Lithium-ion Batteries Research Articles

A Polysaccharide Binder with Carbon Quantum Dots for Improved Flexibility of Si Anodes in Lithium–Ion Batteries

A Polysaccharide Binder with Carbon Quantum Dots for Improved Flexibility of Si Anodes in Lithium–Ion Batteries

Triazine-Based Large-Sized Single-Crystalline Two-Dimensional Covalent Organic Framework for High-Performance Lithium-Ion Batteries.

A large-sized single crystalline 2D COFs with excellent crystallinity and stability was prepared through the traditional thermal solvent method. The electrochemical performance can be significantly enhanced using a straightforward hybrid approach that involves in situ growth of the 2D COFs on multi-walled carbon nanotubes (MWCNTs). Both the advantages of COFs and CNTs are mutually enhanced. The single-crystalline feature of the obtained COFs improves the structural integrity and brings excellent chemical and electrochemical stabilities for lithium-ion battery applications. The resultant COF-CNT core-shell hybrids greatly improved the conductivity and demonstrated excellent lithium-ion storage performance with a high capacity of 228 mAh g-1 (0.2 A g-1).

Multi-scale self-attention feature decoupling transfer network-based cross-domain capacity prediction of lithium-ion batteries

Lithium-ion battery capacity prediction is paramount for improving the safety and reliability of energy storage devices. However, accurately predicting capacity continues to pose a challenge, stemming from the diverse range of operational conditions and the lack of capacity labels under unpredictable scenarios. To tackle this problem, a multi-scale self-attention feature decoupling transfer network is proposed for predicting the capacity of lithium-ion batteries across diverse operational conditions. More specifically, multi-scale multi-head self-attentive encoders are designed to adaptively extract multi-scale domain-invariant features by using a series of loss function constraints. Then, transfer learning integrated with domain-invariant features is applied to migrate the knowledge of the source domain to the target domain for cross-domain capacity prediction. Finally, the performance of our methods is authenticated through utilization of two battery dataset, each including three different charging and discharging scenarios. Experimental results indicate that the proposed method effectively extracts domain-invariant features from charging data characterized by varying distributions, thereby mitigating the effects of distributional differences. Compared with the state-of-the-art methods, the proposed method shows excellent accuracy and bustling ability in two datasets.

A microscale soft lithium-ion battery for tissue stimulation

AbstractAdvances in the development of tiny devices with sizes below a few cubic millimeters require a corresponding decrease in the volume of driving power sources. To be minimally invasive, prospective power sources in biomedical devices must be fabricated from soft materials. Previous endeavors with droplet-based devices have produced promising miniature power sources; however, a droplet-based rechargeable battery has remained out of reach. Here we report a microscale soft flexible lithium-ion droplet battery (LiDB) based on the lipid-supported assembly of droplets constructed from a biocompatible silk hydrogel. Capabilities such as triggerable activation, biocompatibility and biodegradability and high capacity are demonstrated. We have used the LiDB to power the electrophoretic translocation of charged molecules between synthetic cells and to mediate the defibrillation and pacing of ex vivo mouse hearts. By the inclusion of magnetic particles to enable propulsion, the LiDB can function as a mobile energy courier. Our tiny versatile battery will thereby enable a variety of biomedical applications.

Synergistic Anion and Solvent-Derived Interphases Enable Lithium-Ion Batteries under Extreme Conditions.

Lithium-ion batteries (LIBs) face increasingly stringent demands as their application expands into new areas, including extreme temperatures and fast charging. To meet these demands, the electrolyte should enable fast lithium-ion transport and form stable interphases on electrodes simultaneously. In practice, however, improving one aspect often compromises another. For instance, the trend toward electrolytes forming anion-derived interphases typically reduces transport efficiency due to weak-solvating solvents. We propose that instead of relying on anions to form the interphase, leveraging both solvents and anions to form interphases can potentially lead to a balancing point between robust interphase formation and effective ion transport. Guided by this design principle, 2,2-difluoroethyl ethyl carbonate (DFDEC) was identified as the promising solvent. With the new electrolyte using DFDEC as the major solvent and lithium bis(fluorosulfonyl) imide (LiFSI) as the salt, graphite||LiNi0.8Mn0.1Co0.1O2 (NMC811) full cells are capable of fast charging and demonstrate long-term cycling stability with a cutoff voltage of 4.5 V. Notably, the battery shows a capacity retention of 84.3% after 500 cycles with an average Coulombic efficiency (CE) as high as 99.93%. This new electrolyte also enables stable battery cycling across a wide temperature range (-20 to 60 °C), with excellent capacity retention.

