Future Batteries最新文献

{"title":"Characteristic frequency of the diffusion response of the blocked-diffusion Warburg impedance with frequency dispersion","authors":"Samuel Cruz-Manzo","doi":"10.1016/j.fub.2025.100084","DOIUrl":"10.1016/j.fub.2025.100084","url":null,"abstract":"<div><div>The blocked-diffusion Warburg impedance with frequency dispersion (BDWf) can be considered in equivalent electrical circuits to characterise the low-frequency impedance response of batteries. In this study, the characteristic frequency of the diffusion response <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span> of the BDWf impedance is calculated using the analytical transfer function reported in a previous study and the Newton-Raphson iteration method. The results show that the characteristic frequency of the diffusion response <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span> is a numerical value x (calculated from the Newton-Raphson iteration) greater than the frequency calculated from the time constant <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mi>BW</mi></mrow></msub></math></span> of the BDWf impedance as follows: <span><math><mrow><msub><mrow><mi>f</mi></mrow><mrow><mi>d</mi></mrow></msub><mo>=</mo><mfrac><mrow><mi>x</mi></mrow><mrow><mn>2</mn><mi>π</mi><msub><mrow><mi>τ</mi></mrow><mrow><mi>BW</mi></mrow></msub></mrow></mfrac></mrow></math></span>. In this study, the characteristic frequency of the diffusion response <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span> is also represented in the impedance response of the BDWf impedance. The characteristic diffusion time constant <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span> calculated from the characteristic frequency of the diffusion response <span><math><msub><mrow><mi>f</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span> of the BDWf impedance and estimated from battery impedance measurements, could provide a new estimation of the effective anomalous diffusion coefficient of charge carriers in battery electrodes with heterogeneous particle structure. Additionally, the output voltage of a battery measured at the characteristic diffusion time constant <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mi>d</mi></mrow></msub></math></span> during current pulse tests could be considered a valuable ageing signature for assessing the state of health of the battery.</div></div>","PeriodicalId":100560,"journal":{"name":"Future Batteries","volume":"6 ","pages":"Article 100084"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144290885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance optimization of high energy density aluminum-air batteries: Effects of operational parameters and electrolyte composition","authors":"Yasmin Shabeer,&nbsp;Seyed Saeed Madani,&nbsp;Satyam Panchal,&nbsp;Michael Fowler","doi":"10.1016/j.fub.2025.100082","DOIUrl":"10.1016/j.fub.2025.100082","url":null,"abstract":"<div><div>Aluminum-air (Al-air) batteries are promising candidates for high energy-density applications due to their lightweight design, cost-effectiveness, and high theoretical energy output. This study investigates the performance optimization of two rotating disk prototypes, with prototype-1 systematically exploring the combined effects of critical parameters, including anode-cathode distance (ACD), electrolyte flowrate, and temperature- an area previously underexplored. Prototype-1 achieved high peak power densities of up to 155.87 mW/cm² and energy densities of 987.17 mWh/g. Insights gained are used to design prototype-2, which features a larger active electrode surface and an electrode cartridge system for improved usability and maintenance. Prototype-2 focused on the impact of electrolyte composition, comparing KOH and NaOH at varying concentrations. KOH achieved a peak power density of 142.4 mW/cm² and energy densities of 2778.40 mWh/g, outperforming NaOH, which displayed a peak of 120 mW/cm² energy densities of 2385.02 mWh/g. While KOH demonstrated higher energy density and superior discharge stability, NaOH exhibited greater stability at elevated concentrations and slightly better current and energy efficiency at lower concentrations. This study provides a comprehensive understanding of the synergistic effects of operational parameters and electrolyte composition on Al-air battery performance. The findings offer valuable insights for optimizing design and operational strategies, paving the way for the development of high-performance Al-air battery systems.</div></div>","PeriodicalId":100560,"journal":{"name":"Future Batteries","volume":"6 ","pages":"Article 100082"},"PeriodicalIF":0.0,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting the operational remaining life of lithium-ion battery with dynamic attention transformer","authors":"Joel J. Varghese ,&nbsp;Ekundayo Shittu","doi":"10.1016/j.fub.2025.100075","DOIUrl":"10.1016/j.fub.2025.100075","url":null,"abstract":"<div><div>The objective of this study is to introduce and examine an approach to improve and forecast the operational remaining life of batteries, specifically lithium-ion, with the aid of a dynamic attention transformer. This transformer will be aided by Bayesian change point detection. With cleaner energy sources such as lithium-ion batteries making inroads into various sectors ranging from transportation to storage, determining the useful life that is left after these batteries have been in operation