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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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At least 55 records · Page 3

The role of oxygen in automotive grade lithium-ion battery cathodes: an atomistic survey of ageing

The rising demand for high-performance lithium-ion batteries, pivotal to electric transportation, hinges on key materials like the Ni-rich layered oxide LiNi x Co y Al z O 2 (NCA) used in cathodes. The present study investigates the redox mechanisms, with particular focus on the role of oxygen in commercial NCA electrodes, both fresh and aged under various conditions (aged cells have performed >900 cycles until a cathode capacity retention of ~80%). Our findings reveal that oxygen participates in charge compensation during NCA delithiation, both through changes in transition metal (TM)–O bond hybridization and formation of partially reversible O 2 , the latter occurs already below 3.8 V vs. Li/Li + . Aged NCA material undergoes more significant changes in TM–O bond hybridization when cycling above 50% SoC, while reversible O 2 formation is maintained. Nickel is found to be redox active throughout the entire delithiation and shows a more classical oxidation state change during cycling with smaller changes in the Ni–O hybridization. By contrast, Co redox activity relies on a stronger change in Co–O hybridization, with only smaller Co oxidation state changes. The Ni–O bond displays an almost twice as large change in its bond length on cycling as the Co–O bond. The Ni–O 6 octahedra are similar in size to the Co–O 6 octahedra in the delithiated state, but are larger in the lithiated state, a size difference that increases with battery ageing. These contrasting redox activities are reflected directly in structural changes. The NCA material exhibits the formation of nanopores upon ageing, and a possible connection to oxygen redox activity is discussed. The difference in interaction of Ni and Co with oxygen provides a key understanding of the mechanism and the electrochemical instability of Ni-rich layered transition metal oxide electrodes. Our research specifically highlights the significance of the role of oxygen in the electrochemical performance of electric-vehicle-grade NCA electrodes, offering important insights for the creation of next-generation long-lived lithium-ion batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ageing Studies of Mega Battery Packs for Grid Storage Applications Using Physics Based Modeling

The lower Levelized Cost of Electricity (LCOE) from wind and solar photovoltaics has enabled for greater integration of variable energy resources with energy storage tech-nologies such as larger centralized lithium-ion battery megapacks (with 1MWh total energy and 500V rating) to provide utility-scale services to grid operators. The daily cycling of standalone lithium-ion grid storage will reduce the battery cells' capacity due to several degradation mechanisms. A comprehensive physics-based Python tm framework called Liionpack was developed to estimate these megapacks' remaining life and ageing. The study includes various degradation mechanisms coupled to the electrochemical-thermal model at the pack level. The effect of the inhomogeneities from cell-to-cell thermodynamic and kinetic properties for different working conditions including temperature and charge/discharge protocols on the ageing of a megapack are presented here.

Karra, Vikrant↗

Cost Competitive Process of Battery Grade Oxides Preparation from Aged LIBS

The increasing demand for lithium-ion batteries (LIBs ) is driving development of advanced recycling and refining methods. In this project, new cathode active materials are prepared from recycled lithium battery materials and subsequently electrochemically evaluated in coin cells. In detail, scrap LIBs were mechanically processed into a metal rich black mass, then reductive acid leached into an aqueous metal solution, and finally high-purity metal hydroxide precursor materials were prepared by selective electrochemical flow precipitation. Closed-loop LIB recycling into active electrode materials will enable US manufacturers to break their reliance on foreign sources of critical materials. For example, electroextraction process used here has potential to significantly reduce chemical & water use as compared to traditional metallurgic techniques. To this end, electroextracted materials refined from used batteries were collected and processed to be tested as precursor cathode active material (pCam).During this project ,samples of high-purity recycled NMC hydroxide (~2kg each) were received from Nth Cycle. In the first received batch some impurities like cadmium, calcium, and sodium are present in quantities that would negatively impact battery performance. Nth Cycle indicated that the impurities such as cadmium are present due to poor battery separation and co-shredding of NiCd batteries with with LIB. Cadmium was not present in the two subsequent batches as Nth Cycle processed cadmium free black mass. Thus, effective recycled battery sorting is critical to closed-loop LIB recycling into active electrode materials.