Comprehensive study on lithium-ion battery cathode LiNixCoyMn1-x-yO2 as an air electrode for protonic ceramic fuel cells

The protonic ceramic fuel cells (PCFCs) exhibits a remarkable high-energy conversion efficiency and significant application potential at low temperatures. In this context, the layered ternary lithium-ion batteries (LIB) material, LiNixCoyMn1-x-yO2 (LNCM), is explored as a potential cathode for PCFCs. Utilizing density functional theory (DFT) calculations, we have conducted a comprehensive analysis of oxygen vacancies, hydration energy, density of states, and other pertinent properties to evaluate these ternary materials. Both theoretical and experimental findings suggest that LiNi0.5Co0.2Mn0.3O2 (LNCM523) may offer the optimal performance as a PCFCs cathode. Notably, after calcination in air at 700 °C for 100 h, LNCM523 displayed no phase transition or the emergence of new phases. The impedance of LNCM523, measured on a BaZr0.1Ce0.7Y0.1Yb0.1O3-δ (BZCYYb) electrolyte, is 0.225 Ω cm2 at 650 °C. At this temperature, the peak power density of the single cell reaches 355 mW cm−2. Moreover, during a 100-h stability test conducted at 550 °C, the output performance of the single cell remained unaltered. In electrolysis mode, at 650 °C and 1.3 V, the current density for electrolysis water attained 1.75 A cm−2. Based on these promising results, LNCM emerges as a viable cathode candidate for PCFCs.

Effect of the succinonitrile additive, electrode processing, and N/P ratios in the performance of high‐voltage lithium‐ion batteries using LiNi0.5Mn1.5O4 cathode

AbstractThe progressive improvement in the gravimetric energy density of lithium‐ion batteries (LIBs) leads to electrolyte design, positive electrode, and full‐cell optimization processes. The spinel lithium nickel manganese oxide (LiNi0.5Mn1.5O4, LNMO) is one of the potential candidates for the next generation of LIBs applied for electric vehicles due to high working potential (4.75 V vs. Li+/Li), affordable price, and environmental friendliness. Nevertheless, the degradation of cycling performance at high potential induces massive challenges for commercializing LNMO‐based batteries. This study investigated the impact of succinonitrile (SN), electrode processing, and N/P ratios to strengthen the LNMO half‐cell and graphite||LNMO full‐cell performance. According to the performance in half‐cell, the sample contained 85 wt% LNMO: 7.5 wt% C65: 7.5 wt% PVDF/NMP combining with the electrolyte 1.5 M LiPF6 in EC:EMC:DMC (2:1:7 – v/v) at 0.5 wt% SN seems to be the optimal condition for further full‐cell. In addition, the full‐cell with N/P = 1.3 displays a remarkable initial capacity of 118.75 mAh g−1, a Coulombic efficiency of 91.64%, and a superior gravimetric energy density of 537.71 mWh g−1. Moreover, it maintains a capacity retention of around 58% at the current density of 0.1C after 100 cycles. As a result, this study presents an optimal solution to augment the material's potential for commercialization in the immediate future.

High-Selective Separation Recovery of Ni, Co, and Mn from the Spent LIBs Via Acid Dissolution and Multistage Oxidation Precipitation.

For recovering Ni, Co, and Mn from lithium-ion batteries, traditional chemical precipitation methods demonstrate low selectivity and significantly contribute to environmental pollution. This study proposes a separation recovery technique for transition metals, specifically Ni, Co, and Mn, from spent LIBs, involving "acid dissolution" and "multistage oxidation precipitation". More than 98 % of transition metals can be extracted from spent LIBs using a low acid concentration (0.5 M) without reducing agents. The feasibility of separating different metals via multistage oxidation precipitation, based on their different electrode potentials for oxidizing Me2+ (Me=Mn/Co/Ni), was confirmed. The combination of oxidizing agent S2O8 2- and the precipitant OH- was universally applied to the fractional precipitation of Mn, Co, and Ni respectively. About 99 % of Mn, 97.06 % Co, and 96.62 % Ni could be precipitated sequentially by changing the concentrations of S2O8 2- and the pH value of solution. XRD, XPS, XRF, ICP-MS and other methods were employed to elucidate the mechanism behind the multistage oxidation precipitation of target metal compounds, exploiting the differential electrode potentials for oxidizing Me2+ ions. This technique surpasses traditional solvent extraction in cost-effectiveness and selectivity, showing promise for large-scale industrial applications in recovering Mn, Co, and Ni.

