Performance Of Li-ion Batteries Research Articles

Interpreting CNN-RNN Hybrid Model-Based Ensemble Learning with Explainable Artificial Intelligence to Predict the Performance of Li-Ion Batteries in Drone Flights

Li-ion batteries are important in modern technology, especially for drones, due to their high energy density, long cycle life, and lightweight properties. Predicting their performance is crucial for enhancing drone flight safety, optimizing operations, and reducing costs. This involves using advanced techniques like machine learning (e.g., Convolutional Neural Network-CNNs, Recurrent Neural Network-RNNs), statistical modeling (e.g., Kalman Filtering), and explainable AI (e.g., SHAP, LIME, PDP) to forecast battery behavior, extend battery life, and improve drone efficiency. The study aims to develop a CNN-RNN-based ensemble model, enhanced with explainable AI, to predict key battery metrics during drone flights. The model’s predictions will aid in enhancing battery performance via continuous, data-driven monitoring, improve drone safety, optimize operations, and reduce greenhouse gas emissions through advanced recycling methods. In the present study, comparisons are made for the behaviors of two different drone Li-ion batteries, numbered 92 and 129. The ensemble model in Drone 92 showed the best performance with MAE (0.00032), RMSE (0.00067), and R2 (0.98665) scores. Similarly, the ensemble model in Drone 129 showed the best performance with MAE (0.00030), RMSE (0.00044), and R2 (0.98094) performance metrics. Similar performance results are obtained in the two predictions. However, drone 129 has a minimally lower error rate. When the Partial Dependence Plots results, which are one of the explainable AI (XAI) techniques, are interpreted with the decision tree algorithm, the effect of the Current (A) value on the model estimations in both drone flights is quite evident. When the current value is around −4, the model is more sensitive and shows more changes. This study will establish benchmarks for future research and foster advancements in drone and battery technologies through extensive testing.

Enabling Fast‐Charging and High Specific Capacity of Li‐Ion Batteries with Nitrogen‐Doped Bilayer Graphdiyne: A First‐Principles Study

AbstractCarbon‐based materials are the most important anode materials for Li‐ion batteries (LIBs). To improve the electrochemical performance of LIBs for high energy density and fast charging, advanced carbon allotropes are in the research focus. In this work, we applied the density functional theory to investigate the atomic and electronic structures as well as high Li‐ion specific capacity of graphdiyne (GDY). The atomic structures of monolayer graphdiyne (MGDY), bilayer AB(β1)‐stacking graphdiyne (AB(β1)BGDY) and nitrogen‐doped AB(β1)BGDY (N‐AB(β1)BGDY) at different lithiation states were thoroughly investigated. The AB(β1)BGDY and N‐AB(β1)BGDY exhibit promising characteristics in Li‐ion adsorption and intercalation, enhancing its specific capacity from 744 mAhg−1 in the monolayer GDY to 807 mAhg−1 in the bilayer. Besides increasing the capacity through a bilayer‐structure, it is possible to tailor its structural stability and band gap by doping. Especially shown for N‐AB(β1)BGDY (~1 %), an increased structural stability and a decreased band gap of 0.24 eV is found. While this means that N doping in AB(β1)BGDY can lead to longer‐lasting and more stable operatable high‐capacity anodes in LIBs, it increases the open‐circuit voltage (OCV).

Unraveling the Complex Temperature-Dependent Performance and Degradation of Li-Ion Batteries with Silicon-Graphite Composite Anodes

Competing effects of graphite and Si result in a complex temperature dependent performance and degradation of Li-ion batteries with Si-graphite composite anodes. This study examines the influence of varying the Si content (0 to 20.8 wt%) in Si-graphite composite anodes with consistent areal capacity and N/P ratio in full cells containing NMC622 cathodes. One hundred pilot-scale double-layer pouch cells were built and cycle aged in the temperature range from −10 to 55 °C. Electrochemical characterization demonstrated that increasing Si contents enhance capacity and mitigate internal resistance at low temperatures. On the other hand, high Si contents decrease charge-discharge energy efficiency and cycle life, particularly at elevated temperatures. Post-mortem analysis of aged electrodes, including physico-chemical characterization (scanning electron microscopy, energy-dispersive X-ray analysis, thickness measurements) and cell reconstruction revealed significant solid electrolyte interphase growth and increased loss of active material in anodes with high Si content. The optimum temperature for longest cycle life as derived from Arrhenius plots decreased from 30 °C for graphite anodes to 10 °C for cells with moderate Si content up to 5.8 wt%. These findings allow the design of optimized cells by balancing the Si content versus operating temperature in order to achieve lowest cell aging.

