Lithium-ion Batteries Research Articles

Design and Preparation of Soluble Polyimide Binder With Random Copolymerized Rigid‐Flexible Segments for Lithium Ion Batteries

ABSTRACTBinders play a critical role in the preparation and operation of electrodes in lithium‐ion batteries (LIBs). Developing new binding materials with high affinity to Li ions and resistance to higher voltages was desirable for the practical applications of LIBs. In this work, soluble polyimide binder (PI) with random copolymerized rigid‐flexible segments were synthesized and evaluated as cathode binder for the typical lithium iron phosphate cathode material in terms of cycling performances, rate capability, and electrochemical impedance. By introducing the polar and soft ether segment into the rigid PI chains, the NMP‐soluble PI precursors were obtained. The rigid‐flexible segments in the PI binders work synergistically during the electrochemical process, in which the rigid segments of aromatic units with strong lithiophilic CO group provided the necessary mechanical support and affinity with electrolytes, while the flexible segments endow the high solubility and buffer effect to the volume change during the charge/discharge process. Moreover, the 3,5‐diaminobenzoic acid (DABA) working as the crosslinking unit was introduced during the synthesis and the addition ratios were optimized. The as‐optimized PI binders exhibited superior rate performances and comparable cycling stability when compared with the commercial PVDF binder, demonstrating the great potential for PI binder in the LIBs systems.

ControllableSynthesisof Heterogeneous ZnS/SnS2Encapsulated in Hollow Nitrogen-doped Carbon Microcubes as Anode for High-performance Li-ion Capacitors.

Li-ion capacitors (LICs) integrate the desirable features of lithium-ion batteries (LIBs) and supercapacitors (SCs), but the kinetic imbalance between the both electrodes leads to inferior electrochemical performance. Thus, constructing an advanced anode with outstanding rate capability and terrific redox kinetics is crucial to LICs. Herein, heterostructured ZnS/SnS2 nanosheets encapsulated into N-doped carbon microcubes (ZnS/SnS2@NC) are successfully fabricated. The sufficient ZnS/SnS2 heterostructure possesses abundant active sites, and the built-in electric field formed at the heterojunction interface can facilitate electron/ion migration. The interconnected hollow carbon layers could reduce the electron transfer resistance effectively and accommodate the volume expansion of SnS2, thereby maintaining the structural stability. Due to the synergy between multi-components, the ZnS/SnS2@NC anode demonstrates impressive Li storage performance with an excellent cyclic durablity (690 mAh g-1 at 0.5 A g-1 after 600 cycles) and considerable rate capability. Moreover, when matched with active carbon, the ZnS/SnS2@NC based LIC device delivers an admirable energy density of 134.1 Wh kg-1 and a high power output of 11,250 W kg-1, as well as remarkable capacity retention of 73.2% after 6,000 cycles at 1.0 A g-1. The experimental results demonstrate the significance of optimized heterointerface engineering toward construction of electrode materials with high-performance for Li storage.

A Joint Prediction of the State of Health and Remaining Useful Life of Lithium-Ion Batteries Based on Gaussian Process Regression and Long Short-Term Memory

To comprehensively evaluate the current and future aging states of lithium-ion batteries, namely their State of Health (SOH) and Remaining Useful Life (RUL), this paper proposes a joint prediction method based on Gaussian Process Regression (GPR) and Long Short-Term Memory (LSTM) networks. First, health features (HFs) are extracted from partial charging data. Subsequently, these features are fed into the GPR model for SOH estimation, generating SOH predictions. Finally, the estimated SOH values from the initial cycle to the prediction start point (SP) are input into the LSTM network in order to predict the future SOH trajectory, identify the End of Life (EOL), and infer the RUL. Validation on the Oxford Battery Degradation Dataset demonstrates that this method achieves high accuracy in both SOH estimation and RUL prediction. Furthermore, the proposed approach can directly utilize one or more health features without requiring dimensionality reduction or feature fusion. It also enables RUL prediction at the early stages of a battery’s lifecycle, providing an efficient and reliable solution for battery health management. However, this study is based on data from small-capacity batteries and does not yet encompass applications in large-capacity or high-temperature scenarios. Future work will focus on expanding the data scope and validating the model’s performance in real-world systems, driving its application in practical engineering scenarios.

The evolution of lithium-ion battery recycling

The evolution of lithium-ion battery recycling

High-Rate 4.2 V Solid-State Potassium Batteries by In Situ Polymerized Epoxide Ether Electrolyte.

