant (Presentation)

Cost overruns are an ill-fated part of the deployment history of nuclear power plants (NPPs) in the United States, and yet studies increasingly show the important role nuclear technologies must play in decarbonizing the U.S. economy. Paradoxically, then, a key piece of a coherent decarbonization strategy depends on attracting investor action to a purchase where historical cost overruns have been sizable. To address this challenge, this study aims to develop a financial model that quantifies the risk of cost overruns in the decision-making process for purchasing advanced reactor concepts. Using the concept of value at risk (VaR), the model is built to evaluate financial risk nuclear construction with the aim to identify risk mitigation strategies. The objective is to identify strategies to mitigate cost-risk challenges and assess the potential reduction in investor risk exposure. This paper presents the initial development and preliminary verification of the financial risk analysis model. The development of this model involved a comprehensive approach to estimating financial risk over the operating life of NPP that stems from construction uncertainties. By utilizing net present value (NPV) with discounted cash flows, the model captures the complex interconnections of project costs, construction timelines, revenue, and uncertainties. Verifying the model involved testing historical data from previous reactor construction projects against the construction project of Vogtle 3 and 4. This paper’s results present the comparison of the preconstruction cost overrun prediction with the current cost estimates from a nearly complete Vogtle 3 and 4.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Thermal and Well Flow Performance of Closed-Loop Geothermal in the Wattenberg Area: Preprint

Closed-loop geothermal systems provide an alternative to resource-constrained hydrothermal systems and stimulation-intensive enhanced geothermal systems. In this work, we apply the slender-body theory (SBT) model, to simulate the well flow and heat transfer performance of U-loop well designs drilled in the Wattenberg area of the Denver-Julesburg Basin. Three U-loop well patterns are investigated including a single, double, and multi-lateral design. The subsurface within area is characterized by deep, hot (> 200degreesC) igneous/metamorphic basement rock underlying multiple sedimentary formations. The lateral section(s) of the U-loop lies within a target depth of 6 km where temperatures are estimated to approach 300degreesC. As a base case, conduction-only heat transfer is investigated through simulations with the SBT model within U-loops with open-hole laterals that exchange heat directly with the hot dry rock using water as a working fluid. The utilization of supercritical CO2 as a heat transfer fluid is also considered. For each scenario, the system performance in terms of annual heat production and temperature profile over a 20-year project lifetime are assessed. Also, the levelized costs of heat and electricity (LCOH and LCOE) are determined using a top-down technoeconomic analysis model. The results show that the performance and cost optimized U-loop design is one having an injection-production well spacing of 1,000 meters with ten 50-meter-spaced laterals that traverse a subsurface system with a temperature gradient of 60degreesC/km. By injecting 20 degreesC-water at a rate of 60 kg/s through this loop, an average heat production of 19 MWth can be achieved, resulting in an LCOE and LCOH of $136/MWh and $1.53/GJ, respectively, over a 20-year project life.

closed-loop geothermal↗
DOE OSTI2026

Transforming E-Waste Into Strategic Resources: Techno-Economic Analysis of Gallium and By-products Recovery from LEDs via Bioleaching

The growing demand for gallium in optoelectronics and renewable energy applications raises concerns about supply security and production sustainability. This study evaluates the techno-economic feasibility of recovering gallium and by-products (copper and nickel) from waste GaN-based LEDs via bioleaching. A process flowsheet encompassing transportation, robotic disassembly, ball milling, bioleaching, solvent extraction/electrowinning, and refining was modeled. Based on mass balance analysis, more than 53 tons of LED waste are required annually to yield 1 kg of gallium alongside substantial copper and nickel co-products. Preliminary techno-economic analysis (TEA) shows an average total cost (ATC) of 6.84 USD/kg metal when costs are allocated by mass-weighted economic value (market price) fraction, corresponding to 6.75 USD/kg for copper, 15.91 USD/kg for nickel, and 470.95 USD/kg for gallium. For gallium, direct operational costs account for more than 70% of the cost. Monte Carlo simulations further quantify cost uncertainties under market price fluctuations. This work represents the first TEA of gallium recovery from GaN-based LEDs and highlights potential pathways for future cost reduction.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Optimization-based modeling and analysis of brine reflux osmotically assisted reverse osmosis for application toward zero liquid discharge systems