LiF-enriched interphase promotes Li+ desolvation and transportation enabling high-performance carbon anode under wide-range temperature

Li-ion batteries (LIBs) have made inroads into the electric vehicle area with high energy densities, but they still suffer from slow kinetics of Li+ limited by the graphite anode especially at high current density and low-temperature conditions. Sluggish de-solvation of Li+ at the electrode surface and slow Li+ transfer in solid electrolyte interphase (SEI) are main determining factors that restrict the fast-charging and low-temperature performance of graphite-based LIBs. Here, we construct the sodium lignosulfonate layer with abundant polar functional groups on the lithium-montmorillonite surface, which can make it simple for electrons transfer to promote in-situ formation of LiF-based SEI with high ionic conductivity. The thin and robust LiF-based SEI promotes the de-solvation of Li salts and Li+ transfer as proved by the comprehensive electrochemical studies and density functional theory (DFT) calculations. Consequently, a combination of excellent stability and fast-charging ability for LIBs at room and low temperatures is achieved. The designed anode shows the remarkable capacity of 1500 mAh/g at 0.1 A/g, which was 3–4 times better than the commercial graphite. At the high current density of 5 A/g, it can still keep stable with the capacity retention of 70 % after 7000 cycles. Besides, an impressive 70 % of their room-temperature capacity is attained at −10 °C and 150 mAh/g is achieved under the extremely low temperature of −40 °C. This study establishes the effective strategy to construct the LiF-rich interface on the surface of anode to improve the Li+ kinetics and stability of the battery.

An Alternative Polymer Material to PVDF Binder and Carbon Additive in Li-Ion Battery Positive Electrode.

Li-ion battery performance relies fundamentally on modulation at the microstructure and interface levels of the composite electrodes. Correspondingly, the binder is a crucial component for mechanical integrity of the electrode, serving to interconnect the active material and conductive additive and to firmly attach this composite to the current collector. However, the commonly used poly(vinylidenefluoride) (PVDF) binder presents several limitations, including the use of toxic solvent during processing, a low electrical conductivity which for compensation requires the addition of carbon black, and weak interactions with active materials and collectors. This study investigates Poly(3,4-ethylenedioxythiophene):poly[(4-styrenesulfonyl) (trifluoromethylsulfonyl) imide] (PEDOT:PSSTFSI) as an alternative binder and conductive additive, in replacement of both PVDF and carbon black, in Li-ion batteries with LiFe0.4Mn0.6PO4 at the positive electrode. Complex PEDOT:PSSTFSI significantly improves the electronic conductivity and lithium diffusion coefficient within the electrode, in comparison to standard PVDF binder and carbon black. This enhances significantly the electrochemical performance at high C-rates and for high active mass loading electrodes. Furthermore, an excellent long-range cyclability is achieved.

Entropy-Stabilized Multication Fluorides as a Conversion-Type Cathode for Li-Ion Batteries-Impact of Element Selection.

