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At least 1,783 records · Page 99

Porous and Amorphous Mn x Mo 3 S 13 Chalcogel Electrode for High-Capacity Conversion-Based Lithium-Ion Batteries

While Li-ion batteries (LIBs) are a leading energy storage technology, their energy densities are limited by the low capacity of conventional intercalation cathodes, driving interest in high energy-density Li–S batteries that make use of conversion chemistry. Achieving high capacity, reversibility, and cycle stability, and controlling volume changes in conversion batteries during the charge–discharge process, however, remains challenging. Here, in this study, we present a porous, amorphous, sulfide-based Mn x Mo 3 S 13 chalcogel, which concurrently offers high capacity and cycle stability. The solution-processable room temperature synthesized Mn x Mo 3 S 13 (x = 0.25) chalcogel exhibits a local structure that resembles the Mo 3 S 13 cluster with Mn 2+ distributed across the Mo 3 S 13 matrix, as determined by synchrotron X-ray pair distribution function (PDF) and extended X-ray absorption fine structure (EXAFS). Ab initio molecular dynamics (AIMD) simulations reveal that Mn 2+ incorporation shortens the polysulfide chain in the gel matrix compared to the Mo 3 S 13 chalcogel, while forming a coordination environment with disulfide groups, analogous to the experimental findings. A Li/Mn 0.25 Mo 3 S 13 half-cell delivers 897 mAh g –1 capacity during the first discharge and retains 571 mAh g –1 capacity after 100 cycles at a C/3 rate. Distribution of relaxation time (DRT) unveils a stable solid–electrolyte interphase (SEI) formation upon cycling that enables charge–discharge reversibility. Here, the enhanced capacity retention and cycle stability compared to those of the Li/Mo 3 S 13 cell are attributed to the reduced dissolution of active mass into the electrolyte, facilitated by the formation of shorter polysulfide chains within the Mn 0.25 Mo 3 S 13 structure and the strong affinity of Lewis-acidic Mn 2+ for polysulfide anions generated during the charge–discharge process of the Li/Mn 0.25 Mo 3 S 13 cell. Thus, this work illustrates a design principle of material for high-capacity and cycle-stable Li-metal sulfide batteries.

25 ENERGY STORAGE↗

Realizing high-capacity all-solid-state lithium-sulfur batteries using a low-density inorganic solid-state electrolyte

Abstract Lithium-sulfur all-solid-state batteries using inorganic solid-state electrolytes are considered promising electrochemical energy storage technologies. However, developing positive electrodes with high sulfur content, adequate sulfur utilization, and high mass loading is challenging. Here, to address these concerns, we propose using a liquid-phase-synthesized Li 3 PS 4 -2LiBH 4 glass-ceramic solid electrolyte with a low density (1.491 g cm −3 ), small primary particle size (~500 nm) and bulk ionic conductivity of 6.0 mS cm −1 at 25 °C for fabricating lithium-sulfur all-solid-state batteries. When tested in a Swagelok cell configuration with a Li-In negative electrode and a 60 wt% S positive electrode applying an average stack pressure of ~55 MPa, the all-solid-state battery delivered a high discharge capacity of about 1144.6 mAh g −1 at 167.5 mA g −1 and 60 °C. We further demonstrate that the use of the low-density solid electrolyte increases the electrolyte volume ratio in the cathode, reduces inactive bulky sulfur, and improves the content uniformity of the sulfur-based positive electrode, thus providing sufficient ion conduction pathways for battery performance improvement.

25 ENERGY STORAGE↗

Detecting Short Circuits: Post Accident Electric Vehicle Battery Safety Check

Fast and accurate detection of soft short circuits (SCs) in the battery packs of damaged electric vehicles is needed by first responders and mechanics to mitigate the potential risk from battery fires that may occur hours, days, or weeks after an accident. Here, this paper presents an SC-detection algorithm for potentially damaged lithium-ion batteries that works quickly and without a priori knowledge of the battery-pack chemistry, capacity, state of charge, or state of health. The proposed universal SC-detection algorithm is designed to be implemented on an inexpensive handheld device that can connect to and monitor the voltages of all cells in a pack. Transient filtering and linear-quadratic state observation provide estimates of normalized SC current for every cell in the pack. Cells with SC-current estimates outside a sigma-based threshold are detected. Simulations, experiments, and electric vehicle (EV) crash data are used to verify the speed, sensitivity, and accuracy of the method, demonstrating 96% accurate detection of 0.0027 C SCs in under 1 h for 5S cell groups in the lab and no false positives for crashed Volkswagen, Chevrolet, and Tesla vehicles without SCs.

