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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Structure and glide of Lomer and Lomer-Cottrell dislocations: Atomistic simulations for model concentrated alloy solid solutions

Lomer (L) and Lomer-Cottrell (LC) dislocations have long been considered to be central to work hardening in face-centered cubic (FCC) metals and alloys. These dislocations act as barriers of motion for other dislocations, and can serve as sites for twin nucleation. Recent focus on multicomponent concentrated FCC solid solution alloys has resulted in many reported observations of LC dislocations. While these and L dislocations are expected to have a role in the mechanical behavior of these alloys, little is understood about how variations in composition and associated fault energies change the response of these dislocations under stress. Here we present atomistic simulations of L and LC dislocations in a model Cu-Ni system and find that changes in composition and applied stress conditions result in a wide variety of responses, including changes in core configuration and (100) glide. The results are compared to and extend previous literature related to the nature of L/LC core structures and how they vary with respect to intrinsic materials properties and stress states. This study also provides insights into mechanisms such as twin nucleation that could have important implications for work hardening in FCC solid-solution alloys.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Hardware-Efficient Quantum Phase Estimation via Local Control

Quantum phase estimation plays a central role in quantum simulation as it enables the study of spectral properties of many-body quantum systems. Most variants of the phase estimation algorithm require the application of the global unitary evolution conditioned on the state of one or more auxiliary qubits, posing a significant challenge for current quantum devices. In this work, we present an approach to quantum phase estimation that uses only locally controlled operations, resulting in a significantly reduced circuit depth. At the heart of our approach are efficient routines to measure the complex phase of the expectation value of the time-evolution operator, the so-called Loschmidt echo, for both circuit dynamics and Hamiltonian dynamics. By tracking changes in the phase during the dynamics, the routines trade circuit depth for increased sampling cost and classical postprocessing. Our approach does not rely on reference states and is applicable to any efficiently preparable state, regardless of its correlations. We provide a comprehensive analysis of the sample complexity and illustrate the results with numerical simulations. Our methods offer a practical pathway for measuring spectral properties in large many-body quantum systems using current quantum devices.

Schiffer, Benjamin F. [Max Planck Institute of Qua↗
DOE OSTI2026

Searching for synchrotron emission from the geminga TeV halo using the planck satellite

Pulsars convert a significant fraction of their total spin-down power into very high-energy electrons, leading to the formation of TeV halos. While these halos are well characterized at TeV energies, it remains unclear whether pulsars also accelerate electrons efficiently at lower energies and how these particles propagate through their surrounding environments. We aim to test whether synchrotron emission from $\sim 50$–$300 \, \textrm{GeV}$ electrons around the Geminga pulsar can be detected in the frequency range observed by the Planck satellite. This would help constrain low-energy particle acceleration and diffusion in the vicinity of pulsars. We model the expected synchrotron emission from Geminga’s TeV halo based on various diffusion and injection spectrum scenarios and compare these predictions to publicly available multi-frequency Planck data. We find no conclusive evidence of spatially extended synchrotron emission associated with Geminga in any of Planck’s frequency bands. Our calculations show that even under favorable diffusion and injection conditions, the predicted synchrotron flux lies well below Planck’s measured background levels.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Valuing Residential Energy Efficiency: Analysis for a Prototypical Southeastern Utility [Slides]

The increasing amount of variable renewable energy resources and shifts towards more end-use and vehicle electrification suggests profound changes to power system planning and operation. Specifically, renewable energy is expected to shift net peak demand from late afternoon to early evening and end-use electrification may significantly increase winter peak demand. Residential energy efficiency is likely to align well with these shifts as it tends to produce savings in the early evening (e.g., from lighting measures) and coincident with heating loads (e.g., from envelope and space conditioning measures). Despite the opportunity to decrease system costs and emissions, residential energy efficiency is often limited by static valuation methods and its economic potential is considerably less than its technical potential. Using hourly residential energy efficiency characterizations, utility program cost data, and a capacity expansion model, we estimate the benefits of residential energy efficiency for a prototypical, summer-peaking utility in the Southeastern region. We first establish the cost-effective residential energy efficiency portfolio through “competition” with supply-side resources in a forward-looking capacity expansion model. Importantly, we then evaluate several scenarios intended to drive an increasing amount of cost-effective residential energy efficiency through measure cost reductions, increased customer adoption, policy goals (e.g., carbon price), and delivery of an integrated package of measures. The results quantify total system cost and emissions reductions, fossil-fuel plant retirements, and peak demand reductions. Results suggest the design and prioritization of policies and programs to access the untapped amount of cost-effective residential energy efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Mechanisms Engineering Test Loop (METL) Operations and Testing Report (FY2022)