Structural stability and enhanced electrochemical performance of Co-free Li-rich layered Mn-based Li1.2Mn0.6Ni0.2O2 cathodes via F doping at the O site of lithium-ion batteries

Li-rich Mn-based Co-free layered oxides (LLOs) are promising cathode materials for lithium-ion batteries (LIBs). However, they exhibit capacity loss and low initial Coulombic efficiency. Herein, an F-doped Li1.2Mn0.6Ni0.2O1.9F0.10 material has been prepared by the high-temperature solid-state method, with numerous oxygen vacancies on the surface to accelerate Li + transport. The electrochemical performance of Li1.2Mn0.6Ni0.2O1.9F0.10 considerably improved after the treatment. A high-capacity retention of 86.9 % after 100 charge/discharge cycles at 1C was achieved for Li1.2Mn0.6Ni0.2O1.9F0.10. Results revealed that F doping replaces part of O2−, forming more force between the TM-F bonds (compared to the TM-O bond), which inhibits the cation mixing phenomenon. The layered structure stability of the material is improved after F doping, and the migration energy barrier of Li+ is reduced, which promotes the migration of Li+, thereby improving the electrochemical performance of Li1.2Mn0.6Ni0.2O2.

A Rapid Synthesis of Amorphous LiTaOCl4 Solid Electrolytes Through a Two‐Step Reaction Pathway for High‐Rate and Long‐Cycling Lithium Batteries

AbstractA simplified process to prepare solid electrolytes (SEs) that fulfill long cyclability, fast‐charging performance, and wide‐temperature feasibility in all‐solid‐state lithium batteries (ASSLBs) is important. Here, amorphous LiTaOCl4 (aLTOC) SE is synthesized within only four hours via a two‐step reaction by high‐energy ball milling method, which exhibits high ionic conductivity and excellent interfacial compatibility. A bilayer SE based on aLTOC and sulfide along with corresponding ASSLBs, are constructed. Furthermore, slight evolution of the unusual microstructure in the chloride/sulfur interfacial region is observed and analyzed. Density functional theory calculations show that S tends to displace O sites in TaO2Cl4 octahedra instead of Cl sites. As a result of the enhanced interfacial stability and reduced formation of ionically insulating phases, the assembled ASSLBs achieve superior rate performance and cyclability in a wide temperature range. Notably, the ASSLBs show capacity retention of 84.4% and 77.6% after 2000 and 1000 cycles at current density of 10C at 30 and 60 °C, respectively. Importantly, even under −20 °C, the cell works stably over 1600 cycles with capacity retention of 76.3% at 0.5C. The work pave the way for the massive production of high‐performance amorphous chloride electrolytes and the realization of fast‐charging ASSLBs with long cycle life.

A flexible porous polyimide/copper composite film toward high-mass-loading anodes in lithium-ion batteries

Conventional metal foil current collectors are essential for electronic conduction in lithium-ion batteries, but the planar structure limits the fast transporting of electron and the power density. Herein, a light, conductive, self-extinguishing, and flexible porous polyimide/copper composite film (PIF/Cu) derived from a polyimide foam was fabricated via hot pressing and electroless plating methods. The honeycomb structure was illustrated in PIF/Cu under a 3D X-ray tomography microscope, revealing the successful construction of a 3D conductive network. PIF/Cu-30 possessed an electronic conductivity of as high as 3.6 × 105 S m−1 at a bulk density of 0.26 g cm−3 and exhibited exceptional structural stability even after successive and harsh mechanical loads. Graphite with a mass load of 12 mg cm−2 was loaded into the PIF/Cu-30 to prepare the anode for cell assembly. The cells using PIF/Cu-30 achieved a better performance in capacity retention (98.2 %@60 cycles) than those using traditional Cu foils (55.1 %@60 cycles), which resulted from the fast transport of electrons and Li-ion through the 3D conductive networks in the porous PIF/Cu-30.