25 - ENERGY STORAGE↗

Novel Short-Circuit Detection in Li-ion Battery Architectures

Industry and the battery research community don’t have accurate and affordable methods to predict catastrophic battery failures. Recently we published a new method of early detection of nascent internal shorts that are precursors to catastrophic failure. This present work was performed to determine the methods short detection capability within battery architectures consisting of two parallel strings with up to four cells in the string. It was found that detection sensitivity is a function of the number of healthy versus compromised cells in the architecture and placement of the measuring device. The method allows one to locate shorted cells without disconnecting cells or loads from the battery architecture.

25 ENERGY STORAGE↗

Review—Thermal Safety Management in Li-Ion Batteries: Current Issues and Perspectives

Approaches for thermal management of lithium-ion (Li-ion) batteries do not always keep pace with advances in energy storage and power delivering capabilities. Root-cause analysis and empirical evidence indicate that thermal runaway (TR) in cells and cell-to-cell thermal propagation are due to adverse changes in physical and chemical characteristics internal to the cell. However, industry widely uses battery management systems (BMS) originally designed for aqueous-based batteries to manage Li-ion batteries. Even the "best" BMS that monitor both voltage and outside-surface temperature of each cell are not capable of preventing TR or TR propagation, because voltage and surface-mounted temperature sensors do not track fast-emerging adverse events inside a cell. Most BMS typically include a few thermistors mounted on select cells to monitor their surface temperature. Technology to track intra-cell changes that are TR precursors is becoming available. Simultaneously, the complex pathways resulting in cell-to-cell TR propagation are being successfully modelled and mapped. Innovative solutions to prevent TR and thermal propagation are being advanced. These include modern BMS for rapid monitoring the internal health of each individual cell and physical as well as chemical methods to reduce the deleterious effects of rapid cell-to-cell heat and material transport in case of TR.

25 ENERGY STORAGE↗

Water-Processable P2-Na 0.67 Ni 0.22 Cu 0.11 Mn 0.56 Ti 0.11 O 2 Cathode Material for Sodium Ion Batteries

Sodium ion batteries offer a low-cost, sustainable, and environment-friendly solution to large-scale electrochemical energy storage systems. Layered oxides represent a family of promising cathode materials with a potential to improve the energy and power densities while reducing the material cost of sodium ion batteries. However, due to the chemical and structural instability of layered oxides in an aqueous solution, the current battery electrode manufacturing requires expensive and hazardous organic solvents, which impedes the full benefit of the low-cost, sustainable, and eco-friendly advantages. We need an effective technology that empowers a cathode with water processable properties. In this study, we set a representative example, P2-Na0.67Ni0.22Cu0.11Mn0.56Ti0.11O2, to explore its performance under water-processing conditions. This material achieves a discharge capacity of 180 mAh/g and a discharge energy of 544 Wh/kg at 22 ?C. The aging experiments indicate its superior stability against water, having negligible bulk 2 structural or chemical changes. The surface sensitive soft X-ray absorption spectroscopy shows that the P2-Na0.67Ni0.22Cu0.11Mn0.56Ti0.11O2 has stable surface chemistry in the aqueous solution. Moreover, the cells with water-processed cathodes delivered stable cycling performance with minor voltage decay, originating from the decreased cell impedance. Therefore, the present study sets a refined example to establish a low-cost, sustainable, and eco-friendly solution by developing water-processable electrode materials for sodium ion batteries.

