Performance Of Li-ion Batteries Research Articles

Correction: Enhanced cycle performance of Li ion battery by graphene sheets covering with SnO@SnO2 anode materials

Correction: Enhanced cycle performance of Li ion battery by graphene sheets covering with SnO@SnO2 anode materials

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

Experimental Validation of Electrothermal and Aging Parameter Identification for Lithium-Ion Batteries

Modeling and predicting the long-term performance of Li-ion batteries is crucial for the effective design and efficient operation of integrated energy systems. In this paper, we introduce a comprehensive semi-empirical model for Li-ion cells, capturing electrothermal and aging features. This model replicates the evolution of cell voltage, capacity, and internal resistance, in relation to the cell actual operating conditions, and estimates the ongoing degradation in capacity and internal resistance due to the battery use. Thus, the model articulates into two sub-models, an electrothermal one, describing the battery voltage, and an aging one, computing the ongoing degradation. We first propose an approach to identify the parameters of both sub-models. Then, we validate the identification procedure and the accuracy of the electrothermal and aging models through an experimental campaign, also comprising two real cycle load tests at different temperatures, in which real measurements collected from real Li-ion cells are used. The overall model demonstrates good performances in simulating battery characteristics and forecasting degradation. The results show a Mean Absolute Percentage Error (MAPE) lower than 1% for battery voltage and capacity, and a maximum absolute error on internal resistance that is on par with the most up-to-date empirical models. The proposed approach is therefore well-suited for implementation in system modeling, and can be employed as an informative tool for enhancing battery design and operational strategies.

Synergistic boost in Fe3O4 anode performance for li-ion batteries via Zn and Cu double doping and multi-walled carbon nanotube composite integration

In this study, a novel nanocomposite material comprising pure Fe3O4 (FO), doped Zn0.5Cu0.5Fe2O4-3 (ZCFO-3), and Zn0.5Cu0.5Fe2O4-3@ Multi-walled carbon nanotube (ZCFO-3@MWCNT) nanocomposite material is carefully prepared using a simple one-step hydrothermal process. Comprehensive surface and morphological analysis are conducted using X-ray diffraction (XRD), Field emission scanning electron microscopy (FESEM), and High-resolution transmission electron microscopy (HRTEM), while compositional studies are investigated through Raman spectroscopy and X-ray photoelectron spectroscopy (XPS). The electrochemical performance is fully analyzed through Cyclic voltammetry (CV), Electrochemical impedance spectroscopy (EIS), rate capability tests, discharge/charge capacity, and cyclic stability evaluations. Among these three nanomaterials, ZCFO-3@MWCNT nanocomposite at 100 mA g−1 current density reveals the best performance, with a discharge capacity of 1974 mAh g–1, ZCFO-3 and FO reveal 1340 mAh g–1 and 1317 mAh g–1 respectively. After 800 cycles at 500 mA g−1 current density, ZCFO-3@MWCNT stays strong with a discharge capacity of 646 mAh g–1, while ZCFO-3 manages only 362 mAh g–1 and FO only 111 mAh g–1. After 1200 cycles at 500 mA g−1, the nanocomposite still delivers 518 mAh g–1. This study suggests that ZCFO-3@MWCNT could be a promising anode material for lithium-ion batteries.

Enhanced cycle performance of Li ion battery by graphene sheets covering with SnO@SnO2 anode materials

Enhanced cycle performance of Li ion battery by graphene sheets covering with SnO@SnO2 anode materials

Lithium fluorosulfonate-induced low-resistance interphase boosting low-temperature performance of commercial graphite/LiFePO4 pouch batteries

The performance of Li-ion batteries (LIBs) at sub-ambient temperatures is limited by the resistive interphases due to electrolyte decomposition, particularly on the anode surface. In this study, lithium fluorosulfonate (LFS) was added to commercial electrolytes to enhance the low-temperature electrochemical performance of LiFePO4 (LFP)/graphite (Gr) pouch cells. The addition of LFS significantly reduced the charge transfer resistance of the anode, substantially extending the cycle life and discharge capacity of commercial LFP/Gr pouch cells at −10 and −30 °C. Compared with the capacity retention rate of the baseline electrolyte at −10 °C (80 % after 25cycles), the capacity retention rate of the LFS electrolyte after 100 cycles under 0.5 C/0.5 C was retained at 94 %. Further mechanistic studies showed that the LFS additive induced the formation of a solid electrolyte interphase (SEI) film comprising inorganic-rich LiF, Li2SO4, and additional organic fluorides and sulfides to maintain good stability at the Gr/electrolyte interface during low-temperature operation. LFS suppressed electrolyte decomposition by forming a robust and low-resistance SEI film on the anode. These results demonstrate that LFS is a promising electrolyte additive for low-temperature LFP/Gr pouch cells.