99 GENERAL AND MISCELLANEOUS↗

Cost Competitive Process of Battery Grade Oxides Preparation from Aged LIBS

The increasing demand for lithium-ion batteries (LIBs) is driving development of advanced recycling and refining methods. In this project, new cathode active materials are prepared from recycled lithium battery materials and subsequently electrochemically evaluated in coin cells. In detail, scrap LIBs were mechanically processed into a metal rich black mass, then reductive acid leached into an aqueous metal solution, and finally high-purity metal hydroxide precursor materials were prepared by selective electrochemical flow precipitation. Closed-loop LIB recycling into active electrode materials will enable US manufacturers to break their reliance on foreign sources of critical materials. For example, electroextraction process used here has potential to significantly reduce chemical & water use as compared to traditional metallurgic techniques. To this end, electroextracted materials refined from used batteries were collected and processed to be tested as precursor cathode active material (pCam). During this project , samples of high-purity recycled NMC hydroxide (~2 kg each) were received from Nth Cycle. In the first received batch some impurities like cadmium, calcium, and sodium are present in quantities that would negatively impact battery performance. Nth Cycle indicated that the impurities such as cadmium are present due to poor battery separation and co-shredding of NiCd batteries with with LIB. Cadmium was not present in the two subsequent batches as Nth Cycle processed cadmium free black mass. Thus, effective recycled battery sorting is critical to closed-loop LIB recycling into active electrode materials.

25 ENERGY STORAGE↗

Cost Competitive Process of Battery Grade Oxides Preparation from Aged LIBs

The increasing demand for lithium-ion batteries (LIBs) is driving development of advanced recycling and refining methods. In this project, new cathode active materials are prepared from recycled lithium battery materials and subsequently electrochemically evaluated in coin cells. In detail, scrap LIBs were mechanically processed into a metal rich black mass, then reductive acid leached into an aqueous metal solution, and finally high-purity metal hydroxide precursor materials were prepared by selective electrochemical flow precipitation. Closed-loop LIB recycling into active electrode materials will enable US manufacturers to break their reliance on foreign sources of critical materials. For example, electroextraction process used here has potential to significantly reduce chemical & water use as well as waste production as compared to traditional metallurgic techniques. To this end, electroextracted materials refined from used batteries were collected and processed to be tested as precursor cathode active material (pCAM). For this project, two samples of high purity recycled NMC hydroxide (~1 kg each) were received from N th Cycle’s Ohio demonstration facility. The NMC compositions of the two materials are similar, and the levels of impurities have been confirmed. Indeed, impurities like copper, boron and sodium are present in quantities that could negatively impact battery performance. However, some studies have demonstrated that the control of the quantity of elements like copper or boron may improve the electrochemistry properties of Lithium-NMC batteries. The principal objective is to determine the electrochemical performance of these 2 NMC hydroxide batches and clearly determine the effect of the impurities on the performance.

25 ENERGY STORAGE↗

Quantitative Analysis of Origin of Lithium Inventory Loss and Interface Evolution over Extended Fast Charge Aging in Li Ion Batteries

During the extreme fast charging (XFC) of lithium-ion batteries, lithium inventory loss (LLI) and reaction mechanisms at the anode/electrolyte interface are crucial factors in performance and safety. Determining the causes of LLI and quantifying them remain an essential challenge. We present mechanistic research on the evolution and interactions of aging mechanisms at the anode/electrolyte interface. We used NMC 532 /graphite pouch cells charged at rates of 1, 6, and 9 C up to 1000 cycles for our investigation. The cell components were characterized after cycling using electrochemical measurements, inductively coupled plasma optical emission spectroscopy, 7 Li solid-state nuclear magnetic resonance spectroscopy, and high-performance liquid chromatography/mass spectrometry. The results indicate that cells charged at 1 C exhibit no Li plating, and the increase of SEI thickness is the dominant source of the Li loss. In contrast, Li loss in cells charged at 9 C is related to the formation of the metallic plating layers (42%) the SEI layer (38.1%) and irreversible intercalation into the bulk graphite (19%). XPS analysis suggests that the charging rate has little influence on the evolution of SEI composition. The interactions between competing aging mechanisms were evaluated by a correlation analysis. In conclusion, the quantitative method established in this work provides a comprehensive analytical framework for understanding the synergistic coupling of anodic degradation mechanisms, forecasting SEI failure scenarios, and assessing the XFC lithium-ion battery capacity fade.