This report documents the operations, testing, maintenance, and improvements that were performed at the Mechanisms Engineering Test Loop (METL) during FY2022. The METL facility had a very successful fourth year of operations and went through some new experiences such as taking the facility from its frozen state in October 2021 and thawing the facility and also recovering from an oxide plug in one of the cold trap lines. After the facility was fully thawed, the METL staff maintained the facility in a continuous molten state – either flowing sodium or a static flow condition. METL facility continued supporting the Gear Test Assembly (GTA) testing and hosted its first 28” test vessel experiment, called the Thermal Hydraulic Experimental Test Article (THETA) which was inserted into Test Vessel 4. Work to accommodate two additional experiments, a gripper test article (GrTA) and a flow sensor test article (F-STAr) continued as they are expected to make their debut in FY2023. In addition, the steam piping for the B308 scrubber unit was replaced with stainless steel piping and controls and new parts for the scrubber were purchased – such as a new pump, new storage tank, and new blower and motor. These components will ultimately replace the existing scrubber components when those 1970’s era require replacement.

42 ENGINEERING↗
DOE OSTI2021

Empirical Estimation of the Energy Impacts of Projects Installed through Residential Property Assessed Clean Energy Financing Programs in California

We examine the energy use impacts of energy efficiency and solar PV projects financed by residential property assessed clean energy (R-PACE) programs in California. We leverage household-level interval meter data to apply normalized metered energy consumption (NMEC) methods at significant scale—more than 25,000 electric meters and more than 15,000 gas meters. We develop a comparison group to account for non-project-related changes in usage. The projects include homes that replaced existing HVAC equipment with higher-efficiency units and homes that installed central heating or air conditioning equipment for the first time. We have limited information on pre-project household equipment stock so we develop a method to infer new installations. We find that projects that installed energy efficiency technologies reduce electricity consumption by approximately 3% and gas consumption by approximately 3.5% on average. When we remove homes that installed new cooling and heating equipment for the first time, savings rise to approximately 5% for electricity and approximately 6% for gas. Given the California climate and the results of an existing study of similar California projects, these results are in line with expectations. Solar PV projects produce electricity that offsets approximately 69% of household electricity consumption on average. We estimate that California R-PACE projects installed through the end of 2019 produce annual reductions in grid-tied electricity consumption of 506 GWh (equivalent to the electricity consumption of approximately 74,000 California households) and gas consumption reductions of 2 million therms (equivalent to the gas consumption of approximately 4700 California households) in a typical weather year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Multilayered microstructures with shape memory effects for vertical deployment

This paper presents a fabrication and characterization of multilayered microstructures with shape memory effects enabling large vertical deployment under electro-thermal actuation. Our previous research demonstrated vertical deployment of such microstructures by the effect of thermal mismatch. Development of equiatomic NiTi layers in the multilayered microstructure is investigated further for shape memory effects. Multilayered microstructures are built by sputtered NiTi layers and a lift-off process. Negative photoresist ma-N1420 enables clean lift-off of 500 nm thick NiTi layers by forming a significant undercut profile after development. The parametric study on co-sputter powers for Ti and Ni 50 Ti 50 targets suggests that 100 W RF on Ti target and 200 W DC on Ni 50 Ti 50 target can deposit Ni 49.62 Ti 50.38 layers. X-Ray Diffraction (XRD) and Atomic Force Microscopy (AFM) were used to study the crystal structures and surface topography of NiTi layers. XRD results of post-annealed Ni 49.62 Ti 50.38 layers show coexistence of austenite and martensitic phases at room temperature, suggesting that the transformation temperature of such NiTi layers should be approximate 20 °C. The surface topography of Ni 49.62 Ti 50.38 layers reveals substantial increase of surface roughness at ambient conditions after the annealing. Experimental verification of the multilayered microstructure for vertical deployment was carried out by Signatone Probe Station and Dual Scanning Electron Microscope/Focused Ion Beam (SEM/FIB) system. Finally, a vertical deployment of the two-dimensional (2D) multilayered microstructures for three-dimensional (3D) can be detected by applying a constant voltage of 0.04 V, and the expected 3D deployment displacement is enlarged from 2 μm to 10 μm by introducing the shape memory effect.

