Battery Energy最新文献

Covalent organic frameworks (COFs) have emerged as promising electrode materials for lithium-ion batteries (LIBs) due to their tunable redox-active properties and environmental benefits. However, the influence of electrolytes on COF-based battery performance remains poorly understood at the molecular level. In this study, we employ molecular dynamics simulations to investigate the interaction between terephthalaldehyde and 1,3,5-tris(4-aminophenyl)benzene COF (DAAQ-TFP-COF) and two organic electrolytes: lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) in tetraethylene glycol dimethyl ether (TEGDME) and LiPF₆ in a mixture of ethylene carbonate and diethyl carbonate (EC/DEC). Our simulations reveal different lithium coordination environments: while LiTFSI in TEGDME shows better salt dissociation, LiPF₆ in EC/DEC exhibits higher lithium self-diffusion coefficients, despite greater coordination to the COF structure. We identify that lithium transport is primarily mediated by the organic solvent, with COF coordination sites hindering mobility. These findings highlight the importance of electrolyte selection in optimizing COF-based electrodes for LIBs and provide novel insights into the interplay between structural properties and ionic dynamics in porous frameworks.

Lithium-ion batteries are essential in modern energy systems, supplying electricity to many consumer products that require dependable operation. This study introduces a novel method for predicting the remaining useful life (RUL) and end-of-life (EoL) of lithium-ion batteries (LIBs) using the long short-term memory (LSTM) model. The process includes getting the data ready, using exponential smoothing (ES), making a sequence, using the double lightning search algorithm (DLSA) to find the best hyperparameters, and doing iterative LSTM modeling. ES is utilized to preprocess data, reduce noise, and improve input quality for the subsequent model phases, while the iterative integration of LSTM modeling and DLSA hyperparameter optimization enhances capacity estimates across the entire battery lifecycle. The model performance is assessed using basic statistical measures, indicating consistent accuracy in predicting the state of health (SOH) and RUL. The way the time series is set up lets the LSTM accurately find important time-based relationships, even when there is much noise. Adaptive hyperparameter selection through DLSA safeguards against fluctuating degradation rates, yielding an average error of under ±0.002 ampere-hours in capacity prediction. Systematic sampling and normalization make calculations faster without changing the quality of the data. Data from the NASA Prognostics Center of Excellence on LIB performance and degradation are used to validate the model. This predictive modeling approach shows how data smoothing, deep learning, and intelligent search algorithms can improve RUL and EoL forecasts for real-time battery health monitoring and operational safety.

Aqueous zinc-based batteries (ZIBs) are considered promising energy storage solutions, particularly targeting low-cost applications needed for levelling electricity production from renewable energy sources. However, numerous challenges need to be overcome to bring the technology to the market, chiefly including cathode dissolution, dendrite formation, hydrogen evolution reaction, and zinc corrosion. The optimisation of the electrolyte, particularly the use of gel-polymer electrolytes (GPEs), is demonstrated as a viable approach to solve or mitigate such issues. In this respect, a comparative study of two GPEs based on biopolymers, agarose and sodium alginate, is presented here. Despite the fast and facile preparation procedure, the GPEs demonstrate to be strongly effective in suppressing dendrite and byproduct formation on zinc metal anodes, due to the abundant ─OH groups along the chains in polymeric matrices. The electrochemical behaviour of GPEs is evaluated in terms of galvanostatic cycling in laboratory-scale zinc metal cells with a CaV₆O₁₆·3H₂O cathode at low and high active material loadings of 2.5 and 5 mg cm⁻², respectively. Resulting cycling performances in terms of specific capacity and rate capability are comparable (low loading electrodes) and even outperform (high loading electrodes) those obtained with a standard liquid electrolyte (2M ZnSO₄) laboratory-scale cell, thus accounting for the promising prospects of the bio-polymer GPEs as an alternative green, sustainable electrolyte for next-generation Zn-based batteries.