A SOH estimation method of lithium-ion batteries based on partial charging data

Accurate and reliable assessment of lithium-ion battery SOH is critical to improving the safety performance of electric vehicles. In the existing data-driven methods, the models are often complex, the calculation is large and the interpretation ability is not strong, so it is difficult to realize the commercial application. In this paper, a novel SOH estimation method is proposed. Firstly, the incremental capacity (IC) curve is used to extract the aging features from part of the charging data, and a linear battery aging state space equation is established based on the features. The aging state of the battery can be directly observed under the condition of small calculation amount. Second, the aging state of the battery can be tracked and corrected by double Kalman filter to improve estimation accuracy. The performance of the proposed method is verified on CACLE dataset, Oxford dataset and DUT dataset respectively. The estimated errors are all <2.5 %, and the mean RMSE is 0.0066. The results show that the method can be effectively applied to different lithium-ion batteries. In order to further demonstrate the advantages of this estimator, we also compare it with literature methods using the same dataset. In the CACLE data set and Oxford data, the average time of this method is 0.848 s and the average RMSE is 0.0050, which is in a dominant position. The proposed method provides a simple and feasible way to estimate the SOH of electric vehicles.

An efficient state-of-health estimation method for lithium-ion batteries based on feature-importance ranking strategy and hybrid kernel extreme learning machine algorithm

The safe and reliable operation of battery systems depends critically on accurately and dependably estimating the state of health (SOH) of lithium-ion batteries (LIBs). However, accurate prediction of SOH still needs improvement due to the complex battery aging mechanism. This paper introduces a hybrid kernel extremum learning machine (HKELM) for estimating battery SOH. To improve estimation accuracy, we enhance the standard dung beetle optimization algorithm (DBO) with a new initialized population, adaptive weights method, and improved population diversification. We then use the enhanced IDBO algorithm to optimize the parameters of HKELM. This study examines two distinct anode types of LIBs from NASA and Oxford datasets. Fifty significant features are extracted from charging voltage, current, temperature, and incremental capacity (IC) curves. The importance indices of these features are then computed using statistical analyses, including Pearson's correlation coefficient and Spearman's rank correlation coefficient, followed by optimal ranking. The optimal number of final features is determined by comparing various combinations of high-level features, thus reducing model complexity and improving estimation accuracy. This paper proposes the IDBO-HKELM algorithm for SOH estimation. Compared to other methods, the algorithm shows superior estimation performance and anti-interference capability. Both B0007 and Cell8 estimate SOH with MAE < 0.15, RMSE <0.2, and R2 > 99.9 %. Experimental results demonstrate the robustness of the proposed method, achieving accurate and noise-immune SOH estimation.

Effects of fluorine and phosphorus-based flame retardants addition on the lower flammability limit of dimethyl carbonate

This study initially examines the alteration pattern of the lower flammable limit (LFL) of dimethyl carbonate (DMC), a typical electrolyte component in lithium batteries, under the influence of inhibitors, namely di(2,2,2trifluoroethyl) carbonate (DtFEC), perfluorohexanone (C6F12O), and trimethylphosphate (TMP), through experimental investigation. Additionally, the critical inhibitory concentration required for complete inhibition is investigated. Subsequently, numerical simulations and chemical kinetic path analyses reveal how these inhibitors control combustion. Results show that C6F12O and DtFEC initially decrease and then increase the LFL of DMC, while TMP causes a monotonic increase. This is due to the competition between reaction-thermal and reaction-radical effects. Reaction kinetic analysis reveal that when small amounts of C6F12O and DtFEC are added, the fluorine-containing components decomposed by the reaction undergo oxidation, thereby promoting combustion. However, with increased amounts, these components combine with H and OH radicals to form stable substances like HF, inhibiting the combustion process. In the case of TMP, the phosphorus-containing intermediate components produced by cleavage catalyze the recombination of H and OH radicals, thereby inhibiting DMC combustion. The research findings offer a theoretical foundation for the development of safer lithium batteries and provide crucial data references for enhancing battery safety and prevention measures.