for some time is of utmost importance: it increases efficiency, reduces downtime, and improves the cost of maintaining energy systems. The proposed method is based on the use of singular spectrum analysis, Bayesian change point detection, and a dynamic attention transformer. This method aims at capturing the drastic degradation pattern of batteries and learning the correlation of health indicators at those points. This dynamic attention transformer approach serves as an improvement over neural network models and vanilla transformer approaches. The results achieved by monitoring battery health indicators at drastic degradation points help in both the prediction of operational remaining life and its extension by changing the charging pattern. The performance of the algorithm was analyzed with the aid of error metrics, <em>e.g.</em>, the Mean Average Error (MAE) is 0.0189, translating into an accuracy improvement of 74.9% over neural network methods and 7.47% over other vanilla transformer-based methods. In addition, the operational remaining life improved by 15%. These outcomes offer valuable insights into the learning capabilities of DAT and present an efficient, cost-effective method for accurately estimating battery lifespan, outperforming traditional learning approaches.</div></div>","PeriodicalId":100560,"journal":{"name":"Future Batteries","volume":"6 ","pages":"Article 100075"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144115942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of biomaterial-based membranes for sustainable redox flow batteries","authors":"Xiaoyu Huo ,&nbsp;Xingyi Shi ,&nbsp;Yikai Zeng ,&nbsp;Liang An","doi":"10.1016/j.fub.2025.100080","DOIUrl":"10.1016/j.fub.2025.100080","url":null,"abstract":"<div><div>As the key component in the redox flow battery (RFB) systems, the ion exchange membrane (IEM), which facilitates proton transport while preventing electrolyte crossover, plays an important role in determining the overall system performance. However, up till now, the common commercial Nafion membranes still face the challenges raised from high cost and environmental concerns. There is an urgent demand for the development of novel membranes with low cost, high performance, and environmental friendliness. Recently, there has been growing interest in bio-sourced materials such as lignin, cellulose, and chitosan for membrane fabrication. These renewable materials offer low-cost and sustainable alternatives, providing opportunities to improve the economic viability of RFB technology while meeting environmental regulations. This review focuses on the progress of biomaterial-based membranes developed for RFBs. The potentials and limitations of various bio-sourced materials as membrane matrices and additives are evaluated and discussed. Furthermore, future research directions are suggested to provide insights for the development of next-generation membranes that meet the stringent requirements of sustainable long-term energy storage solutions.</div></div>","PeriodicalId":100560,"journal":{"name":"Future Batteries","volume":"6 ","pages":"Article 100080"},"PeriodicalIF":0.0,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144115943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Topological Optimization of Flexible Supercapacitor Electrodes through Modelling and Direct Ink 3D‐Writing","authors":"Arpan Ghosh,&nbsp;Himanshu Singh,&nbsp;Gobinda C. Mohanty,&nbsp;Koushik Biswas,&nbsp;Antony Joseph,&nbsp;Chandra Sekhar Tiwary","doi":"10.1016/j.fub.2025.100078","DOIUrl":"10.1016/j.fub.2025.100078","url":null,"abstract":"<div><div>Flexible, high surface area porous supercapacitors have caught great attention as energy storage devices. However, fabricating them through conventional methods have been challenging. The emergence of 3D printing has made it more effective to produce supercapacitors with both high capacitance and structural rigidity, while minimising material wastage. In this work, extrusion-based 3D printing, i.e. direct ink writing (DIW) has been used for the fabrication of flexible macroscale (centimetre scale) carbon-based interdigital (ID) electrodes of different geometries for supercapacitors. To investigate the effect of geometry and design on supercapacitor performance, electrochemical cyclic voltammetry (CV) analysis was performed through simulation and experiments on ID electrodes with different geometric parameters. The finite elemental analysis simulations carried out using COMSOL Multiphysics shows the interdependency of topology, surface area and capacitance. The maximum areal capacitance of ∼33.2 Fcm⁻² at 50 mVs⁻¹ has been measured experimentally for the printed capacitors. The statistical validation of the experimental results is evaluated through regression analysis. Our findings described an approach to optimize the ID electrode design geometry for high capacitance with good structural rigidity using DIW.</div></div>","PeriodicalId":100560,"journal":{"name":"Future Batteries","volume":"6 ","pages":"Article 100078"},"PeriodicalIF":0.