Metal fluorides (e.g., FeF2 and FeF3) have received attention as conversion-type cathode materials for Li-ion batteries due to their higher theoretical capacity compared to that of common intercalation materials. However, their practical use has been hindered by low round-trip efficiency, voltage hysteresis, and capacity fading. Cation substitution has been proposed to address these challenges, and recent advancements in battery performance involve the introduction of entropy stabilization in an attempt to facilitate reversible conversion reactions by increasing configurational entropy. Building on this concept, high entropy fluorides with five cations were synthesized by using a simple mechanochemical route. In order to examine the impact of element selection, Co0.2Cu0.2Ni0.2Zn0.2Fe0.2F2 (HEF-Fe) was compared with Co0.2Cu0.2Ni0.2Zn0.2Mg0.2F2 (HEF-Mg), replacing electrochemically inactive Mg with Fe as an active participant in the conversion reaction. Combining electrochemical measurements with first-principles calculations, high-resolution electron microscopy, and synchrotron X-ray analysis, HEFs' battery performances and conversion reaction mechanisms were investigated in detail. The results highlighted that replacement of Mg with Fe was beneficial, with enhanced capacity, rate capability, and surface stability. In addition, it was found that HEF-Fe showed similar cycle stability without an electrochemically inactive element. These findings provide valuable insights for the design of high entropy multielement fluorides for improved Li-ion battery performance.

Optimal estimation of SoC, SoH using machine learning models and design of control algorithm for active cell balancing in lithium ion batteries

Abstract Electric vehicles transform the automotive industry by replacing traditional vehicles powered by fossil fuels with less polluting and efficient vehicles. They are powered by rechargeable Li-ion batteries. While there are drawbacks associated with Li-ion battery technology, it's important to note that these challenges can be addressed or mitigated effectively. A battery management system ensures the tracking of all functions performed by the battery. An advanced battery management system should accurately estimate the battery's state of health and state of charge. This paper aims to develop machine learning models for the estimation of the state of health and state of charge and to implement cell balancing in a battery management system. A dataset of battery charging and discharging profiles was used to train various machine learning models for estimation. These methods are computationally less complex than conventional methods. In addition, a cell balancing algorithm is implemented to control the charging and discharging of individual cells in a battery pack and balance the state of charge of each cell. The machine learning solution is created using several machine learning models, including Gradient Boosting, Random Forest, Linear Regression, AdaBoost, and Multi-layer Perceptron. Among the models Gradient Boosting and Random Forest provide good MSE and R2 score. The use of machine learning algorithms for the assessment of state of health and charge estimation combined with the design of an efficient control algorithm for active cell balancing offers significant advancements in the battery management system to optimise the performance, reliability, and useful life of Li-ion batteries. The paper also presents a case study utilising a combination of deep learning-based SoC, SoH estimation algorithms in a simulated data set. A well-designed control algorithm for active cell balancing presents a holistic and effective approach to optimise the performance, reliability, and lifespan of Li-ion batteries.

Understanding the impact of porosity on Li-ion diffusion enhancement in micro-sized silicon particles for advanced batteries

Lithium-ion batteries (LIBs) require advanced and practical anode materials, such as porous silicon (PSi), which can meet these expectations due to their rapid Li-ion diffusion rates and structural relaxation. Several studies have focused on the structural design of PSi or its composites to improve Li-ion diffusion; however, no systematic and quantitative evaluations of the impact of porosity on Li-ion diffusion and battery performance have been reported. Therefore, to understand the impact of porosity on Li-ion diffusion, we developed micro-sized porous silicon (m-PSi) particles with various porosities via metal-assisted chemical etching (MACE) method using different concentrations of AgNO3 (0.02–0.08 M). Among the as-prepared samples, m-PSi-0.06 (prepared using 0.06 M AgNO3) with ∼70 % porosity achieved a maximum Li-ion diffusion rate of 2.35 × 10−9 cm2 s−1. This led to a high-rate capability, enhanced Li-ion storage, and better cyclic retention of 61.4 % compared to the non-porous micro-sized Si (m-Si) (5.8 %) sample at a current density of 0.1 A g−1. Furthermore, the optimal porosity of m-PSi-0.06 resulted in an impressive rate capability of 760 mAh g−1 at a high current density of 4 A g−1 with a recovery rate of 80 %. The improved efficiency of m-PSi-0.06 is attributed to its optimized mesoporosity, which ensures sufficient space for Li-ion storage and shortens the effective transmission path to accelerate Li-ion diffusion. Moreover, the mesopores provide a greater number of active sites for the reversible adsorption of Li ions, thereby improving the capacitive behavior of the anode. In contrast, the highly nanoporous m-PSi-0.08, with a pore diameter of 1–3 nm, impeded Li-ion movement and restricted diffusion. These results reveal that a high nano porosity hinders Li-ion diffusion, whereas an optimal mesoporosity ensures swift diffusion in m-PSi anodes. These insights could guide the design of Si-based anode materials for advanced LIBs.