Revisiting the Effect of Natural and Artificial Graphite on the Performance of Ni-rich Li-ion Batteries at Coin and Cylindrical Cells

Abstract We conducted a detailed evaluation of the electrochemical performance of artificial graphite (AG) and natural graphite (NG) from four leading global companies: AG-1, AG-2, AG-3, and NG-4 towards Ni-rich Li-ion batteries. We found that AG-2, an artificial graphite variant, demonstrated superior performance with exceptional capacity, rapid charging capabilities, and impressive capacity retention. AG-2 achieved a specific capacity of 338.97 mAh/g, outperforming AG-1 (321.16 mAh/g), AG-3 (314.43 mAh/g), and NG-1 (328.08 mAh/g). This superiority was further confirmed by high C-rate tests ranging from 2C to 5C. Notably, after 500 cycles, AG-2 maintained 91.18% of its initial capacity, significantly surpassing AG-1 (89.44%), AG-3 (78.78%), and NG-1 (84.16%). The study attributes AG-2's exceptional performance to its refined properties such as smaller particle size, fewer graphite imperfections, and a higher 2H phase content. These characteristics lead to increased active material in the anode, enhancing battery capacity, and to less material degradation over time, ensuring consistent capacity retention. Overall, AG-2 stands out as a highly efficient and cost-effective option for lithium-ion battery applications, eclipsing other commercial graphite alternatives.

Mg-Composition Dependent Cycle Stability in Zn<sub>1-x</sub>Mg<sub>x</sub>O Li-ion Battery: Transition from Electronic Transport-Limited to Ionic Transport Limited Cycles

This study explores Mg-composition dependent cycle stability in a Zn<sub>1-x</sub>Mg<sub>x</sub>O Li-ion battery, where battery cycles transition from an electronic transport-limited to an ionic transport limited regime. We investigated the impact of Mg doping in Zn<sub>1-x</sub>Mg<sub>x</sub>O nanocrystals on Li-ion battery performance, focusing on Mg compositions between x=0.05 and x=0.15. Mg composition dependent structural and electrical properties were explored using field effect transistors (FETs) and various microscopic/spectroscopic methods. The electronic conductivity was found to be sensitive to changes in Mg composition. Consistently, the initial capacity decreased with an increase in Mg composition, aligning with the reduction in electronic conductivity due to Mg doping. However, with successive cycles, the capacity became independent of the electronic conductivity, an outcome attributed to the formation of a solid-electrolyte interphase (SEI) and the conversion reactions. Initially, Mg doping reduces electronic conductivity due to increased carrier trapping, leading to lower discharge capacity. However, as cycling progresses, the impact of Mg doping diminishes. The formation of the SEI layer becomes more influential, significantly affecting Li-ion transport. Over time, factors like SEI formation, conversion reaction dynamics, and structural changes within the electrode start to dominate the battery's capacity, rather than the initial electronic conductivity influenced by Mg doping. This understanding can guide the development of materials with lower resistance, facilitating faster charging and discharging rates. More importantly, this study indicates that the initial capacity is closely tied to the conductivity of the Zn<sub>1-x</sub>Mg<sub>x</sub>O material.

Unveiling potential of thiophene-functionalized C3N3 nanosheet as an anode for Li-ion batteries: A DFT-D3 study

Covalent triazine frameworks (CTFs) are a fascinating type of porous organic materials that exhibit numerous distinct features, such as significant specific surface area, outstanding chemical/thermal stability, and structural modifiability at the molecular level. These features make CTFs highly appealing for utilization in Li-ion batteries (LIBs). However, their low electronic conductivity limits their practical applications. In the present study, the potential anode application of thiophene-functionalized C3N3 nanosheet for LIBs was conducted by dispersion-corrected density functional theory (DFT-D3) calculations. It was found that functionalization of the C3N3 nanosheet with six thiophene groups ((THP)6@C3N3) led to the highest reduction (0.19 eV) in the energy gap of the pristine C3N3 nanosheet. A single Li-ion preferably adsorbs between two nitrogen atoms of the triazine ring with an adsorption energy of about 4.59 eV. The absorption of Li-ion resulted in a reduction of the band gap from 1.37 eV to 0.43 eV, indicating enhanced electrical conductivity and superior cycle stability. The fully loaded functionalized nanosheet with nineteen Li-ions at various adsorption sites exhibited a remarkable theoretical specific capacity of 526.55 mAh/g. This configuration also displayed a low open-circuit voltage (0.09 V) and diffusion energy barrier (0.35 eV), ideal as an anode with a rapid charging/discharging rate. Therefore, thiophene-functionalized C3N3 nanosheet demonstrates superior anode performance for LIBs due to its high theoretical specific capacity, small diffusion barrier, and low working voltage. This work can provide insights for the refere development of CTF-based anode materials.

