Performance Of Li-ion Batteries Research Articles

Finite Element Approach for Rheological Behavior in Colloidal Electrolytes in Lithium-Ion Battery Performance.

The main implication of articulating electrolyte performance is studying the energy density, charging aspects, formation of precipitates, thermal fluctuations during charging-discharging, and safety of batteries against fire or spark. One of the most significant aspects is the ability to design colloidal electrolytes that can enhance the overall performance of batteries along with dealing with all internal problems within a battery system. Through this optimization progression, the general performance and efficiency of Li-ion batteries can be improved. This work is presented in the study of the boundary value problem for rheological properties of colloidal electrolytes as a fourth grade fluid for lithium ion (Li-ion) batteries down a vertical cylinder. They have exceptional characteristics, such as low volatility and high thermal stability. The practical usage of the exact flow is restricted, as it involves very complicated integrals. The nonlinear problem that arises is solved by Galerkin's finite element approach based on the weighted-residual formulation, which is used to find the approximate solutions of the fourth-grade problem. This approach utilizes a piecewise linear approximation using linear Lagrange polynomials. Convergence of the solutions, which briefly describes the flow characteristics, includes the effects of the emerging parameters. The results obtained after implementation are not restrictive to small values of the flow parameters. Numerical studies have shown the superior accuracy and lesser computational cost of this scheme in comparison to collocation, the homotopy analysis method, and the homotopy perturbation method. The impact of the relevant parameters is examined through graphical results after implementation of a number of iterations.

Carbon coated Li3V2(PO4)3 derived from phytic acid with ultra-high rate performance for rechargeable Li ion batteries

The carbon coating strategy has great potential in improving the conductivity of Li3V2(PO4)3 (LVP). However, the preparation of carbon-coated LVP requires an additional carbon source and a complex synthesis process, such as the prereduction of V5+, which poses obstacles to large-scale production. In this article, the phytic acid, a kind of natural biological material with environmental benign and natural abundance, is directly chelated with V3+ and employed as both the phosphorus source and carbon source in the manufacturing procedure of LVP/C material for electrodes. The physical and electrochemical properties of LVP/C material may be tailored by carefully controlling the heat treatment temperature. This process leads to a remarkable boost in key performance metrics, including initial discharge capacity at 1 C (128.35 mAh·g-1), long cycle life at 10 C (115.75 mAh·g-1 after 1000 cycles), and rate capability at 50 C (101.83 mAh·g-1), all attributed to improved electronic conductivity and enhanced ion diffusion kinetics. The simple, novel, and energy-saving method demonstrates great potential for large-scale preparation for the high-performance cathode materials.

In-situ EIS for corrosion detection in LiFSI-based Li-ion batteries

LiFSI-based electrolytes are frontiers amongst candidates for future generation of high-voltage and high-temperature capable Li-ion batteries. Arguably, the biggest disadvantage of these electrolytes is their undesirable ability to corrode aluminium current collectors. Hence, suppressing the Al corrosion in such electrolytes has become a widely discussed topic. Despite that, there is a lack of studies focusing on in-situ approaches for the detection of such corrosion, even though such approaches are essential for the effective evaluation of the performance of Li-ion batteries containing novel LiFSI-based electrolytes. This work demonstrates the usage of EIS for the detection of corrosion of Al current collectors in NMC/Graphite cells containing 1.0 M LiFSI in EC:DMC (1:1, v/v). When cycled up to 4.2 V at 50 °C, cathode-side Nyquist plots displayed induction loops developing over the cycles, which were ascribed to the corrosion of Al current collectors, and whose presence was confirmed by SEM imaging. When the cut-off voltage was decreased to 3.7 V to maintain a native protective Al2O3 layer and hence suppress the corrosion, neither the induction loops in Nyquist plots nor pitting holes in SEM images were observed, confirming the link between the induction loops and the corrosion. This work aims to support designing and understanding of future experiments focused on suppressing the corrosion of Al current collectors in LiFSI-based high-voltage Li-ion batteries capable of operation at higher temperatures.