Solid-state metallic potassium batteries (SSMPBs) afresh have attracted incremental attention because of their potential to supplement solid-state metallic lithium batteries. However, SSMPBs suffer poor electrochemical performances due to the low ionic conductivity of solid electrolytes and huge electrode/electrolyte interfacial resistance. Herein, high-rate SSMPBs are achieved by in situ ring-opening polymerization of 1,3-dioxolane with succinonitrile as a plasticizer and Al(OTf)3 as the catalyst, where the succinonitrile enables short-chain polyether electrolytes. The in situ polymerized electrolytes deliver a high ionic conductivity of 4.5 × 10-5 S cm-1 at room temperature and excellent stabilities at high oxidation potentials (4.2 V vs K+/K) and against metallic K anodes. All these result in SSMPBs with a discharge capacity of 69 mAh g-1 under a high rate of 100 mA g-1 and a retention of 88.8% after 100 cycles, and the rate and capacity retention are higher than those in previous work on SSMPBs.

Remaining Useful Life Prediction of Lithium-ion Battery based on AConvST-LSTM-Net-TL

Abstract The accurate prediction of the Remaining Useful Life (RUL) of lithium-ion batteries can significantly enhance the safety and reliability of these batteries, thereby reducing operational risks. However, numerous existing methodologies operate under the assumption that both training and testing data adhere to the same distribution pattern, hindering the application of successful laboratory-based models to different target batteries. Hence, this study introduces a transfer learning model for predicting lithium-ion battery life, utilizing an attention mechanism-driven convolutional neural network (ACNN) in conjunction with a spatiotemporal Long Short-Term Memory network (ST-LSTM). Initially, the deep charging process data is leveraged for battery capacity estimation, where a Generalized Additive Model (GAM) is employed to delineate the nonlinear trend of battery capacity decay and characterize the capacity degradation. Following feature extraction, the Maximum Mean Discrepancy (MMD) value is computed to assess the distribution disparity between the two domains. Subsequently, the AConvST-LSTM-Net computes capacity estimations, loss functions for both source and target domains, merging these with the MMD value to formulate a comprehensive loss function. In conclusion, by employing transfer learning, the refined model is adapted to the target domain dataset, enabling the accurate prediction of the RUL of lithium-ion batteries. This approach is validated using the NASA lithium-ion battery dataset and the National Big Data Alliance for New Energy Vehicles (NDANEV), demonstrating the superior accuracy and robustness of the AConvST-LSTM-Net-TL model in comparisn to other prediction methods.

Rational Electrolyte Design for Elevated-Temperature and Thermally Stable Lithium-Ion Batteries with Nickel-Rich Cathodes.

As the energy density of lithium-ion batteries (LIBs) increases, the shortened cycle life and the increased safety hazards of LIBs are drawing increasing concerns. To address such challenges, a series of localized high-concentration electrolytes (LHCEs) based on a solvating-solvent mixture of tetramethylene sulfone and trimethyl phosphate and a high flash-point diluent 1H,1H,5H-octafluoropentyl 1,1,2,2-tetrafluoroethyl ether were designed. The LHCEs exhibited nonflammability and greatly suppressed heat release at elevated temperatures, which would potentially improve the safety performance of the LIBs. Moreover, the optimal LHCE achieved capacity retentions of 87.1% and 81.7% in graphite||LiNi0.8Mn0.1Co0.1O2 cells after 500 cycles at 25 and 45 °C, respectively, which were significantly higher than the conventional electrolyte, whose capacity retentions were only 75.2% and 38.5% under the same conditions. Mechanistic studies revealed that the LHCE not only formed a more robust solid electrolyte interphase but also exhibited improved anodic stability, compared with the conventional electrolyte. This work sheds light on rational electrolyte design for high-energy density LIBs with high battery performance and low safety concerns.

Large-Scale Compatible Roll-to-Roll Coating of Paper Electrodes and Their Compatibility as Lithium-Ion Battery Anodes

A recyclability perspective is essential in the sustainable development of energy storage devices, such as lithium-ion batteries (LIBs), but the development of LIBs prioritizes battery capacity and energy density over recyclability, and hence, the recycling methods are complex and the recycling rate is low compared to other technologies. To improve this situation, the underlying battery design must be changed and the material choices need to be made with a sustainable mindset. A suitable and effective approach is to utilize bio-materials, such as paper and electrode composites made from graphite and cellulose, and adopt already existing recycling methods connected to the paper industry. To address this, we have developed a concept for fabricating fully disposable and resource-efficient paper-based electrodes with a large-scale roll-to-roll coating operation in which the conductive material is a nanographite and microcrystalline cellulose mixture coated on a paper separator. The overall best result was achieved with coated roll 08 with a coat weight of 12.83(22) g/m2 and after calendering, the highest density of 1.117(97) g/cm3, as well as the highest electrical conductivity with a resistivity of 0.1293(17) mΩ·m. We also verified the use of this concept as an anode in LIB half-cell coin cells, showing a specific capacity of 147 mAh/g, i.e., 40% of graphite’s theoretical performance, and a good long-term stability of battery capacity over extended cycling. This concept highlights the potential of using paper as a separator and strengthens the outlook of a new design concept wherein paper can both act as a separator and a substrate for coating the anode material.