Significant amounts of high-salinity wastewater generated by water-intensive industrial activities such as shale oil and gas production have raised serious environmental concerns in recent years. Existing and emerging desalination technologies offer promise to manage these high salinity wastewater streams while simultaneously producing fresh water that could be diverted for beneficial uses. Osmotically assisted reverse osmosis (OARO) is one such emerging desalination technology capable of handling hypersaline brines and achieving high recoveries. However, rigorous modeling and analysis is needed to evaluate the process performance, energy consumption, and treatment cost of various OARO configurations. Here, this work presents detailed modeling and analysis of brine-reflux OARO (BR-OARO) system and compares it with other commonly discussed configurations, including cascading osmotically mediated reverse osmosis (COMRO), consecutive loop OARO, and split feed counterflow RO, through a cost optimization-based framework. We analyze and compare the treatment costs, membrane area, specific energy consumption, and design parameters of the aforementioned configurations with the ultimate goal of achieving zero liquid discharge (ZLD). The results indicate that the BR-OARO system with treatment cost of 5.1 US $/m 3 of produced water with 10% salinity outperforms other configurations in terms of number of stages needed, treatment cost, membrane area, and energy consumption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Final Report: Process Intensification of Hydrogen Production through Sorption-Enhanced Gasification of Biomass

The University of Utah, in partnership with Idaho National Laboratory (INL), evaluated Sorption-Enhanced Gasification (SEG) as a transformative pathway for producing hydrogen with the potential for negative CO 2 emissions. SEG integrates gasification, water-gas shift, and in-situ carbon capture within a dual fluidized bed reactor to enable efficient clean hydrogen production. Key challenges related to biomass variability and process complexity were addressed through feedstock engineering, reaction optimization, and process validation. A co-pelletized biomass–limestone feedstock was developed to simplify feeding and introduction of makeup limestone. Kinetic and sorbent studies identified optimal operating conditions and confirmed the suitability of low-cost limestone, while catalysts were developed to reduce tar formation. Reactor modeling and techno-economic analysis indicated that SEG can achieve competitive hydrogen production costs, particularly when combined with carbon incentives, supporting its potential for scale-up and carbon-negative operation.

08 HYDROGEN↗
DOE OSTI2026

The Real Inputs Behind TCO: Duty Cycle Realism and Opportunity Costs using T3CO

NLR's Transportation Technology Total Cost of Ownership (T3CO) model provides realistic and robust analysis, capturing the impact of real world duty cycles and their variability in operating and opportunity costs. Case studies show that these contributions to costs can be significant and can alter conclusions about technology cost effectiveness.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

A guide to performing CO 2 electrolysis in zero-gap electrolyzers

Recent advances in the technology readiness level (TRL) of low-temperature electrochemical CO 2 reduction (eCO2R) have demonstrated that the technology has potential for industrial deployment. However, industrial deployment of eCO2R still requires advances to reach cost parity with existing thermal catalytic pathways. Technoeconomic analysis of eCO2R suggests that research and development will require a decrease in both capital expenditures and operational expenditures to be cost competitive. Here, to decrease the capital expenditures of the system will require increasing the durability to >3 years, while decreasing the operational expenditures will require an increase in energy efficiency due to the cost of electricity being the driving operational cost of a unit.