Advancements in Lithium-Ion Battery Technology

Lithium-ion (Li-ion) batteries are at the forefront of modern energy storage technologies due to their high energy density, long cycle life, and relatively low self-discharge rate. Recent advancements in materials science, battery management systems, and fabrication techniques have significantly improved the performance, safety, and sustainability of Li-ion batteries. This paper explores the latest developments in lithium-ion technology, including high-capacity anode and cathode materials, solid-state electrolytes, and next-generation designs, while also addressing the challenges and future directions for research and application.

Zwitterion assisted in-situ grain boundary coating on Li-rich cathode boosting electrochemical performance in Li-ion batteries

High-capacity and high-voltage Li-rich cathode materials are promising candidates for next-generation LIB cathodes due to their high energy density characteristics. However, they face challenges such as electrolyte side reactions at high voltages and slow kinetic properties. To overcome these challenges, this study proposed a one-pot Li2WO4 (LWO) grain boundary coating method. Additionally, a novel synthesis process utilizing zwitterions was introduced to uniformly position heavy tungsten on the surface of a cathode material. Through grain boundary coating, the cathode material was modified not only at the secondary particle level, but also between primary particles by filling grain boundaries with the coating compound. The synthesized LWO grain boundary coated Li-rich cathode exhibited significantly superior rate capability and cycle stability compared to the pristine material. Furthermore, it demonstrated a more stable cycling behavior after high-temperature storage than pristine counterpart. This study presents a primary particle surface modification technique through grain boundary coating and a one-pot synthesis process leveraging zwitterions as a new driving force, providing a new perspective for enhancing the performance of Li-rich cathode materials.

First principles study of the electronic structure and Li-ion diffusion properties of co-doped LIFex-1MxPyNy-1O4 (M=Co/Mn, N[dbnd]S/Si) Li-ion battery cathode materials

In this work, a first-principles method based on density functional theory was systematically employed to investigate the stability, electronic properties, lithium-ion migration rates, and capacity-voltage curves of the LiFex-1MxPyNy-1O4 (M = Co/Mn, NS/Si) system. The results indicate that the lattice constants of the LiFex-1MxPyNy-1O4 (M = Co/Mn, NS/Si) system show little variation, and the system exhibits low formation and binding energies. Among the investigated systems, LFP-Mn/S demonstrates the best structural and thermodynamic stability. The bandgap of the doped systems decreases, leading to enhanced electronic conductivity. The LiFe0.875Co0.125P0.875Si0.125O4 and LiFe0.875Mn0.125P0.875Si0.125O4 systems remain semiconductors, while the LiFe0.875Co0.125P0.875S0.125O4 and LiFe0.875Mn0.125P0.875S0.125O4 systems exhibit semi-metallic properties due to the introduction of sulfur. Differential charge density calculations reveal changes in the covalent bond strength of the doped systems, with the introduction of Si and S respectively increasing and decreasing the covalency of their bonds with surrounding oxygen atoms. Additionally, doping reduces the Li-ion diffusion energy barriers, with the LiFe0.875Co0.125P0.875Si0.125O4 system exhibiting the lowest migration energy barrier. The Li-ion diffusion rate is four orders of magnitude faster than that of the intrinsic system. This is attributed to changes in the average lengths of Li–O, Co–O, and Fe–O bonds. Finally, doping also alters the de-lithiation voltage, with values ranging from 2.69 V to 3.65 V for the doped systems, and the LiFe0.875Co0.125P0.875Si0.125O4 system shows the highest complete de-lithiation voltage of 3.65 V. The overall performance improvements of the doped system have significant implications for enhancing the performance of Li-ion batteries.