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automation of image-based measurement of battery cell features by computed tomography and synthetic training data","authors":"Daniel Evans ,&nbsp;Simon Beckmann ,&nbsp;Kevin Talits ,&nbsp;Claas Tebruegge ,&nbsp;Julia Kowal","doi":"10.1016/j.fub.2025.100073","DOIUrl":"10.1016/j.fub.2025.100073","url":null,"abstract":"<div><div>Due to process variations in the production of lithium-ion batteries (LIBs), cells of one production batch can show a variation in physical features, inhomogeneities, and defects. These can impact the performance and safety of the cells and should be detected, and if accepted in tolerances should be measured accurately. The cell features are often unknown to manufacturers of battery modules and packs. Hence, computed tomography (CT) imaging could provide insight into the cells’ quality, allowing the measurement of relevant battery cell features. However, the high number of cells requires an automation of cell inspection. This work focuses on the challenge of automated image processing and provides an image-based workflow measuring multiple cell features based on a single CT scan. Both classical computer vision (CV) and machine learning (ML)-based image algorithms are applied within the developed workflow. To train, test, and validate the convolutional neural network (CNN)-based algorithms, artificially generated training data is created and used due to the scarcity of training data, which can form a bottleneck in CNN-model development and evaluation. Hence, the generation of synthetic training data shown in this work can reduce the need for costly laboratory CT scans before adoption in serial production environments. The results show the promising potential of synthetic training data and the automated approaches to measure cell features, specifically the electrodes’ windings, the corresponding length and width, as well as the anode overhang.</div></div>","PeriodicalId":100560,"journal":{"name":"Future Batteries","volume":"6 ","pages":"Article 100073"},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144083929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Si as an anode material in Li-ion batteries—A review","authors":"Ashish Kumar Mishra,&nbsp;Monika,&nbsp;Anjali,&nbsp;Balbir Singh Patial","doi":"10.1016/j.fub.2025.100070","DOIUrl":"10.1016/j.fub.2025.100070","url":null,"abstract":"<div><div>Li-ion batteries are considered to be the revolutionary development in the field of energy storage. New materials with greater energy density and cyclic stability are of high priority to meet the distinctive and growing demand for energy storage across various applications. To realize the enormous potential of renewable energy and electric vehicles, our immediate focus must be on developing battery materials that store substantially more energy per unit volume, resulting in smaller, lighter and more powerful batteries. Although anode materials other than graphite have been researched but these are not commercially viable due to considerable restrictions. The most commercialized battery with graphite anode has its limitation of lesser theoretical capacity of about 374 mAh g⁻¹. Researchers are testing various materials such as transition metal oxides, carbon allotrope etc., and techniques like pre-lithiation of anode materials, to synthesize new efficient materials for ongoing as well as upcoming larger applications, to build a market for hybrid electric vehicles and to grow the green energy economy. The research community sees potential in prelithiated silicon because of its approximately tenfold capacity increase over graphite, making it a great option for tackling the issue of lesser capacity of the graphite. Researchers are continuously looking for solutions to the limitations such as electrode breaking, large volume growth, capacity fading over time and side reactions of using Si as an anode material. This review paper reports and discusses the chemistry of Li and Si as well as the effect of particle size on Si’s lithiation capabilities. Influence of particle size i.e. nano-Si and micron-Si is also discussed in detail and a comparison between them is drawn for broader aspect of ongoing research. The various solutions such as prelithiation and Si<span><math><mo>/</mo></math></span>C composite used to address the associated problems have also been reviewed.</div></div>","PeriodicalId":100560,"journal":{"name":"Future Batteries","volume":"6 ","pages":"Article 100070"},"PeriodicalIF":0.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143943050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomass-derived biochar for electrochemical energy storage and conversion systems: Opportunities and challenges","authors":"Abdulla Irfan J ,&nbsp;Charulatha G ,&nbsp;Monisha Mary L ,&nbsp;Ramanamoorthy S ,&nbsp;Karthikeyan C ,&nbsp;Naveen Kumar Saravanakumar ,&nbsp;Manikandan G ,&nbsp;Jayapriya Jayaprakash ,&nbsp;Kavitha Nagarasampatti Palani","doi":"10.1016/j.fub.2025.100077","DOIUrl":"10.1016/j.fub.2025.100077","url":null,"abstract":"<div><div>The worldwide usage of fossil fuels brings severe crises, including environmental degradation, energy security concerns, and resource depletion. The materials predominantly used in energy storage and conversion devices, such as carbon, are typically derived from coal and petrochemicals, with highly energy-intensive processes and contributing to environmental pollution. Consequently, there is a pressing demand for powerful and energy-dense electrochemical devices that can reduce our dependence on fossil fuels while efficiently storing energy. In this context, biomass emerges as a promising and sustainable source to produce biochar, offering abundance, affordability, and renewability. Biochar can be easily modified with different functional groups to enhance its electrochemical behavior. This review paper gives insight about the recent advancements in the application of biochar-based materials across various fields for electrochemical energy systems. It covers topics such as lithium/sodium-ion batteries, supercapacitors, hydrogen storage systems, fuel cell technologies, and emerging microbial fuel cells/ dye-sensitized solar cells. The diverse sources of biomass and the various synthesis processes used to derive biochar would be discussed. This paper also provides outline about the potential of biochar as a renewable energy source for overcoming the challenges faced due to overconsumption of fossil fuels.