42 ENGINEERING↗
DOE OSTI2020

Devising novel methods for the controlled synthesis with morphology and size control of scintillator materials

Nanoscale scintillators represent an important class of materials underlying the functioning of high resolution, high ‘light yield’ radiation detection equipment, applicable for medicine in addition to security and environmental monitoring. This current study has focused on the controlled synthesis of Cs 2 ZnX 4 (X = Cl, Br) not only due to its very fast and promising radioluminescence decay time but also because no reliable synthesis protocols have been reported for producing nanoscale motifs of this material, to date. Solution-based methods can be used to synthesize products, possessing different, discrete morphologies with the ability to dictate particle size and shape. Specifically, we have demonstrated that a hot injection technique can be used to fabricate nanoscale rods and plates. Using this method, we systematically studied the effect of varying reaction variables, such as (i) reaction temperature, (ii) surfactants, and (iii) reaction time. As synthesized nanorods of Cs 2 ZnCl 4 possessed lengths of 101.3 ± 24.4 nm with widths of 17.3 ± 4.5 nm, whereas Cs 2 ZnBr 4 , created under identical conditions, were characterized by lengths of 206 ± 50 nm and widths of 26.7 ± 12.6 nm. Ligand-assisted re-precipitation (LARP) was used to produce the corresponding micron-sized particles. Under these conditions, we successfully synthesized spindles and spherical particles of Cs 2 ZnCl 4 with sizes of 1.58 ± 0.16 μm and 1.03 ± 0.34 μm, respectively, whereas plates of Cs 2 ZnBr 4 were prepared with average sizes of 0.76 ± 0.21 μm. High resolution synchrotron mapping, using the hard X-ray nanoprobe at NSLS II, was used to confirm the expected spatial distribution of Cs, Zn, and Cl within the as-produced crystals. Nanorods of Cs 2 ZnCl 4 and Cs 2 ZnBr 4 were subsequently tested for scintillation light yield and decay times. Preliminary results showed that Cs 2 ZnCl 4 maintained a light yield of 100–300 photons per MeV with a fast decay component of 2.6 ns. Finally, the Cs 2 ZnBr 4 analogue did not give rise to any perceptible scintillation emission.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Physics-Guided Machine Learning for Prediction of Cloud Properties in Satellite-Derived Solar Data

With over 20 years of high-resolution surface irradiance data covering most of the western hemisphere, the National Solar Radiation Database (NSRDB) is a vital public data asset. The NSRDB uses a two-step Physical Solar Model (PSM) that explicitly considers the effects of clouds and other atmospheric variables on radiative transfer. High-quality physical and optical cloud properties derived from satellite imagery are perhaps the most important data inputs to the PSM, representing the greatest source of radiation attenuation and scattering. However, traditional methods for cloud property retrieval have their own limitations and are unable to accurately predict cloud properties outside of nominal conditions. We introduce a physics-guided neural network that can accurately predict cloud properties when traditional methods fail or are inaccurate. Using this framework, we show reductions in relative Root Mean Square Error (RMSE) for Global Horizontal Irradiance (GHI) up to 13 percentage points for timesteps that previously had missing or low-quality cloud property data. We expect that this methodology will be effective in improving the quality of cloud property and solar irradiance data in the NSRDB.

cloud properties↗
DOE OSTI2022

Multivariable quantum signal processing (M-QSP): prophecies of the two-headed oracle

Recent work shows that quantum signal processing (QSP) and its multi-qubit lifted version, quantum singular value transformation (QSVT), unify and improve the presentation of most quantum algorithms. QSP/QSVT characterize the ability, by alternating ansätze, to obliviously transform the singular values of subsystems of unitary matrices by polynomial functions; these algorithms are numerically stable and analytically well-understood. That said, QSP/QSVT require consistent access to a single oracle, saying nothing about computing joint properties of two or more oracles; these can be far cheaper to determine given an ability to pit oracles against one another coherently. This work introduces a corresponding theory of QSP over multiple variables: M-QSP. Surprisingly, despite the non-existence of the fundamental theorem of algebra for multivariable polynomials, there exist necessary and sufficient conditions under which a desired stable multivariable polynomial transformation is possible. Moreover, the classical subroutines used by QSP protocols survive in the multivariable setting for non-obvious reasons, and remain numerically stable and efficient. Up to a well-defined conjecture, we give proof that the family of achievable multivariable transforms is as loosely constrained as could be expected. The unique ability of M-QSP to obliviously approximate joint functions of multiple variables coherently leads to novel speedups incommensurate with those of other quantum algorithms, and provides a bridge from quantum algorithms to algebraic geometry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Physics-Guided Machine Learning for Prediction of Cloud Properties in Satellite-Derived Solar Data: Preprint

