Battery Energy最新文献

{"title":"Hierarchical Conducting Bridging Network for Accelerated Charge Transport and Structural Stabilization of Li-Mn-Rich Cathodes","authors":"Somin Namkung,&nbsp;Dawon Jeong,&nbsp;Chanho Lee,&nbsp;Subi Yang,&nbsp;Minseok Kim,&nbsp;Jungmin Lee,&nbsp;Kwang Chul Roh,&nbsp;Seho Sun,&nbsp;Yun Chan Kang,&nbsp;San Moon,&nbsp;Hoon-Hee Ryu,&nbsp;Inyoung Jang,&nbsp;Chanho Kim,&nbsp;Patrick Joohyun Kim,&nbsp;Dongsoo Lee,&nbsp;Junghyun Choi","doi":"10.1002/bte2.70135","DOIUrl":"https://doi.org/10.1002/bte2.70135","url":null,"abstract":"<p>With the rapid deployment of electric vehicles (EVs), achieving high energy density and stable performance in lithium-ion batteries (LIBs) has become a critical challenge. Lithium and manganese-rich layered oxides (LMROs) are promising cathode materials owing to their high theoretical capacities; however, their intrinsically low electronic conductivities and sluggish charge-transfer kinetics result in poor rate capability and limited cycling stability. Furthermore, the non-uniform transport of electrons and Li⁺ within the electrode hinders homogeneous electrochemical reactions and induces localized degradation. This study proposes a strategy to construct a hierarchically conducting bridging network (HCBN) for highly electrochemical stable LMRO electrodes. In this approach, improved reaction uniformity combined with structural reinforcement at the individual particle level mitigates localized structural degradation and particle-level failure. Moreover, HCBN forms a continuous conductive network within the electrode, promoting uniform electrochemical reactions and mitigating localized degradation and internal stress accumulation, thereby delaying structural collapse and effectively suppressing phase transitions and particle pulverization during cycling. Consequently, the proposed strategy improves the reversibility and cycling stability of the LMRO-HCBN electrode. Overcoming the intrinsic limitations of LMROs represents a promising approach to developing next-generation high-energy-density batteries.</p>","PeriodicalId":8807,"journal":{"name":"Battery Energy","volume":"5 4","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bte2.70135","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148386819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MXenes in Advanced High-Performance Energy Storage Technologies: Synthesis, Properties, Applications, and Challenges","authors":"Shajjadur Rahman Shajid,&nbsp;Robel Ahmed,&nbsp;Md. Rasel Ahmed,&nbsp;Monjur Mourshed","doi":"10.1002/bte2.70133","DOIUrl":"https://doi.org/10.1002/bte2.70133","url":null,"abstract":"<p>The global transition to renewable energy is bottlenecked by the efficiency, safety, and environmental limitations of conventional electrochemical storage. MXenes are two-dimensional transition-metal carbides and nitrides. They offer a transformative alternative due to their exceptional electrical conductivity and tunable surface chemistry. However, their commercial viability is severely hindered by key pain points: hazardous synthesis routes, oxidative instability, and nanosheet restacking that restricts ion transport. Despite a rapidly expanding body of literature, existing reviews predominantly evaluate MXene synthesis and device performance in isolation. This review provides a unified framework focused specifically on the intersection of green synthesis and biomimetic architecture. This approach establishes a unique perspective on how nature-inspired designs can simultaneously resolve MXene's structural bottlenecks and broader environmental concerns. This article systematically evaluates the transition from toxic, top-down etching to scalable, fluoride-free, and bio-derived synthesis methods. We highlight how utilizing agricultural biomass achieves competitive electrochemical performance while maximizing cost-effectiveness. Furthermore, we rigorously analyze how biomimetic configurations (nacre-inspired brick-and-mortar layering, honeycomb porosity, and wood vascular channels) directly mitigate restacking. These designs significantly enhance charge transport, yielding superior specific capacitance, energy density, and cyclic stability. The integration of conductive additives and mathematical modeling frameworks further grounds these structural improvements in theoretical optimization. Finally, by confronting ongoing challenges in economic feasibility and manufacturing scalability, this review outlines commercial implementation pathways for electric vehicles and grid storage. These pathways are uniquely augmented by recent advances in artificial intelligence and circular economy principles and establish a comprehensive roadmap for next-generation, sustainable MXene technologies.