Ptn (n = 1, 3, and 4) Cluster-Modified MoSe2 Nanosheets: A Potential Sensing and Scavenging Candidate for Lithium-Ion Battery State Characteristic Gases.

Realizing reliable online detection of characteristic gases (H2, C2H4, CO, and CO2) in lithium-ion batteries is crucial to maintain the safe and stable operation of power equipment and new energy storage power plants. In this study, transition metal Ptn (n = 1, 3, and 4) clusters are attached to MoSe2 nanosheets for the first time based on density functional theory using the perfect crystalline facet modification method, and the adsorption characteristics and electronic behaviors of H2, C2H4, CO, and CO2 are investigated and enhanced. The results show that Ptn (n = 1, 3, and 4) is reliably chemically connected to the substrate without any significant deformation of the geometry. The adsorption properties as well as the band gap, DOS, and LUMO-HOMO are optimized for the modified Gas/Ptn (n = 1, 3, and 4)-MoSe2 system. The large electronic states near the Fermi level are further activated by the modification process, and Pt-MoSe2 and Pt4-MoSe2 can serve as battery state characteristic gas sensors suitably according to the detection needs of specific target gases, whereas Pt3-MoSe2 can be used as a good adsorbent for effective and reliable scavenging of battery state characteristic gases and is further applied to energy and power equipment and new energy storage power plants.

Lithium Battery Degradation and Failure Mechanisms: A State-of-the-Art Review

This paper provides a comprehensive analysis of the lithium battery degradation mechanisms and failure modes. It discusses these issues in a general context and then focuses on various families or material types used in the batteries, particularly in anodes and cathodes. The paper begins with a general overview of lithium batteries and their operations. It explains the fundamental principles of the electrochemical reaction that occurs in a battery, as well as the key components such as the anode, cathode, and electrolyte. The paper explores also the degradation processes and failure modes of lithium batteries. It examines the main factors contributing to these issues, including the operating temperature and current. It highlights the specific degradation mechanisms associated with each type of material, whether it is graphite, silicon, metallic lithium, cobalt, nickel, or manganese oxides used in the electrodes. Some degradations are due to the temperature and the current waveforms. Then, the importance of thermal management and current management is emphasized throughout the paper. It highlights the negative effects of overheating, excessive current, or inappropriate voltage on the stability and lifespan of lithium batteries. It also underscores the significance of battery management systems (BMS) in monitoring and controlling these parameters to minimize the degradation and the risk of failure. This work provides a summary of valuable insight into the development of BMS. It emphasizes the importance of understanding the degradation mechanisms and failure modes specific to different families of lithium batteries, as well as the critical influence of temperature and current quality. Rational management or efficient controlling of these parameters can enhance the performance, reliability, and lifespan of lithium batteries.

Predictive Modeling for Electric Vehicle Battery State of Health: A Comprehensive Literature Review

The rising adoption of electric vehicles (EVs) utilizing lithium-ion batteries necessitates a robust understanding of state-of-health (SOH) estimation. The existing literature highlights various SOH estimation models, but a comprehensive comparative analysis is lacking. This paper addresses this gap by conducting an exhaustive review of diverse SOH estimation approaches for EV battery applications, including the direct measurement method, physical-based and data-driven approaches. Results highlight that data-driven methods, particularly those utilizing machine learning techniques, offer superior accuracy and adaptability but often require extensive datasets. In contrast, physical-based approaches provide interpretable insights but are computationally intensive, and direct measurement methods, though simple, lack generalizability. In addition, this paper also systematically reviews the indicators of battery SOH, influential factors affecting battery SOH, and various datasets used for SOH modeling. Future research should focus on integrating multiple modeling methodologies to leverage their combined strengths, enhancing the collection of comprehensive battery lifecycle datasets to support robust model development, and extending the scope of SOH estimation beyond individual cells to encompass entire battery packs.