25 ENERGY STORAGE↗

Multimodal and In-Situ Chemical Imaging of Critical Surfaces and Interfaces in Li Batteries

Interfaces play a critical role in the properties and lifetime of current generation and advanced batteries. However, detailed characterization of the critical interfaces during battery operation which can enable performance improvements and improved design has been a significant challenge requiring innovative technique development and creative experiments. This paper describes ways that information from a range of microscopy, spectroscopy, and spectrometry tools can be used to address important challenges associated with energy storage science and technology, in particular the development of advanced batteries for consumer use, transportation, , and renewable storage. Expanding the types of measurements that can be made on operational model batteries has significantly expanded the type and quality of information that can be obtained. This paper first shows examples of approaches being used to collect in situ transmission electron microscopy (TEM), secondary ion mass spectrometry (SIMS) and x-ray photoelectron spectroscopy data. The final section of the paper briefly shows two examples: the use of in situ XPS to examine SEI layers and a variety of methods including scanning TEM, atom probe tomography, scanning transmission x-ray microscopy (STXM), and x-ray adsorption near edge spectroscopy to understanding improve the performance of layered lithium transition metal oxide (LTMO) cathodes .

interface analysis, batteries in situ method, batt↗

Fingerprint Oxygen Redox Reactions in Batteries through High-Efficiency Mapping of Resonant Inelastic X-ray Scattering

Realizing reversible reduction-oxidation (redox) reactions of lattice oxygen in batteries is a promising way to improve the energy and power density. However, conventional oxygen absorption spectroscopy fails to distinguish the critical oxygen chemistry in oxide-based battery electrodes. Therefore, high-efficiency full-range mapping of resonant inelastic X-ray scattering (mRIXS) has been developed as a reliable probe of oxygen redox reactions. Here, based on mRIXS results collected from a series of Li1.17Ni0.21Co0.08Mn0.54O2 electrodes at different electrochemical states and its comparison with peroxides, we provide a comprehensive analysis of five components observed in the mRIXS results. While all the five components evolve upon electrochemical cycling, only two of them correspond to the critical states associated with oxygen redox reactions. One is a specific feature at 531.0 eV excitation and 523.7 eV emission energy, the other is a low-energy loss feature. We show that both features evolve with electrochemical cycling of Li1.17Ni0.21Co0.08Mn0.54O2 electrodes, and could be used for characterizing oxidized oxygen states in the lattice of battery electrodes. This work provides an important benchmark for a complete assignment of all mRIXS features collected from battery materials, which sets a general foundation for future studies in characterization, analysis, and theoretical calculation for probing and understanding oxygen redox reactions.

25 ENERGY STORAGE↗

Valve Regulated Lead Acid Battery Evaluation under Peak Shaving and Frequency Regulation Duty Cycles

This work highlights the performance metrics and the fundamental degradation mechanisms of lead-acid battery technology and maps these mechanisms to generic duty cycles for peak shaving and frequency regulation grid services. Four valve regulated lead acid batteries have been tested for two peak shaving cycles at different discharge rates and two frequency regulation duty cycles at different SOC ranges. Reference performance and pulse resistance tests are done periodically to evaluate battery degradation over the time. The results of the studies are expected to provide a valuable understanding of lead acid battery technology suitability for grid energy-storage applications.

25 ENERGY STORAGE↗

Updating PV and Battery Bill Savings Calculations for Net Billing: New Best Practices for Input Data and Uncertainty

Jurisdictions are increasingly adopting compensation structures for distributed PV and PV-battery systems that price exported energy lower than energy consumed onsite (net billing rates). Standard methods for calculating the bill savings from PV and PV-battery systems were developed for net metering structures, and applying these same methods to net billing structures (such as using Typical Meteorological Year weather with actual year load) introduces bias errors that underestimate PV-battery system bill savings by between 1.5\% and 9\%, depending on the utility rate. We assess the magnitude of these errors and compare them to other sources of uncertainty when estimating the bill savings from PV and PV-battery systems under more complex utility rates.

