Reliable Storage Research Articles

Understanding the Crystal Chemistry of Phosphate Cathode Materials

Thermal batteries are primary reserve batteries that can achieve high power output in a short period of time by melting an insulating salt electrolyte with a pyrotechnic heat source and converting it into a highly conductive eutectic salt electrolyte. The thermal battery exhibits no self-discharge before activation, and the initial capacity of the thermal battery is maintained after long-term storage. Thermal batteries are an attractive option for emergency power supplies in aircraft, ejector seats, space landings and helicopters due to their outstanding robustness, high reliability, and long-term storage properties.FeS2 or CoS2 are the most common cathode materials for thermal batteries.1 However, their high cost and relatively low discharge voltage makes it desirable to find new materials that have higher voltage discharges, higher specific capacities, low cost and that are environmentally friendly. Polyanion cathode materials have attracted much attention in the field of both Li-ion and Na-ion batteries,2–4 as they can be regarded as low-cost materials and environmentally friendly. However, to the best of our knowledge, there have been no studies on polyanion cathode materials for thermal batteries. These materials are formed by tetrahedral units (XO4)n- (X = P, S, Si or B) bonded to MO6 polyhedra (M = transition metal). The tetrahedral anion presents a very strong covalent bond between X-O, giving rise to higher voltages versus Li+/Li or Na+/Na via the inductive effect and their very stable framework and open structure facilitates ion diffusion. Thus, polyanion materials present high structural stability and enable the tuning of the operating potential, making them an excellent choice for developing new cathode materials for thermal batteries. Here we report some of our latest work on the synthesis, structure and electrochemistry of polyanionic cathode materials for thermal batteries. 1 R. Li, W. Guo and Y. Qian, Front. Chem., 2022, in press, doi: 10.3389/fchem.2022.832972 2 Z. Gong and Y. Yang, Energy Environ. Sci., 2011, 4, 3223–3242. 3 C. Masquelier and L. Croguennec, Chem. Rev., 2013, 113, 6552–6591. 4 Q. Ni, Y. Bai, F. Wu and C. Wu, Adv. Sci., 2017, 4, 1600275.

Sodium Penetration in Nasicon Solid Electrolytes Under High Current

High conductivity solid electrolytes, such as NaSICON, are poised to play an increasingly important role in safe, reliable battery-based energy storage, enabling a new class of sodium-based batteries. Coupled demands of high current densities (≥0.1 A cm-2) and low temperature (<200 °C) operation, combined with increased discharge times for long duration storage (>12 h), challenge the limitations of solid electrolytes. Here, we explore the penetration of sodium into NaSICON at 0.1 A cm-2 in a symmetric molten sodium cell. Previous studies of β’’-alumina proposed that Poiseuille pressure-driven cracking (Mode I) and low levels of electronic conductivity leading to ion-electron recombination (Mode II) can cause metal accumulation within solid electrolytes, but a comprehensive study at high current density is necessary. To understand and differentiate these modes in NaSICON, this work employs unidirectional galvanostatic testing of Na|NaSICON|Na symmetric cells at 0.1 A cm-2 over 23 1-hour intervals at 110 °C. While galvanostatic testing shows a relatively constant, yet increasingly noisy voltage profile, electrochemical impedance spectroscopy (EIS) between intervals reveals a significant decrease in cell impedance which can be correlated with sodium metal penetration, as observed in scanning electron microscopy (SEM). Significant sodium accumulation from the stripping-side electrode suggests that Mode II failure may be far more prevalent than previously considered. Further, these findings suggest that total charge transported per unit area (mAh cm-2), an important parameter for long duration storage, may be a more critical parameter than current density (mA cm-2) when examining solid electrolyte failure. Together, these results provide a better understanding of the limitations of NaSICON solid electrolytes under high current density and can guide the design of coatings to improve electrode-electrolyte interfaces.

Synthesis of Single Crystalline Spike Shaped Nano-Rod Structured Cathode for High Performance SIB

The increasing need for energy, the widespread adoption of electric vehicles and renewable energy storage systems, and the search for cost-effective, reliable energy storage options are all factors in the dynamic nature of the global energy landscape and energy storage industry. As more and more people switch to using electric vehicles and other kinds of renewable energy storage, there has been a corresponding increase in demand for LIBs all around the globe. Despite increasing demand, there are geopolitical and supply-chain risks as most LIBs are still manufactured in only a few countries, namely China, Japan, and South Korea. Sodium-ion batteries, also known as SIBs, have recently come to the forefront as a potentially advantageous candidate for the large-scale storage of electric energy due to the potential advantages of widespread availability and low cost of sodium resources. SIB research and development are still at an early stage, and there are few opportunities for their commercialization. SIBs do, however, confront a number of issues that need to be addressed, including as their short cycle life and rate capability, the restricted availability of high-performance materials, and the need for more research and development to maximize their performance and dependability. Nonetheless, tremendous progress has been made recently, and several businesses and research centers across the globe are attempting to enhance SIB technology. The high theoretical specific capacity and quantity of component elements make layered metal oxides suitable cathode materials for SIBs. In order to enhance their electrochemical performance, however, further exploration is required to deal with their drawbacks, such as limited rate capability and voltage fading. As the cathode materials play such a large role in determining the energy density of SIBs, the primary issue in developing high-energy SIBs is discovering cathode materials with plentiful active sites, high reaction potential, unhindered ionic channels, and stable structures. Tailoring the morphology of materials using nanostructure engineering opens up hitherto unimagined possibilities for exploiting the functional features such as enhanced electrode's specific surface area, decreased sodium-ion diffusion distance, and boost in electronic conductivity. This study demonstrates a quaternary 1D layered transition metal oxide-based cathode with a composition of Na0.67Fe0.25Mn0.5Ti0.2V0.05O2 synthesized by a facile sol-gel strategy. From the SEM results, it is seen that 1D spoke like nanorods are evolved with a tiny fraction of 3D hexagonal lattice which is due to the excessive presence of vanadium in the stoichiometry ratio of the composite. Such nanorod framework configuration facilitates large surface area in contact with the electrolyte that is suitable for charge migration and rapid diffusion of sodium ions through short solid-state route. The P2- Na0.67Fe0.25Mn0.5Ti0.2V0.05O2 microstructure, with its high crystallinity and nanorod structure, showed off a high specific capacity and outstanding rate capability which is visible through electrochemical analysis results.