Progress in estimating the state of health using transfer learning–based electrochemical impedance spectroscopy of lithium-ion batteries

Progress in estimating the state of health using transfer learning–based electrochemical impedance spectroscopy of lithium-ion batteries

Energy Use and Environmental Impact of Three Lithium-Ion Battery Factories with a Total Annual Capacity of 100 GWh

The rapid evolution of Li-ion battery technologies and manufacturing processes demands a continual update of environmental impact data. The general objective of this paper is to publish up-to-date primary data on battery manufacturing, which is of great importance to the scientific community and decision-makers. The environmental impacts have been calculated and estimated based on publicly available data disclosed under Hungarian government regulations and official decrees. The gate-to-gate energy use, greenhouse gas (GHG) emissions, water consumption, and N-methyl-2-pyrrolidone (NMP) consumption are estimated for three battery factories in Hungary, with a total annual capacity of approximately 100 GWh. The factories use around 30–35 kWh energy per kWh of battery capacity and the associated GHG emissions are around 10 kgCO2eq per kWh of cell production. The water consumption varies considerably among factories, with one plant using 28 L per kWh and the other two using 56 and 67 L per kWh. The specific consumption of NMP was calculated for two factories, resulting in close values of 0.51–0.56 kg per kWh of cell production. As a new approach, we distinguish between global and local GHG emissions related to battery production. The main component of the latter is carbon dioxide from the combustion of natural gas, but the local transport related to the battery factories is also a source of emissions. Our estimations include not only the consumptions required directly for the manufacturing technology, but also those for social purposes (e.g., heating offices), giving a more complete picture of the factory’s environmental impact. We believe that up-to-date primary data are crucial for ensuring transparency and holds significant value for both the scientific community and decision-makers.

Enhanced ALD Nucleation on Polymeric Separator for Improved Li-S Batteries.

Lithium-sulfur (Li-S) batteries, with their superior energy densities, are emerging as promising successors to conventional lithium-ion batteries. However, their widespread adoption is hindered by challenges such as the shuttle effect of polysulfides, which affects discharge capacity and cycling stability. This study explores the transformative potential of atomic layer deposition (ALD) of Al2O3 on commercial PP/PE/PP separators (Celgard), combined with the use of UV ozone exposure to enhance ALD nucleation on the separator surface, to address these challenges. We demonstrate that ALD Al2O3 not only preserves the separator's inherent morphology but also enhances its chemical interactions toward polysulfide, crucial for optimal battery performance. Moreover, batteries with the modified separator exhibit an enhanced specific capacity, reaching up to ∼1150 mAh/g, and a reduced lithium plating overpotential, indicating improved kinetics. Our findings, based on X-ray photoelectron spectroscopy surface characterization and electrochemical evaluations, underscore the significance of ALD-enhanced separators in elevating Li-S battery efficiency by polysulfide adsorption. The research opens up possibilities for high-performance Li-S batteries, suitable for a broad range of applications.

Unravelling Lithium Interactions in Non-Flammable Gel Polymer Electrolytes: A Density Functional Theory and Molecular Dynamics Study

Lithium metal batteries (LiMBs) have emerged as extremely viable options for next-generation energy storage owing to their elevated energy density and improved theoretical specific capacity relative to traditional lithium batteries. However, safety concerns, such as the flammability of organic liquid electrolytes, have limited their extensive application. In the present study, we utilize molecular dynamics and Density Functional Theory based simulations to investigate the Li interactions in gel polymer electrolytes (GPEs), composed of a 3D cross-linked polymer matrix combined with two different non-flammable electrolytes: 1 M lithium hexafluorophosphate (LiPF6) in ethylene carbonate (EC)/dimethyl carbonate (DMC) and 1 M lithium bis(fluorosulfonyl)imide (LiFSI) in trimethyl phosphate (TMP) solvents. The findings derived from radial distribution functions, coordination numbers, and interaction energy calculations indicate that Li⁺ exhibits an affinity with solvent molecules and counter-anions over the functional groups on the polymer matrix, highlighting the preeminent influence of electrolyte components in Li⁺ solvation and transport. Furthermore, the second electrolyte demonstrated enhanced binding energies, implying greater ionic stability and conductivity relative to the first system. These findings offer insights into the Li+ transport mechanism at the molecular scale in the GPE by suggesting that lithium-ion transport does not occur by hopping between polymer functional groups but by diffusion into the solvent/counter anion system. The information provided in the work allows for the improvement of the design of electrolytes in LiMBs to augment both safety and efficiency.