Unlocking enhanced new type of safe open system lithium-ion battery performance: Mn3O4 nano-cubes and their sulfur mixers cathode material

In the pursuit of advancing lithium-ion (Li-ion) battery technology towards enhanced safety and performance, we present research study on the synthesis and evaluation of manganese oxide-based cathode materials. Different phases of manganese oxides (Mn3O4 and MnO2), alongside their different ratio of two manganese oxides phases and Mn3O4 with sulfur (S) combination, we employed a simple hydrothermal and solid-state grinding techniques. Characterized by field emission transmission electron microscopy (FE-TEM), our synthesized materials revealed distinct phases of MnO2 and Mn3O4 accompanied by nanorods (NRs) and nanocubes (NCs) morphologies, respectively. We conducted a comprehensive assessment of the Li-ion battery performance of these materials, initially without S, within a new type of safe open system framework. Notably, Mn3O4 NCs (MNCs) developed as important, exhibiting a maximum discharge capacity of 346.03 mAh/g at a constant current discharging rate of 0.5 A/g. We introduced 30 % of S into 70 % of the MNCs matrix to form the MNCSs-73 composite, resulting in rather moderate enhancement in capacity performance. The MNCSs-73 displayed an exposed discharge capacity of approximately 394.8 mAh/g under identical testing conditions. Our findings underscore the exceptional potential of MNCs and MNCSs-73 composites cathode materials for highly suitable for open system novel safe Li-ion battery applications and other energy storage research field.

Recent Advancements in Battery Thermal Management Systems for Enhanced Performance of Li-Ion Batteries: A Comprehensive Review

Li-ion batteries are crucial for sustainable energy, powering electric vehicles, and supporting renewable energy storage systems for solar and wind power integration. Keeping these batteries at temperatures between 285 K and 310 K is crucial for optimal performance. This requires efficient battery thermal management systems (BTMS). Many studies, both numerical and experimental, have focused on improving BTMS efficiency. This paper presents a comprehensive review of the latest BTMS designs developed in 2023 and 2024, with a focus on recent advancements and innovations. The primary objective is to evaluate these new designs to identify key improvements and trends. This review categorizes BTMS designs into four cooling methods: air-cooling, liquid-cooling, phase change material (PCM)-cooling, and thermoelectric cooling. It provides a detailed analysis of each method. It also offers a unique examination of hybrid cooling BTMSs, classifying them based on their impact on the cooling process. A hybrid-cooling BTMS refers to a method that combines at least two of the four types of BTMS (air-cooling, liquid-cooling, PCM-cooling, and thermoelectric-cooling) to enhance thermal management efficiency. Unlike previous reviews, this study emphasizes the novelty of recent designs and the substantial results they achieve, offering significant insights and recommendations for future research and development in BTMS. By highlighting the latest innovations and providing an in-depth analysis, this paper serves as a valuable resource for researchers and engineers aiming to enhance battery performance and sustainability through advanced thermal management solutions.

Hydrothermal modification of natural graphite with KCl: different roles of K+ and Cl− in promoting the electrochemical performance of Li-ion batteries

Hydrothermal modification of natural graphite with KCl: different roles of K+ and Cl− in promoting the electrochemical performance of Li-ion batteries

LiF modified hard carbon from date seeds as an anode material for enhanced low-temperature lithium-ion batteries

The performance of traditional Li-ion batteries deteriorates when operating at sub-zero temperatures mainly due to the slow diffusion of Li-ions in commercial negative electrode materials. Various alternative anodes have been explored, but complex fabrication methods hinder practical implementation. This work proposes a cost-effective anode material, a porous structured nitrogen-doped hard carbon synthesized from date seeds with further LiF modification to achieve an artificial LiF-rich solid electrolyte interphase (SEI) layer. The resulting anode material showcases promising characteristics, achieving a specific capacity of 525 mAh g−1 after 50 cycles at room temperature. Furthermore, it maintains a substantial capacity of 280 mAh g−1 after 100 cycles at −20 °C. Notably, even when subjected to a high current of 2C at −20 °C, the electrode still provides a remarkable capacity of 72 mAh g−1 after 500 cycles. The outstanding charge storage performance at low temperatures is attributed to the predominance of capacitance-controlled charge storage mechanisms in the prepared anode. Post-mortem analysis confirms structural stability and formation of a uniform LiF-rich SEI layer. This novel approach presents a practical solution to the difficulties encountered by LIBs in cold environments, paving the way for improved battery performance and longevity.