Energy↗
DOE OSTI2025

Boosting efficiency and reducing graph reliance: Basis adaptation integration in Bayesian multi-fidelity networks

The computational cost of high-fidelity numerical models makes outer-loop analysis, which requires repeated interrogation of the model such as uncertainty quantification, computationally demanding. Multi-fidelity methods, which construct a surrogate model using data from an ensemble of models of varying cost and accuracy, can substantially reduce the cost of outer-loop analysis. However, these methods can be difficult to apply when the model ensemble does not admit a clear hierarchy a priori and the correlations between models are low. Consequently, in this paper, we present a multi-fidelity method that leverages dimension reduction to enhance the correlation between models, thereby reducing the amount of data needed to train a surrogate from an unordered ensemble of models. Our method utilizes basis adaptation to build low-dimensional polynomial chaos expansions of each model and employs Multi-fidelity Networks to encode the relationships among models. We show that the resulting method exhibit two notable advantages over its counterpart: (1) enhanced accuracy (both reduced bias and variance); and (2) reduced dependency on the graph structure encoding relationships among models. We demonstrate the approach on an analytical test problem and a challenging finite element model for a spent nuclear fuel. Our method produces a surrogate model that is significantly more accurate than either a single-fidelity surrogate or a multi-fidelity surrogate constructed without basis adaptation.

42 ENGINEERING↗
DOE OSTI2022

High Temperature Steam Electrolysis Process Performance and Cost Estimates - DOE Hydrogen Program AMR Presentation

Technology readiness levels (TRLs) of electrolysis systems have dramatically increased in recent years as the interest in clean hydrogen production and decarbonization of transportation, industrial and other sectors increases across the globe. This is especially true of high temperature steam electrolysis (HTSE) / solid oxide electrolysis cell (SOEC) systems which show promise of much higher system efficiencies than other more developed electrolysis technologies. This possibility of higher efficiencies of HTSE / SOEC systems has been previously assumed to be theoretically possible but in recent years it has become less theoretical and more realistic as an increasing amount of suppliers complete lab and pilot tests showing very promising results. Research in the areas of manufacturing techniques, material selection, electrode and electrolyte compositions, and balance of plant size and integration continues at a fast pace as an increasing number of suppliers both internationally and domestically become involved. The advantages of HTSE become more pronounced when HTSE is coupled with nuclear power plants (NPPs). This is because thermal energy produced by the nuclear reactor can be used in a series of heat transfer loops and heat exchangers to vaporize HTSE feedwater, which drastically improves the economics of the process. Idaho National Laboratory (INL) has been very involved in the research and modeling of HTSE systems for a number of years, in collaboration with other national laboratories, academia, and industry stakeholders both on the hydrogen production as well as the hydrogen demand side. The modeling completed over the years on a large variety of projects has led to a wealth of knowledge at INL including in the area of the technoeconomic assessment (TEA) of HTSE systems. TEAs include process modeling of the HTSE systems to calculate system energy requirements and equipment sizing, followed by estimation of capital and operating costs to enable calculation of the levelized cost of hydrogen (LCOH). The TEA work performed has produced incremental improvements and tuning of the methods, assumptions, models, and results of the analyses as well as providing some opportunities for validating these results. The purpose of this document is to record the current baseline HTSE analyses led by INL to show the current status of assumptions and costs of these systems. Given the rapid development of this technology, the variety of suppliers entering the space, and the increasing attention government and industry are giving to such systems, this document may be updated on a periodic basis with updated analysis and assumptions. This document compiles various analyses results and approaches completed over a period of years into a single document to be used as a baseline going forward. It represents what the INL HTSE analysis group assumes to be the internal best estimate of the current operation, costs, and landscape of the HTSE industry state of the art capability for current SOEC technology in an Nth-of-a-Kind (NOAK) plant, which in this study is defined as existence of the manufacturing capacity to support previous deployment of N = 100 count of 25 MWe modular HTSE blocks (with modular equipment component cost reductions specified as following a 95% learning curve). That said, this is a public document and as such so no proprietary data was used or included in this report. There may be HTSE suppliers that have performance specifications, and cost estimates, and test data that differ from the analysis presented in this document. This document is meant to be a best conservative estimate of the technology and not an absolute reference.