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

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.

Analysis of Trace Impurities in Lithium Carbonate.

Lithium carbonate (Li2CO3) is a critical raw material in cathode material production, a core of Li-ion battery manufacturing. The quality of this material significantly influences its market value, with impurities potentially affecting Li-ion battery performance and longevity. While the importance of impurity analysis is acknowledged by suppliers and manufacturers of battery materials, reports on elemental analysis of trace impurities in Li2CO3 salt are scarce. This study aims to establish and validate an analytical methodology for detecting and quantifying trace impurities in Li2CO3 salt. Various analytical techniques, including X-ray diffraction (XRD), scanning electron microscopy-energy-dispersive X-ray spectroscopy (SEM-EDX), X-ray photoelectron spectroscopy (XPS), and inductively coupled plasma optical emission spectroscopy (ICP-OES), were employed to analyze synthetic and processed lithium salt. X-ray diffraction patterns of Li2CO3 were collected via step-scanning mode in the 5-80° 2θ range. SEM-EDX was utilized for particle morphology and quantitative impurity analysis, with samples localized on copper tape. XPS equipped with a hemispherical electron analyzer was employed to analyze the surface composition of the salt. For ICP-OES analysis, a known amount of lithium salt was subjected to acid digestion and dilution with ultrapure water. Multielemental standard solutions were prepared, including elements such as Al, Cd, Cu, Fe, Mn, Ni, Pb, Si, Zn, Ca, K, Mg, Na, and S. Results confirmed the presence of the zabuyelite phase in XRD analysis, corresponding to the natural form of lithium carbonate. SEM-EDX mapping revealed impurities of Si and Al, with low relative quantification values of 0.12% and 0.14%, respectively. XPS identified eight potential impurity elements, including S, Cr, Fe, Cl, F, Zn, Mg, and Na, alongside Li, O, and C. Regarding ICP-OES analysis, performance parameters such as linearity, limit of detection (LOD), and quantification (LOQ), variance, and recovery were evaluated for analytical validation. ICP-OES results demonstrated high linearity (>0.99), with LOD and LOQ values ranging from 0.001 to 0.800 ppm and 0.003 to 1.1 ppm, respectively, for different elements. The recovery rate exceeded 90%. In conclusion, the precision of the new ICP-OES methodology renders it suitable for identifying and characterizing Li2CO3 impurities. It can effectively complement solid-state techniques such as XRD, SEM-EDX, and XPS.

Multi-interest adaptive unscented Kalman filter based on improved matrix decomposition methods for lithium-ion battery state of charge estimation

Accurately predicting the state of charge (SOC) is crucial to improving Li-ion battery performance. However, available model-based estimation approaches still face challenges in handling model uncertainty and measurement noise effects on parameter identification. Besides, the widely used unscented Kalman filter (UKF) algorithm has limitations in electric vehicles as it requires the error covariance matrix to maintain positive definiteness, limiting its applicability under certain conditions. This study introduces the bias-compensated forgetting factor recursive least squares (BCFFRLS) method for parameter estimation within the second-order RC equivalent circuit model specific to the INR18650-20R battery. Furthermore, we propose a novel algorithm named the optimization multi-interest adaptive unscented Kalman filter (O-MIAUKF). This algorithm is designed to address stability and robustness issues with traditional UKF encounters in dynamic environments. Experimental validation demonstrates that the O-MIAUKF algorithm excels in maintaining strong stability and robustness in various working conditions, accurately estimating SOC even with a non-positive covariance matrix. The SOC estimation error remains stable at 0.8 %, which is lower than that of the current Extended Kalman Filter (EKF), UKF, and Dual Extended Kalman Filter (DEKF).

Electrolyte Dependence of Li+ Transport Mechanisms in Small Molecule Solvents from Classical Molecular Dynamics.