Synthetic ester-based forced flow immersion cooling technique for fast discharging lithium-ion battery packs

Rapid advancements in Li-ion battery technology are being made to meet the growing demand for efficient energy storage solutions in electric vehicles and portable electronics. However, heat generation during rapid charging and discharging remains a significant challenge, as it can lead to overheating, fire, and explosion. To address this issue, battery thermal management systems require improvements in cooling strategies. This study aims to optimize the thermal performance of Li-ion battery packs during fast discharge operation by single-phase synthetic ester oil-based forced flow immersion cooling (FFIC) technique. The study analyzes the thermal performance of the FFIC of a 4S2P LIB pack based on various flow rates, pressure drops, and pump power consumption and compares it with various conventional cooling methods and dielectric fluids. The MSMD-based NTGK battery modeling approach is used to analyze the electrical and thermal characteristics of the battery pack at 3C discharge and environmental temperature of 25 °C. The simulation findings revealed that the synthetic ester oil has a superior cooling effect than mineral oil in the 4S2P Li-ion battery pack. The experimental results showed that the synthetic ester-based FFIC Li-ion battery pack achieves an optimal pack temperature of 31.3 °C and uniform temperature distribution at the flow rate of 5 L/min and pressure drop of 228.44 Pa. Moreover, FFIC reduces temperature rise by 51 % compared with natural air convection and 35 % compared with static flow immersion cooling (SFIC) in the 4S2P lithium-ion battery pack. Also, the practical significance of the SEO-based FFIC immersion cooling technique is assessed across extreme climate zones such as −10 °C and 40 °C and determined its superior performance in Li-ion batteries. Hence, this study proved that the FFIC technique is suitable for Li-ion batteries in electric vehicle applications in terms of optimal performance, reliability, and safety during high-current discharge operations.

Enhanced Electrochemical Performance and Cyclic Stability of Li-Ion Batteries by Employing Nanostructured Bi2Te3 Particles with Amorphous ZrO2 Nanocoating

Enhanced Electrochemical Performance and Cyclic Stability of Li-Ion Batteries by Employing Nanostructured Bi₂Te₃ Particles with Amorphous ZrO₂ Nanocoating

Relating state-of-charge to impedance and equivalent circuit parameters in lithium-ion cells: An experimental study

The wide-band impedance of Lithium-ion (Li-ion) batteries has become a focal point for researchers interested in State-of-Charge (SOC) estimation and battery modeling. However, the interplay between SOC, wide-band impedance, and model parameters has not been extensively explored. This paper addresses this gap by investigating how SOC impacts the impedance and Equivalent Circuit Model (ECM) parameters of a Li-ion battery cell through empirical measurements. The study utilizes discharge tests to vary the SOC and employs the Coulomb Counting Method (CCM) to estimate the approximate SOC from the response signals. A novel measurement technique is introduced and applied to determine a cell’s wide-band impedance at different SOC levels. This innovative approach uses a Pseudo-random Impulse Sequence (PRIS) perturbation signal to measure wide-band cell impedance. The collected impedance data is then used to estimate the ECM parameters. Experimental findings reveal an inverse relationship between impedance and SOC. Additionally, the ECM parameters exhibit significant correlation with SOC, particularly in mid- to low-frequency regions. This research highlights that SOC profoundly influences ECM parameters, offering valuable insights into the performance of Li-ion batteries under various conditions.