Nitrogen-doped carbide-derived carbons (N-CDCs) are promising materials for energy storage due to their tunable structure and chemistry. Here, we design a molecular architecture strategy to promote nitrogen incorporation and microstructural control during the synthesis of N-CDCs. By varying polymerization and pyrolysis conditions, we obtain materials with hierarchical porosity and high specific surface area (S_BET > 2000 m² g⁻¹) and nitrogen content between 1.8 and 6.4 wt.%. Electrochemical evaluation in aqueous 6 M KOH using both three- and two-electrode configurations, identifies nitrogen doping, defect density, and hierarchical porosity as key contributors to performance. The optimized N-CDC delivers a specific capacitance of 210 F g⁻¹ at 1 A g⁻¹, with high retention at elevated current densities. A proof-of-concept pouch cell shows 100 F g⁻¹ at 0.5 A g⁻¹ and stable cycling over 5000 cycles, resulting in superior coulombic efficiency. The practical applicability is demonstrated with two pouch cells connected in series to power an electronic watch (1.5 V). These findings demonstrate the effectiveness of molecular-level control in the design of high-performance carbon-based supercapacitor electrodes.

Half-cells have been employed to investigate the intrinsic electrochemical behavior of the cathode material, as the chemical potential of the alkali metal reference electrode remains relatively constant during discharge. However, in full cells, the discharge mechanism is anode-dependent. Herein, a rechargeable nonaqueous sodium ion battery (SIB) is fabricated using tungsten trioxide (WO₃) nanopowder on a graphite substrate as the anode and a nickel-hexacyanoferrate Prussian blue (PB) cathode to understand the dominant discharge mechanism. The battery cells are evaluated for reversibility and durability and exhibit reversible charge–discharge plateaus, confirming sodium-ion intercalation/deintercalation in both electrodes. The sodium-ion diffusion coefficient of 5.3 × 10⁻¹³cm².s⁻¹ calculated using electrochemical impedance spectroscopy (EIS) is consistent with a planar finite space diffusion mechanism. Cyclic voltammetry (CV) shows a broad reversible redox peak on the WO₃ anode, owing to its multiple valence states, also observed in potential versus differential capacitance (dQ/dV) and simulated density of states (DOS). The full cell demonstrates an open-circuit voltage (OCV) of 2.2 V (charged), a discharge capacity of 79 mAh.g⁻¹ at 0.1C rate, and retains 69% of its capacity after 500 cycles, indicating promising durability and reversibility for sodium-ion storage. The charge carrier concentration (ccc), DOS, electrical and thermal conductivities, and chemical potential simulations for the charged and discharged phases, in both electrodes, reveal that the anode determines the shape of the discharge curve and the cathode the capacity of the cell. This study paves the way to predicting the behavior of a full cell, including cycling curve shape, process, dependencies, and thermal runaway.

Sodium carboxymethyl cellulose (CMC) and polyacrylic acid (PAA) are state-of-the-art binders in aqueous-processed anodes for lithium-ion batteries. Binders act as dispersing agents and rheology modifiers in aqueous slurries, while also providing mechanical integrity of dry electrodes during battery fabrication and operation. However, despite their low concentration, they may have detrimental effects on the conductivity and electrochemical performance of batteries, for example, due to their adsorption on active material particles, which is supposed to limit Li⁺ insertion and extraction, but also affect electrode microstructure and adhesion to the current collector. Here, a commercially available, cross-linked acrylate binder (Carbopol® Ultrez10, x-PAA) with high thickening efficiency is applied for graphite anodes. At lower polymer content, anode slurries based on x-PAA exhibit high-shear viscosities similar to those of the CMC reference and provide a yield stress, which is advantageous for slurry stability. Furthermore, SBR content could be reduced without loss of adhesion strength compared to the CMC reference, since x-PAA does not adsorb onto graphite. Thus, the total binder content could be lowered by about 40% in comparison to reference anodes comprising CMC. The substantial reduction in total binder amount resulted in slightly lower long-term stability compared to the reference cell including CMC. Cells incorporating x-PAA, however, outperformed references under fast-charging conditions (up to 5C) presumably since x-PAA does not adsorb on graphite, thus enabling more effective Li⁺ insertion and extraction. Further refinement of crosslinking microstructure may enable fabrication of electrodes with higher energy density and higher capacity retention during cycling, irrespective of cycling rate.