</p>","PeriodicalId":8807,"journal":{"name":"Battery Energy","volume":"5 4","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bte2.70133","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal Control of Mobile Energy Storage via Knowledge-Guided Deep Reinforcement Learning","authors":"Xinlei Cai,&nbsp;Zijie Meng,&nbsp;Qian Guo,&nbsp;Lizhou Jiang,&nbsp;Zhijun Shen,&nbsp;Yuheng Cheng,&nbsp;Xuanang Gui,&nbsp;Junhua Zhao","doi":"10.1002/bte2.70132","DOIUrl":"https://doi.org/10.1002/bte2.70132","url":null,"abstract":"<p>While mobile battery energy storage systems (MBESSs) are typically used to improve the stability of power systems, their ability to move also creates good opportunities for businesses to earn money through energy arbitrage. This profit depends heavily on decisions about timing and location, and is affected by uncertain conditions like fluctuating electricity prices and traffic. However, finding the best real-time control strategy that considers long-term profit and these uncertainties requires significant computing power. To tackle this issue, this paper presents a deep reinforcement learning framework for MBESSs designed to get the most profit from market arbitrage. Within this framework, we introduce the Knowledge-Assisted Deep Deterministic Policy Gradient (KA-DDPG) algorithm to learn the best policy more efficiently. The core novelty of KA-DDPG lies in its probabilistic hybrid action selection mechanism that unifies the agent's learned policy, offline expert criteria, and random exploration to manage the complex hybrid action space. Additionally, a two-phase guidance strategy is implemented to transition from offline-based to real-time-based criteria actions, ensuring both learning acceleration and policy robustness under computational constraints. Our rigorous statistical evaluations demonstrate that the proposed KA-DDPG approach leads to a 3%–7% improvement in average profits over the state-of-the-art Soft Actor-Critic baseline. Furthermore, it achieves exceptional policy stability, exhibiting a variance reduction of over 60% compared to standard DRL baselines and over 92% compared to the deterministic closed-loop MPC. The KA-DDPG algorithm also substantially speeds up the learning phase, validating its efficacy for real-time MBESS control under high uncertainty.</p>","PeriodicalId":8807,"journal":{"name":"Battery Energy","volume":"5 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bte2.70132","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148237412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hierarchically Structured CNT@Co-N-CNF Interlayers for Enhanced Lithium Polysulfide Confinement in Lithium-Sulfur Batteries","authors":"Seoye Shin,&nbsp;Dae Kyom Kim,&nbsp;Jeong Jun Park,&nbsp;San Moon,&nbsp;Je-Nam Lee,&nbsp;Jong Hyeok Park,&nbsp;Sang-Gil Woo,&nbsp;Jungdon Suk","doi":"10.1002/bte2.70128","DOIUrl":"https://doi.org/10.1002/bte2.70128","url":null,"abstract":"<p>Lithium-sulfur batteries (LSBs) are considered promising candidates for high-energy-density storage systems. However, challenges such as the polysulfide shuttle effect and limited cycling stability hinder their commercialization. This study introduces a hierarchically structured interlayer, CNT @Co-N-CNF (CCNC), fabricated through a novel process that combines electrospinning with ZIF-67-derived carbonization. This interlayer uniquely integrates physical and chemical confinement mechanisms for lithium polysulfides (LiPSs) by leveraging a conductive carbon nanotube (CNT) network, nitrogen (N)-doping, and embedded cobalt species. Designed to enhance sulfur utilization and effectively suppress LiPS migration, the 50-CCNC interlayer demonstrates an initial discharge capacity of 1137.4 mAh g_s⁻¹, along with excellent cycling stability in coin cell configurations. Furthermore, its practical potential is validated in a pouch stack cell configuration, achieving an initial capacity of 1082.7 mAh g_s⁻¹and retaining 92.46% of its capacity after 40 cycles. These findings underscore the interlayer's effectiveness in addressing key challenges for large-scale LSB applications and represent a significant step toward the commercialization of high-energy-density LSB technology.</p>","PeriodicalId":8807,"journal":{"name":"Battery Energy","volume":"5 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bte2.70128","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148173710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Manufacturing-Driven Programming of Carbon Interfaces via Controlled Densification for Solid-State Sodium Storage","authors":"Fitra Ari Aditya,&nbsp;Fissilmi Zetta Dzakiyah,&nbsp;Muhammad Ilham Rizky Maulana,&nbsp;Evan Cahya Putra,&nbsp;Mutiara Tabitha Kamal,&nbsp;Antonia Anetha Binar Bulan,&nbsp;Maeza Dhenta Purniawan,&nbsp;Sahrul Ramadani,&nbsp;Adam Gilbran,&nbsp;Abbas Ali Iftikhar Hussain,&nbsp;Xiong Wen (David) Lou,&nbsp;Cancio Monteiro","doi":"10.1002/bte2.70129","DOIUrl":"https://doi.org/10.1002/bte2.70129","url":null,"abstract":"<p>Interfacial instability in solid-state sodium storage is largely dictated by uneven ion flux and localized degradation, while its control through manufacturing parameters remains limited. Here, controlled densification is employed to regulate interfacial structure and sodium-ion behavior in nitrogen-doped bio-derived carbon electrodes. Increasing pressure leads to a transition from porous and discontinuous interfaces to compact and continuous pathways, which moderates ion flux and suppresses local Na⁺ accumulation. Electrochemical impedance measurements show a reduction in interfacial resistance from 320 to 140 Ω, accompanied by restrained resistance evolution during extended cycling. Structural and post-cycling analyses indicate that this stabilization is associated with more uniform ion redistribution and reduced defect formation at the interface. Nitrogen functionalities further contribute by tuning the interfacial electronic environment, supporting more stable ion transport. The optimized electrodes maintain capacity retention above 90% with consistent rate behavior. These observations reveal a direct link between densification, ion redistribution, and interfacial stability, indicating that ion transport can be regulated through manufacturing-controlled structural design. This work highlights a practical route for stabilizing solid-state interfaces through process-driven control of material architecture.