Preparation of SiO2 nanotubes and nanoparticles in the presence of L-tartaric acid by sol-gel method and their electrochemical performance for Li-ion batteries

Recently, SiO2 has attracted increasing attention as an anode material for lithium-ion batteries (LIBs) owing to its low cost and high theoretical specific capacity. However, its inherent poor conductivity limits its practical application. To address this issue, nanostructured material design is considered an effective solution. Herein, based on the traditional ammonium tartrate template-directed sol-gel method, we use low-cost and easily available L-tartaric acid in place of D, L-tartaric acid to prepare high-yield silica nanotubes (SNTs) with a thin wall (ca. 50 nm), small diameter (ca. 150 nm), rough surface and open ends, as well as tiny spongy-like silica nanoparticles (SNPs) by adjusting the feeding amount and feeding mode of NH4OH solution. The electrochemical characterization results suggest that the SNTs show better cyclability and rate performance than the SNPs, which maintain a reversible capacity of 741.3 mAh g−1 after 500 cycles at a current density of 0.4 A g−1 and deliver a high rate capacity of 819.4 mAh g−1 at a high current rate of 2 A g−1. The excellent electrochemical performance suggests that hollow one-dimensional hollow nanotubes are more efficient in improving the electrochemical performance of SiO2 than zero-dimensional nanoparticles, and SNTs with thin tube walls and rough surfaces are demonstrated to be fascinating and promising anode materials for LIBs.

Selection of Li-Ion Batteries Used On Electric Vehicles

The lithium-ion battery is one such energy source. Li-Ion batteries are widely used in EVs for three reasons: they are more energy efficient than conventional batteries, have a longer lifespan, and charge batteries more quickly. The following is a succinct description of the Li-Ion battery's operating principle: The battery's active component is the electrochemical cell, consisting of a cathode and an anode, which are separated and connected by an electrolyte. The primary function of the electrolyte is to facilitate the movement of ions. When the battery is discharged, lithium ions migrate from the anode through the electrolyte to the cathode, while the accompanying electron powers an electrical device. During the charging process, electrons travel from the cathode to the anode through the separator, while current flows from the anode to the cathode. The performance of Li-Ion batteries is primarily influenced by the materials used for the cathode and anode. Early in the nineteenth century, electric vehicles (EVs) using batteries were designed and manufactured. However, compared to fossil fuel cars, whose ingenuity and development outshone EVs, it lagged behind in producing high power. At the moment, internal combustion engines powered by fossil fuels are being phased out in favour of electrical motors for traction because of climate change. Zero CO2 emissions, development on materials has advanced significantly thanks to nanotechnology, and battery development is no exception. On the creation of nanostructured materials for electrodes used in li-ion batteries, several research studies have been described. To provide safe, sturdy, and trustworthy automotive vehicle systems, reliable systems are essential. The selection of Li-ion batteries for use in electric vehicles (EVs) holds significant research significance. Li-ion batteries are currently the preferred choice for EVs due to their high energy density, long cycle life, and relatively low self-discharge rate. However, there are several key research areas that contribute to the importance of battery selection: In this Research we will be using Weighted product method and Weighted sum method. Alternate Parameters taken as LCOB, LNMCOB, LMOB, LFPB, LTOB. Evaluation Parameters taken as Reliability, Safety, Specific power, Specific energy density, Price. The study that was done is briefly summarised in the following lines, along with a prediction of potential future actions. It discusses the evaluation process that was put together before going through the findings related to the utilisation of Li-NMC and Life P batteries in electric cars.

Resynthesis of Ni-rich lithium nickel manganese cobalt oxide cathode materials from the industrial leachate of spent Li-ion batteries: The effect of PF6− species from electrolyte

A significant rise in the generation of spent Li-ion batteries (LIBs) is expected due to the widespread usage of LIBs in various applications. The benefit of spent LIB valorization can be maximized by a high value-added recycling process. The resynthesis of cathode active materials (CAMs), a promising recycling method that directly produces CAMs from LIB leachate, is explored in this study. We resynthesize Ni-rich LiNi0.9Co0.05Mn0.05O2 (NCM955) CAMs via coprecipitation and sintering by varying the amount of PF6−, which can raise environmental concerns, in industrial LIB leachate. Our first employment of glow discharge mass spectrometer in the investigation of PF6− decomposition behavior reveals that the small amounts of PO43− are precipitated into NCM precursors and F− remains in the leachate during resynthesis process. The incorporation of PF6− species during the coprecipitation results in an enlargement of crystal lattice parameters. The incorporated PF6− species increases the ratio of Ni2+ to Ni3+ and leads to the formation of LixPOyFz on the surface of NCM, which exerts a positive effect on the overall LIB performance. This study is the first attempt where the effect of PF6− species from LIB electrolyte is investigated in the resynthesis of the state-of-the-art NCM955 from industrial LIB leachate.