With over 20 years of high-resolution surface irradiance data covering most of the western hemisphere, the National Solar Radiation Database (NSRDB) is a vital public data asset. The NSRDB uses a two-step Physical Solar Model (PSM) that explicitly considers the effects of clouds and other atmospheric variables on radiative transfer. High-quality physical and optical cloud properties derived from satellite imagery are perhaps the most important data input to the PSM, representing the greatest source of radiation attenuation and scattering. However, traditional methods for cloud property retrieval have their own limitations and are unable to accurately predict cloud properties outside of nominal conditions. We introduce a physics-guided neural network that can accurately predict cloud properties when traditional methods fail or are inaccurate. Using this framework, we show reductions in relative Root Mean Square Error (RMSE) for Global Horizontal Irradiance (GHI) up to 13 percentage points for timesteps that previously had missing or low-quality cloud property data. We expect that this methodology will be effective in improving the quality of cloud property and solar irradiance data in the NSRDB.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2024

The Design, Fabrication, and Test Program for NREL's Wave-Powered Desalination System: Preprint

Starting in 2018, the U.S. Department of Energy's Water Power Technologies Office (WPTO), initiated the development of a prize competition as a foundational investment of Powering the Blue Economy, The prize encouraged the development of small, modular, cost-competitive wave-powered desalination systems. The National Renewable Energy Laboratory (NREL) was tasked with managing the prize, known as the Waves to Water Prize (W2W), and providing technical input based on prior desalination research performed at the lab. NREL partnered with the Coastal Studies Institute (CSI) and Jennette's Pier in North Carolina for their expertise in deploying research articles at the Jennette's Pier research facility. The prize consisted of five stages that included high-level concept proposals, numerical modelling, site- specific design, subsystem prototyping, and a final ocean demonstration. Due to the logistical risks of installing numerous prototypes in the ocean at the same time, NREL was tasked with designing and building a test article to de- risk the final event. The test article design needed to represent the technologies expected in the final stage of the prize. This meant that the design was expected to follow the same rules as the competitors, providing CSI with an opportunity to practice installations and develop a final logistics plan prior to the final event. After concluding the W2W event in April 2022, the NREL test article was redeployed in August 2022 to better understand the challenges of anchoring wave energy converters (WECs) in shallow water conditions with breaking waves. For the Spanish version of this report, see NREL/CP-5700-88482 (https://www.nrel.gov/docs/fy24osti/88482.pdf).

deployment↗
DOE OSTI2024

The Design, Fabrication, and Test Program for NREL's Wave-Powered Desalination System

Starting in 2018, the U.S. Department of Energy's Water Power Technologies Office (WPTO), initiated the development of a prize competition as a foundational investment of Powering the Blue Economy, the prize encouraged the development of small, modular, cost-competitive wave-powered desalination systems. The National Renewable Energy Laboratory (NREL) was tasked with managing the prize, known as the Waves to Water Prize (W2W), and providing technical input based on prior desalination research performed at the lab. NREL partnered with the Coastal Studies Institute (CSI) and Jennette's Pier in North Carolina for their expertise in deploying research articles at the Jennette's Pier research facility. The prize consisted of five stages that included high-level concept proposals, numerical modelling, site-specific design, subsystem prototyping, and a final ocean demonstration. Due to the logistical risks of installing numerous prototypes in the ocean at the same time, NREL was tasked with designing and building a test article to de-risk the final event. The test article design needed to represent the technologies expected in the final stage of the prize. This meant that the design was expected to follow the same rules as the competitors, providing CSI with an opportunity to practice installations and develop a final logistics plan prior to the final event. After concluding the W2W event in April 2022, the NREL test article was redeployed in August 2022 to better understand the challenges of anchoring wave energy converters (WECs) in shallow water conditions with breaking waves.