Comparison of Different Nanomaterials in Anode Materials of Lithium Battery

The increasing demand for sustainable energy necessitates the enhancement of lithium-ion battery technology, especially in the advancement of superior anode materials. Contemporary lithium-ion batteries exhibit specific constraints, including comparatively poor energy density and restricted cycle life, which have stimulated growing interest in alternative battery materials with superior performance. This research conducts a literature analysis to investigate the potential of several nanomaterialsgraphene, clay mineral-derived materials, and transition metal sulfidesas improved anode materials for lithium-ion batteries. The study analyzes their characteristics, including energy storage capacity, charging speed, and cycling stability, emphasizing both their benefits and drawbacks. The study concludes that although these materials enhance battery performance considerably, obstacles persist regarding their commercialization and long-term stability. This research provides significant insights into the advancement of more efficient and sustainable lithium-ion battery technology, facilitating the global shift to renewable energy.

Fostering lithium-ion battery remanufacturing through Industry 5.0

Abstract The rise of electric vehicles (EVs) has resulted in notable environmental benefits, yet challenges persist regarding battery disposal and recovery. The increasing demand for EVs heightens concerns about the environmental impact of lithium-ion battery (LIB) waste, which threatens both ecosystems and public health. Although remanufacturing is seen as a sustainable solution to these issues, current research does not thoroughly examine the role of Industry 5.0 technologies in optimising this process. This study aims to compare and assess the potential of various Industry 5.0 technologies and approaches to enhance the remanufacturing of lithium-ion batteries. Using the AHP-PROMETHEE method, we identify the most critical and influential Industry 5.0 prospects that should be prioritised for addressing key challenges such as diagnostic accuracy, safe disassembly, and high-quality reassembly. The multi-criteria analysis highlights key Industry 5.0 imperatives that can facilitate efficient and effective remanufacturing processes. The study identifies Digital Product Passport (DPP), Digital Twin (DT), and the Internet of Everything (IoE) as critical enablers in optimizing the LIB remanufacturing process. The analysis reveals that DPP stands out as the top enabler, significantly enhancing transparency, traceability, and lifecycle management for LIBs. DT and IoE follow closely, contributing to real-time monitoring, predictive maintenance, and seamless data integration across the supply chain. This paper delves in the emerging concept of the Digital Battery Passport (DBP), a DPP mandated by recent European regulations aimed at improving battery management and circularity. The DBP facilitates access to critical data throughout the battery’s lifecycle, including its origin, composition, and state of health. This information is crucial for optimising remanufacturing processes, ensuring compliance with sustainability standards, and extending battery life. The paper highlights the potential of DBP to transform the EV battery value chain by enhancing transparency and enabling more informed decision-making across stakeholders. Our findings offer significant insights for policymakers, battery manufacturers, and remanufacturing firms.

A room temperature rechargeable Li–LiNO3 battery with high capacity

Lithium-ion batteries (LIBs) have become advanced energy storage technologies; however, specific capacity remains limited by the active materials in cathodes. Here, we report Li-LiNO3 batteries (LNBs) where LiNO3 in electrolyte serves as both active materials and ion conductor at room temperature. LNBs operate on a highly reversible redox between NO3- and NO2-, which results in an impressive areal capacity of 19 mAh cm-2 at a plateau voltage of 1.75 V. Furthermore, the pouch cell exhibits stable cycling at a capacity of 100 mAh. This research underscores the potential of LNBs for high-capacity energy storage.

Mitigation strategies can alleviate power system vulnerability to climate change and extreme weather: a case study on the Italian grid

Abstract This study explores compounding impacts of climate change on power system’s load and generation, emphasising the need to integrate adaptation and mitigation strategies into investment planning. We combine existing and novel empirical evidence to model impacts on: (i) air-conditioning demand; (ii) thermal power outages; (iii) hydro-power generation shortages. Using a power dispatch and capacity expansion model, we analyse the Italian power system’s response to these climate impacts in 2030, integrating mitigation targets and optimising for cost-efficiency at an hourly resolution. We outline different meteorological scenarios to explore the impacts of both average climatic changes and the intensification of extreme weather events. We find that addressing extreme weather in power system planning will require an extra 5–8 GW of photovoltaic (PV) capacity, on top of the 50 GW of the additional solar PV capacity required by the mitigation target alone. Despite the higher initial investments, we find that the adoption of renewable technologies, especially PV, alleviates the power system’s vulnerability to climate change and extreme weather events. In fact, renewable energy sources are generally less vulnerable to the impacts of climate change, such as rising temperatures and shifting precipitation patterns, compared to thermal power and hydropower generation. Furthermore, enhancing short-term storage with lithium-ion batteries is crucial to counterbalance the reduced availability of dispatchable hydro generation.

Critically assessing sodium-ion technology roadmaps and scenarios for techno-economic competitiveness against lithium-ion batteries

Critically assessing sodium-ion technology roadmaps and scenarios for techno-economic competitiveness against lithium-ion batteries