</div></div>","PeriodicalId":100560,"journal":{"name":"Future Batteries","volume":"6 ","pages":"Article 100077"},"PeriodicalIF":0.0,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143911540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison between organic and inorganic PCMs providing effective battery thermal management – A machine learning approach","authors":"G. Amba Prasad Rao ,&nbsp;Sai Karthik Valaboju ,&nbsp;AR Babu ,&nbsp;G.V.S. Saurav","doi":"10.1016/j.fub.2025.100072","DOIUrl":"10.1016/j.fub.2025.100072","url":null,"abstract":"<div><div>Lithium-ion batteries (LIBs) are favored for their high energy density and long cycle life; however, their performance is highly sensitive to temperature fluctuations during charge-discharge cycles. To ensure effective heat dissipation, battery thermal management systems (BTMS) are required. The BTMS of LIBs is critical and highly essential, particularly as power batteries, in electric vehicle (EV) applications. An internal method of BTMS interferes with cell components, and hence, many researchers employed an external mode, a passive method through the use of phase change materials (PCMS) has attracted the research community. The present study, conducted using ANSYS 2023 R1, investigates the thermal performance of two LIB geometries using passive cooling strategies with phase change materials. The analysis evaluates the influence of PCM type, thickness, cell volume, and ambient temperature at discharge rates of 5 C, 6 C, and 8 C. Both organic and inorganic PCMS were analysed, demonstrating that thermal conductivity is a key factor in effective heat dissipation. Among the PCMs studied, Galinstan, an inorganic type, exhibited superior performance. Ambient temperatures significantly impact the use of PCMS and thus necessitate wider phase transition ranges to provide better adaptability. To enhance predictive capabilities, a machine learning model was employed, achieving high accuracy with an RMSE of 0.629 and an R² of 0.997. It is inferred that lower discharge rates are preferable under high ambient temperatures to ensure safe operation, even when using high thermal conductivity PCMs. Additionally, incorporating flame retardants or anti-corrosive agents, tailored to the PCM type, can further improve safety and system performance.</div></div>","PeriodicalId":100560,"journal":{"name":"Future Batteries","volume":"6 ","pages":"Article 100072"},"PeriodicalIF":0.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143904230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced thermal management of lithium-ion battery using fin-enhanced PCM: A CFD study","authors":"Md Ahnaf Adit,&nbsp;Md Mahamudul Hasan Pranto,&nbsp;Md. Golam Kibria","doi":"10.1016/j.fub.2025.100076","DOIUrl":"10.1016/j.fub.2025.100076","url":null,"abstract":"<div><div>The study investigates the thermal behavior of a lithium-ion battery, particularly 18650 LiFePO₄ cell, at different discharge rates through computational fluid dynamics (CFD) simulations. An advanced battery thermal management system (BTMS) utilizing phase change material (PCM) and hybrid nanocomposite PCM (HNPCM) was examined to reduce temperature elevation and improve thermal uniformity. HNPCMs exhibited enhanced thermal conductivity, increasing by 359.09 % compared to pure PCM; nevertheless, the somewhat diminished latent heat of melting constrained energy absorption. Simulations indicated the peak surface temperatures for fin-only designs as 315.3 K, 318 K, and 320.81 K; for PCM/fin configurations as 314.16 K, 316.36 K, and 318.64 K; and for HNPCM/fin configurations as 313.67 K, 315.52 K, and 317.4 K at 12 C, 16 C, and 20 C, respectively. Notwithstanding minimal melting during operation, the HNPCM/fin configuration exhibited the most efficient heat regulation. The findings indicate that the HNPCM/fin configuration consistently surpassed the PCM/fin and fin-only arrangements at all discharge rates. At discharge rates of 12 C, 16 C, and 20 C, maximum reductions in surface temperature of 6.64 %, 8.73 %, and 11 %, respectively, were attained in comparison to setup without a BTMS. This study highlights the promise of improved BTMS designs, especially those employing HNPCMs, in facilitating safer and more efficient operation of lithium-ion batteries. Subsequent research should concentrate on enhancing fin-and-housing configurations, integrating low-melting-point phase change materials, and investigating small, scalable battery thermal management system designs for electric vehicle applications.</div></div>","PeriodicalId":100560,"journal":{"name":"Future Batteries","volume":"6 ","pages":"Article 100076"},"PeriodicalIF":0.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143917598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}