desalination↗
DOE OSTI2020

GIS Visualization of Transportation Energy Consumption

Transportation is witnessing unprecedented transformation, where emerging technologies are disrupting the way we travel. Be it sharing economy, or micro-mobility, the landscape of urban transportation is undergoing a much-needed paradigm shift. In order to capture and model these shifts, researchers need to be agile in their studies of the current and future transportation landscape. The need for agility in turn calls for sophisticated, intuitive, and reliable means to visualize and share transportation data. Travel is inherently spatial, so methods of visualizing transportation information should also be rooted in spatial analysis. Geographic Information Systems (GIS) are the premier technological framework to analyze and display spatial data. GIS tools have been used in the past to depict flow of vehicles, and display of network conditions (speed, congestion, etc.). However, in an ever-changing technological landscape, spanning advancements in vehicle as well as information systems, depicting vehicle flows falls short of providing a comprehensive picture of the impact these advancements have on travel related energy consumption. To address this issue, this research effort presents a web-based mapping application to visualize how travel related energy flows across a city. The application is being developed by National Renewable Energy Laboratory researchers to integrate various transportation energy consumption models within a GIS schema. This has the goal of enabling rapid analysis of energy impacts of the dramatically evolving transportation environment. The application is being developed using a Python framework for ArcGIS Online. Using road network data from the City of Columbus, Ohio and traffic data from CATT Laboratory's Regional Integrated Transportation Information System, transportation energy consumption will be modeled at a macro level. The application aims to provide highly accurate data while still maintaining the flexibility needed to adapt the model when new technologies arise. The methodology presented through this effort is expected to provide insights into how light-duty vehicles use energy on a large scale based on the road network they use. The application will also provide data exports to enable sharing and collaboration. " need for agility in turn calls for sophisticated, intuitive, and reliable means to visualize and share transportation data. Travel is inherently spatial, so methods of visualizing transportation information should also be rooted in spatial analysis. Geographic Information Systems (GIS) are the premier technological framework to analyze and display spatial data. GIS tools have been used in the past to depict flow of vehicles, and display of network conditions (speed, congestion, etc.). However, in an ever-changing technological landscape, spanning advancements in vehicle as well as information systems, depicting vehicle flows falls short of providing a comprehensive picture of the impact these advancements have on travel related energy consumption. To address this issue, this research effort presents a web-based mapping application to visualize how travel related energy flows across a city. The application is being developed by National Renewable Energy Laboratory researchers to integrate various transportation energy consumption models within a GIS schema. This has the goal of enabling rapid analysis of energy impacts of the dramatically evolving transportation environment. The application is being developed using a Python framework for ArcGIS Online. Using road network data from the City of Columbus, Ohio and traffic data from CATT Laboratory's Regional Integrated Transportation Information System, transportation energy consumption will be modeled at a macro level. The application aims to provide highly accurate data while still maintaining the flexibility needed to adapt the model when new technologies arise. The methodology presented through this effort is expected to provide insights into how light-duty vehicles use energy on a large scale based on the road network they use. The application will also provide data exports to enable sharing and collaboration.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Direct Observation of Photoinduced Ion Migration in Lead Halide Perovskites

Unique optoelectronic, electronic, and sensing properties of hybrid organic–inorganic perovskites (HOIPs) are underpinned by the complex interactions between electronic and ionic states. In this study, the photoinduced field ion migration in HOIPs is directly observed. Using newly developed local probe time-resolved techniques, more significant CH 3 NH 3 + migration than I – /Br – migration in HOIPs is unveiled. It is found that light illumination only induces CH 3 NH 3 + migration but not I – /Br – migration. By directly observing temporal changes in bias-induced and photoinduced ion migration in device conditions, it is revealed that light illumination suppresses the bias-induced ion redistribution in the lateral device. These findings, being a necessary compensation of previous understandings of ion migration in HOIPs based on simulations and static and/or indirect measurements, offer advanced insights into the distinct light effects on the migration of organic cation and halides in HOIPs, which are expected to be helpful for improving the performance and the long-term stability of HOIPs optoelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Observations of multi-ion physics and kinetic effects in a surrogate to the solar CNO reactions