Constructing Targeted Strong Nb4d-O2p-Li2s Configurations to Obtain Excellent Energy Density and Long Life for Li-Rich Cathodes.

The Li-rich Mn-based cathode materials (LMRs) deliver excellent energy density and exhibit low cost, which are considered as the most promising cathode materials for the next generation lithium-ion batteries. However, the irreversible redox reaction of the oxygen atoms directly leads to release oxygen and intensifies phase transformation. Besides, the local stress and strain will be generated due to the unit-cell volume difference between R-3m and C2/m phases, which continuously aggravates the collapse of secondary particles. Herein, the strong Nb4d-O2p-Li2s configurations at the Li1 sites of the TM-layer in the C2/m phase and secondary particles with the radial arrangement of refined primary particles are designed to inhibit oxygen release and relieve lattice stress by Nb2O5 treatment. Meanwhile, the preferential growth of the active {010} planes is presented to obtain an excellent transmission rate of Li+. As a result, the designed LMR delivers remarkable electrochemical properties with high discharge capacity and initial coulomb efficiency of 276 mAh g-1 and 85 % at 0.1 C, outstanding cycling retention rate of 81 % after 300 cycles. This novel crystal structure combining oxygen coordination regulation and micro-nano scale design provides inspiration for the design of high-performance LMRs.

Optimization of Retired Lithium-Ion Battery Pack Reorganization and Recycling Using 3D Assessment Technology

Optimization of Retired Lithium-Ion Battery Pack Reorganization and Recycling Using 3D Assessment Technology

Electrochemical performance of ultra-high‑nickel layered oxide cathode synthesized using different lithium sources

Ultra-high‑nickel layered oxide cathodes are extensively explored in lithium-ion battery research owing to their high specific capacity. However, the rapid decline in discharge specific capacity considerably limits their long-term performance. The choice of lithium precursors is crucial in enhancing both the structural and cycle stability of these batteries, yet this aspect has not been adequately addressed in existing studies. In this study, Li2O, LiOH, and Li2CO3 were used as lithium precursors to synthesize LiNi0.92Co0.04Mn0.04O2 (NCM92) cathodes. We compare the structure and electrochemical properties of NCM92 cathode materials prepared with these three lithium precursors, examining a lithium residual layer on the surface of three NCM92 and thus inferring the varying amounts of Li incorporation into the bulk lattice. Our findings highlight the effect of lithium precursors on the rapid degradation of NCM92's discharge capacity. Notably, the NCM92–Li2O cathode demonstrates a higher discharge specific capacity and superior capacity retention after 100 cycles compared to cathodes synthesized with LiOH and Li2CO3. This study provides valuable insights and guidance for further research on ultra-high‑nickel layered oxide cathode materials.

Application of Spectroscopic Techniques in the Development of Fast-Charging Lithium-Ion Batteries

Application of Spectroscopic Techniques in the Development of Fast-Charging Lithium-Ion Batteries

Risk assessment in lithium-ion battery circular economy in sustainable supply chain in automotive industry using gray degree of possibility in game theory and MCDM

Risk assessment in lithium-ion battery circular economy in sustainable supply chain in automotive industry using gray degree of possibility in game theory and MCDM

Fast acquisition method of battery electrochemical impedance spectra based on impedance fragments

Electrochemical impedance spectroscopy (EIS) is often used for battery characterization and monitoring. However, there are still difficulties in acquiring battery impedance spectra in large quantities and wide frequency bands in practical applications. The lower the frequency range of acquisition, the longer the measurement time spent, and the higher the frequency range of measurement, the more expensive the measurement equipment, and these problems seriously limit the wide application of impedance information. To address this problem, this study proposes a method for fast acquisition of electrochemical impedance spectra of lithium-ion batteries based on impedance fragments. Firstly, impedance segments at specific frequencies in the EIS are selected as features based on the distribution of relaxation times (DRT). Then, a Long Short-Term Memory (LSTM) neural network model is used to reconstruct the complete impedance spectrum, and a population optimization algorithm is used to optimize the hyperparameters in the model. The validation results indicate that the reconstructed RMSE error is only 14.26 mΩ, corresponding to a MAPE of 1.65 %, while the measurement time is reduced to 27.01 % of the original measurement time. Finally, the performance of this method in identifying fractional-order model parameters is further discussed.