</p>","PeriodicalId":8807,"journal":{"name":"Battery Energy","volume":"5 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bte2.70129","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148174058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accelerating Perovskite Solar Cell Development Through High-Throughput Technologies: Computational Simulation, Automated Experimentation, and Intelligent Integration","authors":"Yiming Wang,&nbsp;Ziwei Du,&nbsp;Yuhui Chen,&nbsp;Yicheng Qiu,&nbsp;Dong Yan,&nbsp;Bo Hou","doi":"10.1002/bte2.70127","DOIUrl":"https://doi.org/10.1002/bte2.70127","url":null,"abstract":"<p>Perovskite solar cells have emerged as promising candidates for next-generation photovoltaics. However, optimizing their efficiency and long-term stability is complicated by the vast parameter space involving composition, processing, and device architecture, and so on. Conventional trial-and-error approaches are labor-intensive and often inefficient for navigating these complex multidimensional interactions. Consequently, the field is shifting toward high-throughput (HT) data-driven methodologies capable of accelerating the development cycle. This review highlights recent progress in HT computational and experimental strategies, along with their synergistic integration. Regarding computational efforts, we summarize the use of density functional theory and machine learning to identify single, double, and derivative perovskite candidates, as well as emerging techniques in literature data mining. We also discuss automated experimental platforms utilizing automatic processing and combinatorial characterization to optimize material compositions, device fabrication processes, and operational stability. Furthermore, we examine the integration of these domains through closed-loop workflows that combine computational prediction with automated experimentation to establish intelligent prediction, fabrication, and validation cycles. Finally, we provide an outlook on prevailing challenges regarding data acquisition, machine learning integration, HT platform infrastructure, and multi-modal data processing, alongside potential solutions for achieving fully autonomous material discovery and device optimization.</p>","PeriodicalId":8807,"journal":{"name":"Battery Energy","volume":"5 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bte2.70127","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148174715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chemically Self-Powered Pre-Activation Strategy for Catalytic Purification of Lithium-Ion Battery Thermal Runaway Off-Gas","authors":"Ruijian Tang,&nbsp;Zhiqiang Wang,&nbsp;Ningqi Sun,&nbsp;Chuanzhao Zhang,&nbsp;Xingyu Zhang,&nbsp;Shiqing Wang,&nbsp;Lin Lin,&nbsp;Ziyi Li","doi":"10.1002/bte2.70121","DOIUrl":"https://doi.org/10.1002/bte2.70121","url":null,"abstract":"<p>During lithium-ion battery thermal runaway, oxygen-depleted, highly concentrated flammable fumes are released, posing a significant challenge to safety control. Catalytic oxidation requires both sufficient O₂ and elevated temperatures for activation. However, thermal runaway off-gas is inherently oxygen-free, creating a fundamental paradox: direct air supply cools the gas below activation threshold, while pre-heating demands external energy input. To address this issue, this study proposes a chemically self-powered pre-activation strategy based on both O₂ and heat supply. By placing superoxides upstream of the catalyst and utilising their exothermic reaction with CO₂ in the fumes, the necessary O₂ and reaction heat were released during the initial stage of catalytic oxidation. Simultaneously, a blower is introduced to provide a continuous O₂ supply for subsequent sustained oxidation. This strategy achieves purification efficiencies exceeding 87% for both H₂ and CO throughout the thermal runaway event with zero open flame occurrence and outlet temperatures below 100°C, ensuring safe discharge. This study provides a viable technical pathway for the post-treatment of battery thermal runaway emissions, eliminating dependency on external heating or compressed oxygen supplies.</p>","PeriodicalId":8807,"journal":{"name":"Battery Energy","volume":"5 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bte2.70121","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148174682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":8807,"journal":{"name":"Battery Energy","volume":"5 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148096772","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":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":8807,"journal":{"name":"Battery Energy","volume":"5 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148096771","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":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":8807,"journal":{"name":"Battery Energy","volume":"5 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148088684","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}