Active Cell Balancing Approach for Efficient Battery Management System

With the increasing concern for EV and its battery management system, the effective life and performance of li-ion battery is of utmost importance. The battery cells should be frequently equalized in order to increase the lifetime of battery pack. The conventional method of cell balancing is passive cell balancing where excess energy from cell is dissipated in the form of heat until all the cells are equally charged, causing thermal issues and efficiency in the battery pack. This paper proposes a novel approach for improving the efficiency of battery management systems through active cell balancing using the Kalman filter algorithm thereby overcoming the drawbacks of passive cell balancing. The goal of this paper is to develop a system that can extend the lifespan of batteries by ensuring that each cell is charged and discharged evenly. The proposed system includes an active balancing circuit that uses the Kalman filter algorithm to estimate the state of each battery cell and determine the optimal charging and discharging currents.

Numerical and experimental investigations on thermal performance of Li-ion battery during explosion

Electric vehicles (EVs) are eco-friendly alternative to internal combustion (IC) engine based vehicles to combat with global warming. Lithium-ion batteries (LIBs) are adopted in EVs and their performance and longevity depends on thermal environment. Inadequate thermal management results in suboptimal performance, thermal runaway and consequent explosion in extreme cases. The present study delves into the experimental investigation on catastrophic failure of a Lithium ion cell under abusive conditions. The temperature variations leading up to the point of explosion were meticulously monitored, revealing a critical temperature of 440 K just before the explosion. The pressure waves during the explosion gives the sound pressure levels from 46.2 dB to 83.85 dB within a 34 ms time window and the predominant portion of sound generated during the explosion lies in the range of 129 to 3488 Hz. The battery pack discharge experiments show a temperature rises above the critical limit of 313.15 K and sudden voltage drops to the cut of value of 20 V at t = 850 s during 1C discharge condition, which shows the warning of explosion. Numerical model was developed to simulate the complex conjugate heat transfer in the cell and simulation results are validated. To underscore the practical implications, a case study of fire accident during battery cooling experiment was presented. From the insights gained by explosion of single-cell and fire accident of battery, several recommendations are provided, which includes the orientation of cells within the EVs aiming at the safety of battery design and operation.

Enhanced Li-ion battery performance based on multisite oxygen vacancies in WO3-x@rGO negative electrode

While transition-metal oxides have emerged as promising candidates for lithium energy storage, several issues are remained to be addressed such as low conductivity, rate performance, and recyclability. In this study, a three-dimensional interconnected sheet-like heterostructure of WO3-x coated with reduced graphene oxide (rGO) was synthesized using the hydrothermal method. This structure significantly enhanced the conductivity of WO3-x. By combining the heterojunction with oxygen vacancies (OV), the active sites are enlarged, promoting the effective movement of ions and electrons at the interface between the WO3-x and rGO. The prepared anode exhibits a high specific capacity of 1202.6 mAh/g at 0.1 A g−1, with a cycling retention rate of 96 % after 100 cycles. Meanwhile, even at 5 A g−1, it still maintains a capacity of 305 mAh/g after 500 cycles. Theoretical calculations reveal that the presence of the composite heterogeneous structure enables WO3-x@rGO to possess appropriate adsorption energy, lower work function, and reduced barriers. This arrangement provides abundant active sites, promoting the rapid penetration of the electrolyte and enhancing the interface reaction kinetics, which is consistent with the experimental results. This study offers a new strategy for Li-ion anode materials.

Climate-adaptive battery solutions for renewable microgrids: A case study in Indian coastal and inland regions