14 SOLAR ENERGY↗

Multi-Node Thermal System Model for Lithium-Ion Battery Packs: Preprint

Temperature is one of the main factors that controls the degradation in lithium ion batteries. Accurate knowledge and control of cell temperatures in a pack helps the battery management system (BMS) to maximize cell utilization and ensure pack safety and service life. In a pack with arrays of cells, a cells temperature is not only affected by its own thermal characteristics but also by its neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model, which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs. neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model, which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs.

25 ENERGY STORAGE↗

Micro Calorimeter for Batteries

As battery technology forges ahead and consumer demand for safer, more affordable, high-performance batteries grows, the National Renewable Energy Laboratory (NREL) has added a patented Micro Calorimeter to its existing family of R&D 100 Award-winning Isothermal Battery Calorimeters (IBCs). The Micro Calorimeter examines the thermal signature of battery chemistries early on in the design cycle using popular coin cell and small pouch cell designs, which are simple to fabricate and study.

25 ENERGY STORAGE↗

The Role of Innovation in the Circularity of EV Lithium-Ion Batteries

This case study analysis highlights the role of innovations in EV battery design (cells, modules, and packs), reverse supply chain, and recycling processes in yielding value for the economics of recycling (and have the largest impact on the circularity of LIBs). Part of the assessment of value will be a semi-quantitative evaluation of the value of resilience in the rapidly evolving LIB market – i.e., there are a variety of risks that recyclers would face in making a financial commitment to a recycling facility including; the possibility that batteries would not be collected in sufficient quantities, the market for key constituents (e.g., cobalt) might decrease because of changes in battery chemistry, battery manufacturers may not be willing to pay as much for recycled material, etc. The analysis would be semi-quantitative in that two simple models would be used to assess 1. material flows using a previously developed excel-based reverse supply chain flows model, and 2. A LIB recycling process material and energy balance cost model that will be used to qualitatively assess the cost impacts of process innovations and changes in feed streams. Both sets of models are highly speculative in that they rely on a multitude of assumptions and input values (e.g., EV adoption rates) that vary widely in the literature. Additionally, the initial process flow diagrams and equipment lists for the recycling cost model are based on the Argonne EverBatt model, which is still under development. However, in combination with a critical review of the literature, economic modeling can yield valuable insights into the role of innovation in the circularity of LIBs and high-technology (“energy relevant”) products in general.

28 EE - Advanced Manufacturing Office (EE-5A)↗

Predicting battery capacity from impedance at varying temperature and state of charge using machine learning

Prediction of battery health from electrochemical impedance spectroscopy (EIS) data can enable rapid measurement of battery state in real-world applications without using additional sensors or time-consuming performance measurements. However, deconvoluting the effect of capacity, state of charge, and temperature on EIS response is complicated analytically. Here, various machine-learning models, such as linear, Gaussian process, random forest, and artificial neural network regression, are utilized to predict capacity from EIS using hundreds of capacity, direct current (DC) resistance, and EIS measurements recorded under varying conditions of health, temperature, and state of charge (SOC). Several feature extraction and selection methods from traditional electrochemical analysis and statistical modeling are explored using machine-learning pipelines. EIS data from just two frequencies can accurately predict capacity, and interrogation shows that the optimal set of frequencies is not usually intuitive. Best results are achieved with an ensemble model, which predicts battery capacity with a mean absolute error of 1.9% on data from unobserved cells.

25 ENERGY STORAGE↗

Reversible Crosslinked Polymer Binder for Recyclable Lithium Sulfur Batteries with High Performance

Owing to the negative impact of the extensive utilization of batteries on the environment, sustainability of the cells needs to be included in the systemic research of batteries. In this work, a dissolvable ionic crosslinked polymer (DICP) is exploited as a binder for lithium–sulfur batteries by crosslinking the polyacrylic acid and polyethyleneimine through carboxy-amino ionic interaction. This interaction is pH-controlled, and therefore, the crosslinked binder network can be readily dissociated under basic conditions, providing a facile strategy enabling valuable components recycled through a convenient washing method. The sulfur cathode prepared using the recycled carbon–sulfur composite can deliver comparable capacity as that of fresh electrode. In addition, evidence from cell performance and characterizations, such as in situ X-ray absorption spectroscopy, in situ UV–visible spectroscopy, X-ray photoelectron spectroscopy, and density functional theory calculation, confirms that DICP is a more effective binder than its commercial counterpart on suppressing polysulfide dissolution in the electrolyte. Exploiting reversible crosslinked polymer binder for recyclable Li–S batteries with ameliorated electrochemical performance, this study illuminates sustainable development for large-scale energy storage systems.