25 ENERGY STORAGE↗

Elastic-Poroelastic Simulation of Locally Resonant Ultrasound for Aging Li-Metal Batteries

An elastic-poroelastic simulation of ultrasound inspection for lithium-metal batteries is presented and compared to empirical reflection spectra measured during battery cycling. Simulated reflection spectra were obtained using a two-dimensional (2D) plane strain model, comprised of dozens of individual microns-thick layers within a Li-metal pouch cell. The simulated reflection spectra were then compared to ultrasonic reflection spectra measurements taken intermittently during cell cycling. A sensitivity analysis and parameter calibration were performed for the pristine pouch cell simulation prior to cycling, providing a baseline to account for difficult to measure poroelastic material parameters. Then, the reduction in solid Li anode thickness and corresponding growth into a mossy lithium layer was modeled to represent aging conditions. Results from both simulations and empirical inspections show similar trends in through-thickness resonance frequencies due to cell aging.

Battery↗

Rapid failure mode classification and quantification in batteries: A deep learning modeling framework

Unique, rapid identification and quantification of the dominant aging modes in lithium-ion batteries (LiBs) with early and non-specialized test data is a significant scientific challenge. Leveraging synthetic-data, deep-learning (DL) techniques have great potential to enable fast and robust classification and quantification of battery aging modes that produce different patterns of cell aging. This study, for the first time, presents a synthetic–data-based DL modeling framework for rapid and automatic classification and quantification of battery-aging modes and resultant aging with experimental validation. Availing synthetic dQ.dV -1 curves for ~26000 initial conditions and aging modes, the framework classified the dominant aging modes, for cells undergoing fast charge, in fewer than 100 cycles. Upon classification, the framework quantified the evolution of the aging modes, which were often nonuniform with cycling, for 22 gr/NMC532 pouch cells tested up to 600 cycles at different charging rates (1C–9C).

25 ENERGY STORAGE↗

Mitigating Calendar Aging in Si-NMC Batteries with Advanced Dual-Salt Glyme Electrolytes

In addressing the critical challenge of calendar aging in silicon (Si)-based lithium-ion batteries, this study introduces a groundbreaking strategy utilizing glyme-type dual-salt electrolytes (lithium bis(trifluoromethanesulfonyl)imide [LiTFSI] and lithium difluoro(oxalato)borate [LiDFOB]). These electrolytes are demonstrated to significantly mitigate parasitic reactions and capacity loss in Si-NMC (lithium nickel manganese cobalt oxide) full cells, especially when compared with traditional carbonate-based electrolytes. Further, our exhaustive mechanistic analysis reveals that such electrolytes not only preserve the integrity of the Si anode but also improve the cathode/electrolyte interphases (CEI) through the formation of a conformal coating on the high-voltage cathode surface. This dual-salt approach, enhanced by the addition of a phosphate additive, effectively decelerates calendar aging, marking a substantial advance in the quest for durable and reliable Si-based energy storage technologies. The findings underscore the vital role of electrolyte composition in extending the calendar life of Si batteries, offering an alternative avenue toward maximizing the performance and longevity of next-generation Li-Si batteries.

36 MATERIALS SCIENCE↗

An experimentally validated electro-thermal EV battery pack model incorporating cycle-life aging and cell-to-cell variations

Lithium-ion batteries are used in a wide variety of applications. To meet the power and energy demands of these applications battery packs are composed of hundreds to thousands of cells. The electrical and thermal interactions between cells introduce additional complexity in the pack dynamics. To capture these effects, a battery pack model composed of 192 cells based on a first-generation (2012) Nissan Leaf battery pack is developed in MATLAB/Simulink/Simscape. Here, with this model, we simulate the electrical dynamics (using a first-order equivalent-circuit model), the thermal dynamics (using a first-order lumped-parameter thermal model), and the aging dynamics (using a semi-empirical severity factor-based model) of every cell in the pack and we also create a pack thermal model that explicitly captures the heat exchange between the modules, and the cells contained within, during operation. The models are calibrated and validated, both at the cell and pack level, with experimental data. Two different case studies of this pack model are investigated. In the first case study, an initial, normally-distributed, cell-to-cell capacity variation is introduced and its effect on the pack voltage and module temperatures is studied. In the second case study, we deliberately insert cells with lower than nominal capacity into the pack and we investigate how this type of initial cell-to-cell capacity variation affects the pack’s ability to deliver energy over time. Finally, we also study how parallel-connected cells can reduce the effects of cell-to-cell variations at the expense of increased aging of the pack overall.