The utilization of renewable energy has the potential to alleviate global warming, reduce carbon emissions in the environment, and offer sustainable energy solutions to remote regions. Presently, 13 % of the worldwide population resides in isolated inland and coastal areas where electricity remains inaccessible. Consequently, implementing microgrids powered by renewable energy sources becomes essential to enhance electricity accessibility in these remote locations. This study aims to identify efficient and cost-effective renewable energy technologies suitable for deployment inland and coastal areas. The techno-economic feasibility of renewable energy systems is being evaluated in two distinct locations: Yadavole (inland) and Uppada (coastal) villages in the Indian state of Andhra Pradesh. The energy analysis encompasses various sources, including photovoltaic, diesel generators, wind turbines, flywheels, and batteries (Li-ion and lead-acid). The HOMER software conducts all necessary modeling and simulations for economic analysis and optimal system sizing. According to the simulation results, the most viable microgrid configurations for the inland region, Yadavole, are photovoltaic/diesel and generator/Li-ion. In contrast, for the coastal region, Uppada, photovoltaic/diesel, and generator/lead-acid configurations prove to be the most promising configurations. Moreover, a MATLAB model of the proposed system is created to analyze energy quality. Given the superior performance of Li-ion batteries in elevated temperatures typically found inland, this study recommends a diversified range of battery solutions. Specifically, Li-ion batteries are recommended for inland areas, while lead-acid batteries are recommended for coastal regions. This approach aims to efficiently store renewable power by the specific climatic conditions of each area. It is crucial to systematically analyze region-specific renewable energy technologies to provide valuable insight to stakeholders involved in investment and energy policy decisions.

Numerical investigation on thermal management performance of soft packing Li-ion batteries with oblique multi-channel cold plates

During the driving process of electric vehicles (EVs), the continuous high-rate discharge of the power battery causes significant heat accumulation. An efficient battery thermal management system (BTMS) is critical for the safe and stable operation of EVs. In this study, an oblique channel cold plate (OCCP) is designed based on the traditional straight channel cold plate (SCCP) in order to addresses the problem of excessive and uneven temperatures during the high-rate discharge of soft packing lithium-ion batteries. Effects of glycol solution concentration, coolant mass flow rate, coolant inlet temperature, oblique angle for cooling channel, ambient temperature and discharge rate for the cell on the performance characteristics of BTMS, including the cooling efficiency (φ) and pressure drop (ΔP), are analyzed numerically with Ansys Fluent software. The results show that the OCCP has better cooling performance and lower pressure loss than the SCCP. Based on the analysis with the orthogonal design method, when the glycol solution concentration is 20 %, the mass flow rate is 1.0 g/s, and the inlet temperature is 25 °C, the BTMS with SCCP could obtain the optimal performance, corresponding to that the maximum temperature (Tmax) of the battery is controlled at 32.056 °C, while the φ is 0.581, and the ΔP across the cold plate is 52.652 Pa. Furthermore, the cooling efficiency φ of the cold plate decreases with the increase in the oblique angle. When the ambient temperature is 35 °C, the OCCP with a 20° oblique angle provides the best cooling effect for the battery during a 10C discharge. This work is helpful for the design of liquid cold plates in BTMS under high-rate discharge conditions for power battery of EVs.

In-situ cladding PEDOT:PSS on V-doped NCA cathodes for optimized interface and high electrochemical performance of Li-ion battery

The LiNi0.8Co0.15Al0.05O2 (NCA) nickel-rich layered cathode material is widely used for Li-ion batteries because of its excellent structural stability and high specific capacity. However, the Li/Ni mixing effect and the generation of interfacial secondary reactions in NCA cathode materials reduce the electrochemical properties of Li-ion batteries. Herein, we report a series of vanadium (V)-doped NCA cathode (VNCA) materials with different amounts of poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) polymers in-situ coated on the surface using a liquid-phase method. The introduction of PEDOT:PSS coating not only improves the conductivity of NCA cathode materials but also protects the surface of cathode materials from cracking during the cycle. Electrochemical results show that the PEDOT:PSS (2 wt%) coating possesses high capacity retention rate (83.58%) after 200 cycles at 1 C, which is better than that of the sample without coating (66.7%). The PEDOT:PSS (2 wt%) coated cathode materials also display superior rate performance to VNCA at high magnification. This work provides new methods and theoretical guidance for the development of efficient ternary cathode materials for Li-ion batteries.