Probing Particle-Carbon/Binder Degradation Behavior in Fatigued Layered Cathode Materials through Machine Learning Aided Diffraction Tomography.

Understanding how reaction heterogeneity impacts cathode materials during Li-ion battery (LIB) electrochemical cycling is pivotal for unraveling their electrochemical performance. Yet, experimentally verifying these reactions has proven to be a challenge. To address this, we employed scanning μ-XRD computed tomography to scrutinize Ni-rich layered LiNi0.6Co0.2Mn0.2O2 (NCM622) and Li-rich layered Li[Li0.2Ni0.2Mn0.6]O2 (LLNMO). By harnessing machine learning (ML) techniques, we scrutinized an extensive dataset of μ-XRD patterns, about 100,000 patterns per slice, to unveil the spatial distribution of crystalline structure and microstrain. Our experimental findings unequivocally reveal the distinct behavior of these materials. NCM622 exhibits structural degradation and lattice strain intricately linked to the size of secondary particles. Smaller particles and the surface of larger particles in contact with the carbon/binder matrix experience intensified structural fatigue after long-term cycling. Conversely, both the surface and bulk of LLNMO particles endure severe strain-induced structural degradation during high-voltage cycling, resulting in significant voltage decay and capacity fade. This work holds the potential to fine-tune the microstructure of advanced layered materials and manipulate composite electrode construction in order to enhance the performance of LIBs and beyond.

Probing Particle‐Carbon/Binder Degradation Behavior in Fatigued Layered Cathode Materials through Machine Learning Aided Diffraction Tomography

AbstractUnderstanding how reaction heterogeneity impacts cathode materials during Li‐ion battery (LIB) electrochemical cycling is pivotal for unraveling their electrochemical performance. Yet, experimentally verifying these reactions has proven to be a challenge. To address this, we employed scanning μ‐XRD computed tomography to scrutinize Ni‐rich layered LiNi0.6Co0.2Mn0.2O2 (NCM622) and Li‐rich layered Li[Li0.2Ni0.2Mn0.6]O2 (LLNMO). By harnessing machine learning (ML) techniques, we scrutinized an extensive dataset of μ‐XRD patterns, about 100,000 patterns per slice, to unveil the spatial distribution of crystalline structure and microstrain. Our experimental findings unequivocally reveal the distinct behavior of these materials. NCM622 exhibits structural degradation and lattice strain intricately linked to the size of secondary particles. Smaller particles and the surface of larger particles in contact with the carbon/binder matrix experience intensified structural fatigue after long‐term cycling. Conversely, both the surface and bulk of LLNMO particles endure severe strain‐induced structural degradation during high‐voltage cycling, resulting in significant voltage decay and capacity fade. This work holds the potential to fine‐tune the microstructure of advanced layered materials and manipulate composite electrode construction in order to enhance the performance of LIBs and beyond.

Solvation Structures and Transport Mechanisms of Cations in Water-in-Bisalt Electrolytes for High-Concentration Lithium-Ion Batteries Revealed by Molecular Dynamics Simulations.

The development of safe and cost-effective electrolytes for rechargeable batteries is currently underway. While water-based electrolytes hold promise, their restricted electrochemical stability window poses a challenge. Combining multiple ionic species emerges as a promising strategy to broaden this stability window and optimize Li-ion battery performance. This study focuses on dual-cation electrolytes, which blend lithium and potassium acetates to enhance the electrochemical characteristics of the solution at high concentrations. We investigated the solvation structure of each ion and its interactions on a molecular level. Our analysis reveals that ion clusters and aggregates are formed through shared acetate and water molecules at high salt concentrations. Furthermore, the residence time analyses of atom pairs indicate that cations diffuse in vehicular mode at low concentrations. In contrast, they switch to a structural mode at high concentrations due to diminishing water content. This study offers a comprehensive model for exploring diverse solvation structures of cations and gaining insights into their diffusion mechanisms within water-in-bisalt electrolytes for aqueous Li-ion batteries.