This study explores the development of calcium-ion batteries (CIBs) by focusing on the design of a novel electrolyte to overcome key challenges, such as poor calcium plating/stripping. Hydrated vanadium pentoxide (H-V₂O₅) served as the cathode, and graphite acted as the anode. Tricalcium dicitrate tetrahydrate (Ca-citrate) salt was used for the first time in an ethylene carbonate/propylene carbonate (EC/PC) solvent system. Ca-citrate showed marked improvement in ionic conductivity (up to 2.6 × 10⁻¹ S/cm) and electrochemical stability (~6 V) relative to traditional Ca-nitrate (2.5 V) and also displayed better capacity retention. To solve the solubility limitations of Ca-citrate in EC/PC, highly diluted (0.001 M) solution of EC/PC and modified electrolytes with cosolvents like poly(ethylene glycol) 200 (PEG 200) and trifluoroacetic anhydride (TFA) were studied. PEG 200 increased solubility and stability through hydrogen bonding, while TFA increased ionic mobility but decreased electrochemical stability. The PEG-modified electrolyte achieved a stability window of ~4 V with a charge/discharge capacity of ~198 mAh/g. Additionally, using ethylene glycol (EG) as an alternative solvent increased the electrochemically reversible, soluble, and capacitive Ca-citrate (up to 708 mAh/g, 85 mA/g). EG-based electrolyte showed high columbic efficiency (~99%–100%) and stable interfacial behavior.

In this study, a series of polydopamine (PDA)/MXene nanocomposites with varying weight ratios (90:10, 70:30, and 50:50) are synthesized via in situ polymerization and evaluated as cathode materials for both lithium-ion (LIBs) and potassium-ion batteries (KIBs). Electrochemical evaluations revealed superior performance of these composites in LIB systems, attributed to smaller ionic radius and faster diffusion kinetics of Li^⁺ compared to K^⁺. PDA exhibits low capacities of 98.6 and 96.1 mAh g^-1 for LIB and KIB, respectively. The incorporation of conductive MXene into PDA resulted in significantly improved performance. The PDA90MXene10, PDA70MXene30, and PDA50MXene50 nanocomposites delivered high specific capacities of 198.5, 297.8, and 246.6 mAh g⁻¹ for LIBs, and 165.3, 249.3, and 171.8 mAh g⁻¹ for KIBs, respectively, at 100 mA g⁻¹. These materials also exhibited excellent rate capabilities, with capacities of 133.1, 171.4, and 163.4 mAh g⁻¹ for LIBs, and 131.1, 151.5, and 125.2 mAh g⁻¹ for KIBs at a high current density of 5 A g⁻¹. Among all compositions, PDA70MXene30 demonstrated the most outstanding electrochemical performance, underscoring synergistic effect between redox-active PDA and highly conductive MXene nanosheets. This synergy facilitates improved electron transport and ion diffusion, making PDA70MXene30 a promising candidate for high-performance cathodes in both LIBs and KIBs.

Back Cover: Accurate state of health estimation is critical for battery management systems in electric vehicles. In article number BTE.20240126, Zhiqiang Lyu, Xinyuan Wei, Longxing Wu and Chunhui Liu leverages the open source battery cell data set to address the aging model SOH estimation. To handle nonlinearity and feature coupling, a flexible data-driven aging model is proposed, employing dual Gaussian process regressions and transfer learning to enhance model efficiency and accuracy. Adaptive filtering via the Particle filter further refines the model by integrating aging features and output capacity, resulting in a close loop data fusion approach for precise SOH.

Front Cover: Insight Into Puncture-Induced Thermal Runaway in Lithium-Ion Batteries to Reduce Fire Risks in Electric Vehicle Collisions. In article number BTE.20250036, Hong Zhao, Xiangkun Bo, Zhiguo Zhang, Li Wang, Walid A. Daoud and Xiangming He provided an analysis of experimental and modeling studies to establish the hierarchy of thermal runaway initiation and its influencing factors, including battery status and penetration protocols. Furthermore, he proposed materials-by-design approaches for developing intrinsically safe lithium-ion batteries (LIBs) that maintain energy density while achieving automotive-grade mechanical robustness (ISO 6469-1 compliance), ultimately advancing collision-resilient electric vehicle battery systems.