08 HYDROGEN↗
DOE OSTI2024

Towards Resilient Near Real-Time Analysis Workflows in Fusion Energy Science

Nuclear fusion holds the promise of an endless source of energy. Several research experiments across the world and joint modeling and simulation efforts between the nuclear physics and high performance computing communities are actively preparing the operation of the International Thermonuclear Experimental Reactor (ITER). Both experimental reactors and their simulated counterparts generate data that must be analyzed quickly and in a resilient way to support decision making for the configuration of subsequent runs or prevent a catastrophic failure. However, the cost if the traditional techniques used to improve the resilience of analysis workflows, i.e., replicating datasets and computational tasks, becomes prohibitive with explosion of the volume of data produced by modern instruments and simulations. Therefore, we advocate in this paper for an alternate approach based on data reduction and data streaming. The rationale is that by allowing for a reasonable, controlled, and guaranteed loss of accuracy it becomes possible to transfer smaller amounts of data, shorten the execution time of analysis workflows, and lower the cost of replication to increase resilience. We develop our research and development roadmap towards resilient near real-time analysis workflows in fusion energy science and present early results showing that data streaming and data reduction is a promising way to speed up the execution and improve the resilience of analysis workflows.

Suter, Fred↗
DOE OSTI2026

Evaluating alternative steam generation pathways in the food industry

Steam generation in the food sector requires substantial energy and cost expenditures, requiring nearly half of its energy intake. Here, we used life cycle assessment and life cycle cost assessment to investigate the cost and energy impacts of steam generating alternatives: NG, biomass and hydrogen boilers and grid-supplied and self-generated electric steam generation systems (electric boilers, renewable thermal energy storage and industrial heat pumps). The analysis starts with a set of average U.S. conditions, where biomass boilers are the most cost-competitive alternative to NG. In a series of scenarios beyond average conditions, the analysis shows energy procurement costs dominate the total life cycle cost for all technologies and, unfortunately, are highly variable geographically and temporally, significantly affecting the viability of the alternatives. Results show that site-energy consumption ranges from 0.3 MMBtu/klb for industrial heat pumps to 1.6 MMBtu/klb for biomass boilers, with heat pumps achieving up to 78% lower energy use compared to natural gas systems. For the steam costs, the results show a range between $\$$8 and $\$$50/klb for NG, with biomass following closely ($\$$11 – $\$$44/klb) and grey hydrogen and IHP next ($\$$13 – $\$$33/klb and $\$$6 - $\$$78/klb), with cost reductions if IHP's cooling is utilized. Factors like operating hours, the need for cooling, and the ability to negotiate utility rates complicate the decision, making site-specific analyses critical. Therefore, we present a decision-making matrix to help manufacturers identify which steam generating technology is the best business decision for their situation. Overall, these results highlight the importance of steam generation for the facility's organizational goals, as well as the criticality of conducting individual site analyses.

Biomass boilers↗
DOE OSTI2021

Local and Global Sensitivity Analysis of a Reactive Transport Model Simulating Floodplain Redox Cycling

Reactive transport models (RTMs) are essential tools that simulate the coupling of advective, diffusive, and reactive processes in the subsurface, but their complexity makes them difficult to understand, develop and improve without accompanying statistical analyses. Although global sensitivity analysis (SA) can address these issues, the computational cost associated with most global SA techniques limits their use with RTMs. In this study, we apply distance-based generalized sensitivity analysis (DGSA), a novel and computationally efficient method of global SA, to a floodplain-scale RTM and compare DGSA results to those from local SA. Our test case focuses on the impact of 17 uncertain environmental parameters on spatially and temporally variable redox conditions within a floodplain aquifer. The input parameters considered include flow and diffusion rates, geochemical reaction rates, and the spatial distribution of sediment facies. Sensitivity was evaluated for three distinct components of the model response, encompassing both multidimensional and categorical output. Parameter rankings differ between local SA and DGSA, due to nonlinear effects of individual parameters and interaction effects between parameters. DGSA results show that fluid residence time, which is controlled by aquifer permeability, generally exerts a stronger control on redox conditions than do geochemical reaction rates. Sensitivity indices also demonstrate that sulfate reduction is key for establishing and maintaining reducing conditions throughout the aquifer. Furthermore, these results provide insights into the key drivers of heterogeneous redox processes within floodplain aquifers, as well as the main sources of uncertainty when modeling complex subsurface systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantifying agricultural productive use of energy load in Sub-Saharan Africa and its impact on microgrid configurations and costs