25 ENERGY STORAGE↗

Calendar aging of silicon-containing batteries

High-energy batteries for automotive applications require cells to endure well over a decade of constant use, making their long-term stability paramount. This is particularly challenging for emerging cell chemistries containing silicon, for which extended testing information is scarce. While much of the research on silicon anodes has focused on mitigating the consequences of volume changes during cycling, comparatively little is known about the time-dependent degradation of silicon-containing batteries. Here we discuss a series of studies on the reactivity of silicon that, collectively, paint a picture of how the chemistry of silicon exacerbates the calendar aging of lithium-ion cells. Assessing and mitigating this shortcoming should be the focus of future research to fully realize the advantages of this battery technology.

25 ENERGY STORAGE↗

Dynamic cycling enhances battery lifetime

Laboratory aging campaigns benchmark and elucidate the complex degradation behavior of lithium-ion batteries, and are critical not only for developing new battery chemistries and cell designs but also for engineering reliable battery management systems. Critically, these laboratory experiments aim to quantify and capture realistic aging mechanisms. In this study, we systematically compare dynamic discharge profiles representative of electric vehicle driving to the well-accepted constant-current profiles. Surprisingly, we discovered that dynamic discharge enhances lifetime substantially compared to constant current discharge. Specifically, for the same average current and voltage window, varying the dynamic discharge profile leads to an increase of up to 38 % in equivalent full cycles at end-of-life. Explainable machine learning reveals the importance of low-frequency current pulses as well as time-induced aging under these realistic discharge conditions. Our work quantifies the importance of evaluating new battery chemistries and designs with realistic load profiles, and highlights the opportunities to revisit our understanding of aging mechanisms at the chemistry, materials, and cell levels.

25 ENERGY STORAGE↗

Battery Life Prediction Using Reduced-Order Physics Models and Machine Learning (CRADA Final Report)

Phase 1 (Original CRADA, plus no-cost extension modifications #1-3, 6/1/2017 to 3/13/2021): The Australian Department of Defence (AUDoD) is performing accelerated aging tests of Li-ion batteries to benchmark their reliability and degradation characteristics. Using its previously developed battery lifetime predictive model framework, the National Laboratory of the Rockies (NLR) will develop analytical models based the AUDoD data to predict lifetime of the multiple Li-ion battery chemistries under real-world use scenarios of interest to AUDoD. The NLR model is based on physical degradation mechanisms encountered by Li-ion batteries and has been previously validated. Phase 2 (CRADA modification #4, plus no-cost extension modification #5, 2/22/2021 to 3/30/2025): Train and support Australian Department of Defence personnel to use NLR software for model-based estimation of Li-ion battery lifetime using accelerated battery aging data collected by the Australian Department of Defence. Under separate DOE funding from 2019 to 2021, NLR enhanced its battery life-prediction software using machine learning algorithms to automate portions of the model-fitting process, requiring significantly less labor and expert judgment and also adding uncertainty quantification, increasing statistical rigor. Under Phase 2, NLR will customize NLR Software and provide it to AuDoD. NLR will enhance its NLR Model to capture aging modes of AuDoD's multi-cell modules, including cell-balancing effects. NLR will develop example single-cell and multi-cell models based on one AuDoD battery aging dataset. NLR will train AuDoD personnel on NLR Software. By the conclusion of the project, NLR will have provided AuDoD the training materials, a user manual and software needed to perform their own analysis of additional and/or future battery aging datasets.

33 ADVANCED PROPULSION SYSTEMS↗

Physics-Based Analysis of Cell Imbalances and Aging in Lithium-Ion Battery Modules and Packs

Lithium-ion battery (LIB) packs are a key solution for grid-scale energy storage, enabling grid resilience and supporting critical infrastructure. LIB modules and packs experience current imbalances and uneven cell aging due to various design and operational factors, and require a battery management system (BMS) to continuously monitor and control. In this context, a physics-based modeling framework for LIB modules and packs (liionpack) was enhanced to identify design and control strategies that minimize current imbalance and improve module/pack operation. Simulations of an 8-cell parallel-connected module demonstrate that reducing current imbalance leads to more uniform cell aging and improved module/pack-level degradation predictions. The analysis shows that current imbalance are affected by the electrical resistances. Terminal location significantly affects imbalance, with opposite-end terminal connections at intermediate branches minimizing the imbalance, and the pack circuit construction influences the accuracy of physics-based analysis at the pack scale. This framework enables design optimization of modules and packs through a fast and easy evaluation of pack performance and aging, and supports the development of aging-informed balancing strategies compatible with BMS implementation. Thereby, offering practical pathways to improve reliability and cycle life predictions in large-scale battery energy storage systems.

Ayalasomayajula, Surya Mitra [Oak Ridge National L↗