36 MATERIALS SCIENCE↗

Deep-Learning-Enabled Crack Detection and Analysis in Commercial Lithium-Ion Battery Cathodes

We report in Li-ion batteries, the mechanical degradation initiated by micro cracks is one of the bottlenecks for enhancing the performance. Quantifying the crack formation and evolution in complex composite electrodes can provide important insights into electrochemical behaviors under prolonged and/or aggressive cycling. However, observation and interpretation of the complicated crack patterns in battery electrodes through imaging experiments are often time-consuming, labor intensive, and subjective. Herein, a deep learning-based approach is developed to extract the crack patterns from nanoscale hard X-ray holo-tomography data of a commercial 18650-type battery cathode. Efficient and effective quantification of the damage heterogeneity with automation and statistical significance is demonstrated. The crack characteristics are further associated with the active particles’ packing densities and a potentially viable architectural design is discussed for suppressing the structural degradation in an industry-relevant battery configuration.

25 ENERGY STORAGE↗

A High‐Rate Li–CO 2 Battery Enabled by 2D Medium‐Entropy Catalyst

Abstract Lithium‐air batteries based on CO 2 reactant (Li–CO 2 ) have recently been of interest because it has been found that reversible Li/CO 2 electrochemistry is feasible. In this study, a new medium‐entropy cathode catalyst, (NbTa) 0.5 BiS 3 , that enables the reversible electrochemistry to operate at high rates is presented. This medium entropy cathode catalyst is combined with an ionic liquid‐based electrolyte blend to give a Li–CO 2 battery that operates at high current density of 5000 mA g −1 and capacity of 5000 mAh g −1 for up to 125 cycles, far exceeding reported values in the literature for this type of battery. The higher rate performance is believed to be due to the greater stability of the multi‐element (NbTa) 0.5 BiS 3 catalyst because of its higher entropy compared to previously used catalysts with a smaller number of elements with lower entropies. Evidence for this comes from computational studies giving very low surface energies (high surface stability) for (NbTa) 0.5 BiS 3 and transmission electron microscopystudies showing the structure being retained after cycling. In addition, the calculations indicate that Nb‐terminated surface promotes Li–CO 2 electrochemistry resulting in Li 2 CO 3 and carbon formation, consistent with the products found in the cell. These results open new direction to design and develop high‐performance Li–CO 2 batteries.

25 ENERGY STORAGE↗

The Riddle of Dark LLZO: Cobalt Diffusion in Garnet Separators of Solid‐State Lithium Batteries

Abstract Solid‐state batteries (SSBs) with a Li 7 La 3 Zr 2 O 12 (LLZO) garnet electrolyte are attracting much attention as robust and safe alternative to conventional lithium‐ion batteries. Technical challenges in the practical implementation of garnet SSBs are related to the need for high‐temperature sintering, which often leads to undesirable chemical reactions with the cathode material. While these reactions are well understood for composite cathodes, very little is known about similar processes between cathode and separator during battery fabrication. This work focuses on understanding the processes between the composite LiCoO 2 ‐LLZO cathode and the LLZO separator and how they affect the battery performance. The extensive diffusion of Co‐ions within LLZO, which leads to the often‐observed LLZO darkening, is shown to have a significant impact on ionic conductivity, electronic conductivity, and dendrite stability of the separator. Experimental data coupled with large‐scale molecular dynamics simulations uncover the diffusion mechanism for Co‐ions and identify secondary phases that form during these interactions. In addition to extensive Co‐ion diffusion within the grains, a non‐uniform segregation of Co‐ions at grain boundaries is found leading to the formation of three distinct Co‐containing phases. This work offers a general approach to studying the fundamental ion diffusion processes that occur during the fabrication of oxide SSBs.

electrochemical properties↗