The use of advanced energy technologies for agricultural purposes—such as irrigation, refrigeration, crop processing, and egg incubation—has the potential to increase crop yield, reduce vulnerability to changing precipitation patterns, increase shelf life, strengthen income and employment opportunities in rural areas, and reduce emissions by displacing fossil fuel-based technologies. These productive uses of energy (PUE) in remote areas could potentially be powered by microgrids that additionally serve otherwise unelectrified communities, most of which are located in rural Sub-Saharan Africa. Here, in this paper, we use high-resolution geospatial data to estimate the end-use electricity demand for a range of agricultural PUE across Sub-Saharan Africa, and we share these data in an open-access mapping tool. Next, we use REopt®, a techno-economic optimization model of energy systems, to determine the cost and system sizing implications of incorporating agricultural PUE into microgrid designs in Kenya and Zambia. We estimate the upper bound of agricultural PUE demand for irrigation, milling, shelling, refrigeration, and egg incubation across Sub-Saharan to be 16.8 TWh/yr. We find that incorporating local agricultural PUE into microgrid system designs increases the required system sizing while having minimal impact on the levelized cost of energy of these systems. Our analysis is the first to demonstrate the PUE potential in the agricultural sector at a 10x10-kilometer resolution across Sub-Saharan Africa and to show, at scale, how site-specific PUE can impact the cost and sizing of microgrids that are otherwise deployed to serve local household and community load.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Parametric Modeling and Economic Analysis of a 2MW th 3-Stream sCO 2 Heat Exchanger

Here, this paper presents the design and cost optimization of a novel 2MW th 3-stream sCO2 plate-fin heat exchanger. This heat exchanger design is unique in that it uses reduced metal oxide particle-to-sCO2 heat exchanger for cost-effective energy storage applications. The design uses low velocity, laminar air as the re-oxidizing reactant to transfer the heat of the re-oxidizing reaction to a sCO2 power loop. The design of the heat exchanger is based on a 2-D, 3-fluid plate/fin heat transfer model. The model parameterizes the size, shape, and number of passages of the heat exchanger to calculate the temperature profile, pressure drop, and fluid velocities of all three fluids. Global heat exchanger parameters such as the effectiveness and total heat transferred to the sCO2 are then calculated for overall performance. Due to the value and increased use of sCO2 heat exchangers in power cycles, a cost model of the system based on the unique high temperature/high pressure operating conditions was created using quotes from reference projects and market analysis. These quoted air-to-sCO2 heat exchangers are then processed using multiple weighting factors pertinent to heat exchanger design, including heat exchanger type, maximum temperature, differential pressures, fluids, duty, and more. These factors are then used in an exponential function in order to generate a parameterized cost curve. The design and cost of the heat exchanger are then optimized using the SMPSO genetic algorithm in Python. The optimization objectives for the system are to maximize the overall system effectiveness, including an air recuperator for preheating, and to minimize unit costs. Additional constraints are added to the system for the sCO2 and air pressure drops, air velocity to reduce particle entrainment, and the length and volume of the heat exchanger.

Cost Model↗
DOE OSTI2021

Design and Optimization of the Direct Recycling of Spent Li-Ion Battery Cathode Materials

Direct regeneration of spent Li-ion batteries based on the hydrothermal relithiation of cathode materials is a promising next-generation recycling technology. In order to demonstrate the feasibility of this approach at a large scale, we systematically design and optimize the process parameters to minimize both energy and raw material costs. Specifically, the effects of regenerative processing parameters on the composition, structure, and electrochemical performance of the regenerated cathode materials are investigated via systematic characterization and testing. From this analysis, it was found that the raw material costs can be substantially reduced by either replacing the typically employed 4 M LiOH solution by a cost-effective mixture of 0.1 M LiOH and 3.9 M KOH or recycling of the concentrated 4 M LiOH for continuous relithiation processes. Finally, life cycle analysis suggests that this strategy results in reduced energy consumption and greenhouse gas emissions, leading to an increased potential revenue, particularly when compared with hydro- and pyrometallurgical recycling methods.

25 ENERGY STORAGE↗