As demands on Li-ion battery performance increase, the need for electrolytes with high ionic conductivity and a high Li+ transference number (tLi) becomes crucial to boost power density. Unfortunately, tLi in liquid electrolytes is typically <0.5 due to Li+ migrating via a vehicular mechanism, whereby Li+ diffuses along with its solvation shell, making its diffusivity slower than the counteranion. Designing liquid electrolytes where the Li+ ion diffuses independently of its solvation shell is of significant interest to enhance the transference number. In this work, we elucidate how the properties of the solvent influence the Li+ transport mechanism. Using classical molecular dynamics simulations, we find that a vehicular mechanism can be increasingly preferred with a decreasing solvent viscosity and increasing interaction energy between the solvent and Li+. Thus, a weaker interaction energy can enhance tLi through a solvent-exchange mechanism, ultimately improving Li-ion battery performance. Finally, metadynamics simulations show that in electrolytes where a solvent-exchange mechanism is preferable, the energy barrier to changing the coordination environment of Li+ is much lower than in electrolytes where a vehicular mechanism dominates.

Understanding solid electrolyte interface formation on graphite and silicon anodes in lithium-ion batteries: Exploring the role of fluoroethylene carbonate

This study explores how fluoroethylene carbonate (FEC) influences the solid electrolyte interface (SEI) layer formation during battery cycling process. FEC improves SEI properties, producing a uniform, chemically stable layer enriched with lithium fluoride. This enhances mechanical resilience and electrochemical stability. FEC also suppresses electrolyte deformation and decomposition, maintaining its initial state. The findings highlight the significance and comprehension of electrolyte additives, offering an electrolyte research pathway for improving Li-ion battery performance and durability.

Separator with active coating for fast and stable Li-ion batteries

Li-ion batteries are widely used in various applications, but their performance is limited by the stability and capacity of the separator. Developing a separator that can prevent thermal runaway and provide additional capacity is a significant challenge in battery research. In this study, a novel method of applying a Lithium titanate (LTO) active coating on the separator of Li-ion batteries is proposed. The LTO active coating can participate in electrochemical reactions and provide additional capacity. The active coating also improves the separator stability by preventing thermal shrinkage and enhancing thermal stability. The active coating has little impact on the Li-ion diffusion, and enables fast and stable battery performance at high C rates. The separator with active coating exhibits the highest ionic conductivity of 1.45 mS/cm, the lowest thermal shrinkage of 1.1% at 160 °C, and the highest capacity of 80.2 mAh/g at 15 C among the tested separators. This method offers a simple and effective way to enhance the performance of Li-ion batteries.

Thermally stable poly-aromatic solid electrolyte coated polyethylene membrane as high-performance lithium-ion battery separator

Improving the dimensional stability and electrolyte wettability of polyolefin separators is crucial to enhancing the safety and performance of power lithium-ion batteries (LIBs). In this work, composited separators that significantly improve both thermal stability and solvent wettability are prepared by coating polyaromatic solid electrolyte (sulfonated poly(aryl ether ketone), SPAEK) onto the surface of commercial polyethylene (PE) separators. Interestingly, the coating layer formed by SPAEK with a 60% sulfonation degree exhibits abundant porous structure owing to the polar sulfonic group inducing a retarded phase separation process. The polyelectrolyte coating layer enables both super-electrolyte affinity and higher electrolyte uptake of the composite separator. Moreover, the composited separator presents much better comprehensive properties, including thermal stability and ionic conductivity. As a result, the SPAEK-coated composite separator assembles LiNi0.83Co0.11Mn0.06O2 (NCM811)/Li battery exhibits a higher capacity retention rate of 84.01% at 2 C with a specific capacity of 151.25 mAh g−1 after 200 cycles. Hence, this modified separator is a potential material that facilitates high performance and safety for Li-ion batteries.

Electrochemical Removal of HF from Carbonate-based LiPF6-containing Li-ion Battery Electrolytes

Due to the hydrolytic instability of LiPF6 in carbonate-based solvents, HF is a typical impurity in Li-ion battery electrolytes. HF significantly influences the performance of Li-ion batteries, for example by impacting the formation of the solid electrolyte interphase at the anode and by affecting transition metal dissolution at the cathode. Additionally, HF complicates studying fundamental interfacial electrochemistry of Li-ion battery electrolytes, such as direct anion reduction, because it is electrocatalytically relatively unstable, resulting in a LiF passivation layer. Methods to selectively remove ppm levels of HF from LiPF6-containing carbonate-based electrolytes are limited. We introduce and benchmark a simple yet efficient electrochemical method to selectively remove ppm amounts of HF from LiPF6-containing carbonate-based electrolytes. The basic idea is the application of a suitable potential to a high surface-area metallic electrode upon which only HF reacts (electrocatalytically) while all other electrolyte components are unaffected under the respective conditions.