KOH-activated hard carbon spheres with enhanced pseudo-capacitance for superior low-temperature electrochemical performance of Li-ion batteries

KOH-activated hard carbon spheres with enhanced pseudo-capacitance for superior low-temperature electrochemical performance of Li-ion batteries

Improved Wide Temperature and Rate Performance in Li-Ion Batteries with Fluorinated Electrolyte Solvents

Commercial electrolytes include organic solvents unable to withstand the conditions required for the rapidly growing Li-ion battery industry, such as extreme temperatures and charge rates. The thermal and electrochemical stability limits of these solvents restrict the development of Li-ion batteries needed to sustain automotive electrification and other industrial applications. Further efforts are needed to enable electrolyte formulations suited for the operational demands in the market.Koura has designed a series of fluorinated materials for use in Li-ion electrolytes that demonstrate improved performance and safety over conventional commercial electrolytes. The impact of Koura’s fluorinated solvents on performance in 4.3V Gr/NMC811 was examined, with a particular focus on benefits seen on extreme temperature and rate performance. Testing included cycling and rate performance across a range of temperatures from -20 °C to 45 °C and cycling conditions from C/2 to 4C. It has been found that these materials improve low temperature performance and reduce gassing and increase capacity retention during high-temperature and fast charge cycling. Where appropriate, performance of Koura materials is compared to common commercial solvents.To elucidate the mechanisms responsible for the observed improvements, comprehensive post-test analysis has been conducted, including gas composition analysis and quantification via gas chromatography, bulk electrolyte composition analysis via NMR spectroscopy, and surface layer characterization via XPS and SEM. Bulk transport properties of the materials and electrolytes, including conductivity, viscosity, and Li+ solvation, are correlated to performance benefits.This presentation will show Koura’s efforts to fill a major gap in the demands of the Li-ion battery industry today through the design of fluorinated materials and optimization of advanced electrolyte formulations. Specifically, we will present data highlighting the performance of fluorinated compounds on improving battery performance under strenuous conditions with respect to both temperature and cycling rate. Results from fundamental mechanistic studies will be discussed to highlight the mechanisms underlying the observed performance improvements.

Using Micrometer Scale X-Ray CT and Pore Network Modeling to Assess High-Energy Bi-Layer Li-Ion Battery Cathode Structures

The optimization of cathode pore space is pivotal for enhancing the rate capability of lithium-ion battery electrodes. Previous studies on simulated cathodes have highlighted the importance of achieving an optimal porosity gradient, with a gradual increase from the current collector side to the separator side to accommodate the growing demand for ion transport in that direction [1]–[3]. In this research, we address this requirement by introducing and investigating bi-layer NCM 811 cathodes. These cathodes consist of a slurry-coated dense bottom layer and a spray-coated highly porous top layer with varying relative thickness to approximate the desired porosity gradient. Employing Micrometer-scale X-ray CT characterization and pore network modeling, we evaluate the structural features, demonstrating the effectiveness of the design, and quantify essential parameters such as porosity and tortuosity. Furthermore, the cathodes are integrated into lithium anode half-cells and subjected to electrochemical cycling at different rates to assess ion transport and rate capability. Our findings reveal that to achieve the highest discharge spatial energy density above 1C for cathodes approximately 100μm thick, the compressed bottom layer with 30% porosity should have a thickness of 60μm, while the highly porous top layer with around 47% porosity should be 40μm thick.Reference:[1] A. Shodiev et al., “Deconvoluting the benefits of porosity distribution in layered electrodes on the electrochemical performance of Li-ion batteries,” Energy Storage Mater., vol. 47, pp. 462–471, May 2022, doi: 10.1016/j.ensm.2022.01.058.[2] X. Lu et al., “3D microstructure design of lithium-ion battery electrodes assisted by X-ray nano-computed tomography and modelling,” Nat. Commun., vol. 11, no. 1, p. 2079, Apr. 2020, doi: 10.1038/s41467-020-15811-x.[3] K. Song, C. Zhang, N. Hu, X. Wu, and L. Zhang, “High performance thick cathodes enabled by gradient porosity,” Electrochimica Acta, vol. 377, p. 138105, May 2021, doi: 10.1016/j.electacta.2021.138105.