A DFT modeling of 4-cyclohexene-1,3-dione embedded in covalent triazine framework as a stable anode material for Li-ion batteries

Developing porous organic anode materials with outstanding electrical conductivity and high capacity is crucial to enhancing the performance of Li-ion batteries (LIBs). Herein, 4-cyclohexene-1,3-dione-functionalized covalent triazine framework (CYC-CTF0) monolayer as a new anode material in LIBs was explored through density functional theory calculations. The monolayer demonstrates good thermal, mechanical, and cycling stability and has a strong affinity for Li-ions to bind to the C=O and C=N redox-active sites. The adsorption of Li-ions transforms the CYC-CTF0 monolayer from being semiconducting to becoming metallic, reflecting its high electrical conductivity. Remarkably, the lattice undergoes a minimal expansion of 1.1 % throughout the charging and discharging process, suggesting an extended cycle life. The unit cell of the monolayer can be fully loaded with four Li-ions at different adsorption sites, exhibiting a specific theoretical capacity of 585.41 mAh g−1 and a low open-circuit voltage of 0.12 V. Moreover, the adsorbed Li-ions display a low diffusion energy barrier of 0.17 eV, enabling effective rates of charging and discharging. Our findings reveal the unique characteristics of the CYC-CTF0 monolayer as a promising anode material in LIBs.

The Li battery digital twin – Combining 4D modelling, electro-chemistry, neutron, and ion-beam techniques

Knowledge driven materials and component design is key for improving the performance of Li-ion batteries and solving the remaining hurdles for next-generation battery concepts like all-solid-state batteries. While the spatial and time dependent distribution of Li would help elucidating performance bottlenecks and degradation phenomena, only a few analysis techniques are available, due to the unique nature of Li, especially as Li+-ion. In fact, only two non-destructive techniques with good time resolution can combine spatial information with absolute quantification of Li, one being Neutron Depth Profiling (NDP), the other Ion-Beam-Analysis (IBA). While both exploit nuclear processes, the information gained is complementary. NDP provides high depth resolution, but only limited lateral resolution, whereas IBA has high lateral, but only limited depth resolution. In this study, we benchmark both techniques for the first time using a set of Li-battery test-samples and show the strengths and synergies of both techniques. The derived information regarding the depth dependent Li-concentration is then used to validate a microstructure resolved continuum model of charge, discharge, and relaxation behavior of the cells and electro-chemical analysis. This fundamental work demonstrates a new route to optimize Li batteries on material and component level by combining advanced characterization and digital twin modelling.

Weak Li-O bonds and small grains enable fast ion diffusion and electron transport for LiFePO4 cathode

The LiFePO4 material continue to suffer from poor rate performance. Nanosized LFP can improve rate performance; however, nanofabrication typically requires expensive organic matter and high-pressure-resistant equipment. The current widely used solid-phase sintering methods employ FePO4 as the precursor, but it is difficult to suppress grain growth. Here, we propose a W–Ti codoping strategy to suppress grain growth during sintering, thereby improving rate performance of Li-ion batteries. W and Ti doping shrinks grains during the sintering process and make the Li-O bond more ionized. Li0.36WO3 accumulates at grain boundaries, hindering grain boundary diffusion and inhibiting grain growth during sintering. The resulting material exhibits refined grains and suppressed polarization growth, resulting in improved rate performance while maintaining a specific capacity of 117 mAh g−1 at a rate of 10 C. After 1000 cycles at a rate of 1 C, 91.0 % of the initial capacity was retained. In summary, this research provides a method for large-scale production of LFP with excellent rate performance.

New Numerical Approach to Determine the Optimum Mixing Ratio of Electrode Materials for Maximum Li-ion Battery Performance by the Hierarchical Homogenization and Feedforward Neural Networks

New Numerical Approach to Determine the Optimum Mixing Ratio of Electrode Materials for Maximum Li-ion Battery Performance by the Hierarchical Homogenization and Feedforward Neural Networks