The ‘CNO process’ occurs in heavier stars with finite metallicity in which hydrogen burning is catalyzed in the presence of 12 C. These reactions are more strongly dependent on temperature than the pp cycle reactions, and thus the CNO cycle dominates only in massive stars. For these types of reactions to be studied at ICF facilities such as OMEGA, an implosion platform using heavier nuclei in the fuel and capable of creating ion temperatures on the order of at least 20 keV is required. A potential route to reach these conditions is to take advantage of kinetic effects in low-convergence shock-driven ‘exploding pusher’ implosions. In this experiment, shots were conducted at the OMEGA laser facility using the surrogate reaction 13 C + D. Its cross section is substantially higher than the actual astrophysical CNO reactions. The yield of this reaction in these implosions was much lower than expected. Finally, physical explanations are discussed, with significant species stratification the likely explanation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Ironing out the transition metal contribution to the magnetism of the n = 3 members of the homologous series Pr n +1 M n Ge 3 n +1 (M = Fe, Co): Pr 4 Fe 3 Ge 10 vs. Pr 4 Co 3 Ge 10

The Ln n+1 M n X 3n+1 (Ln = lanthanide, M = transition metal, and X = tetrel) homologous series provides a platform to study collective phenomena in quantum materials. Here, in this work, we compare the crystal growth, structure, and magnetic properties of the n = 3 members of the Pr n+1 M n Ge 3n+1 (M = Fe, Co) analogues, Pr 4 Fe 3 Ge 10 (a = 4.3207 (10) Å, b = 35.523 (8) Å, c = 4.2982 (15) Å, and V = 659.7 (3) Å 3 ) and Pr 4 Co 3 Ge 10 (a = 4.3091 (12) Å, b = 35.750 (9) Å, c = 4.2807 (11) Å, and V = 659.4 (3) Å 3 ). We determined that the ideal flux growth conditions for each compound are highly dependent on the concentration of Sn flux and quench temperature. Pr 4 Fe 3 Ge 10 orders ferromagnetically at 10 K along the c-direction while Pr 4 Co 3 Ge 10 orders antiferromagnetically at 16 K along the b-direction. For both compounds, we observed a magnetic moment higher than that expected for only Pr 3+ ions (3.58 µ B /Pr), implying that the transition metal ions contribute to magnetic ordering (3.91, 3.48, and 3.69 µ B /Pr for Pr 4 Fe 3 Ge 10 , and 3.76, 4.04, and 3.83 µ B /Pr for Pr 4 Co 3 Ge 10 measured along the a-, b-, and c-directions, respectively). Moreover, the zero-field Mössbauer spectrum obtained at 4.2 K for Pr 4 Fe 3 Ge 10 demonstrates that the iron sites participate in magnetic ordering.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Sustainable bioleaching of lithium-ion batteries for critical materials recovery

The demand for lithium-ion batteries (LIBs) has increased substantially over the last few decades due to their longer lifetime, greater resistance to self-discharge, and higher output voltage compared to other battery types. With the global trend of electrifying vehicle fleets, the number of LIBs reaching their end-of-life (EOL) is expected to grow substantially in the next decade. These EOL LIBs represent a significant secondary source of materials (e.g., Li, Co, Ni, Mn) that can be recovered and reused in LIBs or other products. In this study, we developed a bioleaching process that could recover critical materials from EOL LIBs in an economical and environmentally sustainable manner under industrially relevant conditions. Black mass, i.e., cathode-containing powder, prepared from EOL LIBs was leached using a biolixiviant produced from corn stover by Gluconobacter oxydans bacteria. Iron(II) was used as a reducing agent to promote metal dissolution. Techno-economic analysis (TEA) estimated a potential average profit margin of 21% for processing 10,000 t of black mass per year, which represents approximately 30% of the available black mass in the US in 2020. Life cycle assessment (LCA) demonstrated that bioleaching of spent LIBs could be more environmentally sustainable than alternative hydrometallurgical recovery methods such as hydrochloric acid leaching (16-19 kg vs. 43-91 kg CO 2 equivalent global warming potential per kg of recovered cobalt). The TEA results are highly dependent on the cost of black mass production, which varies by EOL LIB collection and transportation costs. Finally, emerging technologies for deactivating used LIBs for fire safety at collection centers will allow the transport of EOL LIBs as non-hazardous materials, lower the cost of preparing black mass and thereby increase economic prospects for EOL LIBs recycling using this approach.

25 ENERGY STORAGE↗