Molten Sodium Penetration Through Solid-State Nasicon Electrolytes Under High Current

High conductivity solid electrolytes, such as NaSICON, are poised to play an increasingly important role in safe, reliable battery-based energy storage, enabling a new class of sodium-based batteries. Increasing demands of both high current densities (≥0.1 A cm-2) and low temperature (<200 °C) operation, coupled with increased discharge times for long duration storage (>12 h), challenge the limitations of solid electrolytes. Here, we explore the penetration of sodium into NaSICON at 0.1 A cm-2 in a symmetric molten sodium cell. Previous studies of β’’-alumina proposed that Poiseuille pressure-driven cracking (Mode I) and low levels of electronic conductivity leading to ion-electron recombination (Mode II) can cause metal accumulation within solid electrolytes, but a comprehensive study at high current density is necessary. To understand and differentiate these modes in NaSICON, this work employs unidirectional galvanostatic testing of Na|NaSICON|Na symmetric cells at 0.1 A cm-2 over 23 1-hour intervals at 110 °C. While galvanostatic testing shows a relatively constant, yet increasingly noisy voltage profile, electrochemical impedance spectroscopy (EIS) between intervals reveals a significant decrease in cell impedance which can be correlated with sodium metal penetration, as observed in scanning electron microscopy (SEM). Significant sodium accumulation from the stripping-side electrode suggests that Mode II failure may be far more prevalent than previously considered. Further, these findings suggest that total charge transported per unit area (mAh cm-2), an important parameter for long duration storage, may be a more critical parameter than current density (mA cm-2) when examining solid electrolyte failure. Together, these results provide a better understanding of the limitations of NaSICON solid electrolytes under high current density and can guide the design of coatings to improve electrode-electrolyte interfaces.

Investigation of Ultra-Low Temperature Li/CF x Batteries in the Liquefied Gas Electrolyte

Lithium-fluorinated carbon (Li/CFx) is one of the most promising chemistries to serve as a reliable high-energy density primary energy storage system in applications where rechargeability is not required. Though Li/CFx demonstrates high energy density (>2100 Wh kg–1) under ambient conditions, achieving such a high energy density when exposed to subzero temperatures remains challenging, particularly under high current density.Liquefied gas electrolytes (LGE) are regarded as one of the most promising electrolyte systems, offering excellent ionic conductivities at wide temperature ranges from -80 to + 60 oC due to low viscosity and low freezing point of gas molecules. Moreover, the LGE can significantly improve the capacity retention of Li-metal batteries operated at reduced temperatures.Here, we report a liquefied gas electrolyte with an anion-pair solvation structure based on dimethyl ether with a low melting point (−141 oC) and low viscosity (0.12 mPa×S, 20 oC), leading to high ionic conductivity (> 3.5 mS cm–1) between −70 and 60 oC. Besides that, through systematic X-ray photoelectron spectroscopy (XPS) integrated with transmission electron microscopy (TEM) characterizations, we evaluate the CFx interphase from the low-temperature discharge process. We conclude that the fast transport and anion-pairing solvation structure of the electrolyte bring about reduced charge transfer resistance at low temperatures, which resulted in significantly enhanced performance of Li/CFx cells (1690 Wh kg–1, −60 oC;1172 Wh kg–1, −70 oC based on active materials). Utilizing 50 mg cm-2 loading CFx electrodes, the Li/CFx displayed 1530 Wh kg–1 at −60 oC. This work provides insights into the electrolyte design that may overcome the operational limits of batteries in extreme environments.

(Invited) 2D Nitride Mxenes with Unusual Chemistries for Carbon-Neutral Energy

The large-scale shift towards renewable energy technology requires the ability to reliably convert and store electrochemical energy. This technology is still limited in terms of performance, cost, and/or ease of utilization. In recent years, two-dimensional (2D) materials have been explored as low-cost, high-performing catalysts and electrodes for the reliable conversion and storage of electrochemical energy. Of these 2D materials, a special class of carbides and nitrides, known as MXenes, have gained popularity due to their high tunability, conductivity, and high surface area-to-volume ratio. From these carbide and nitride MXenes, the nitrides have received less attention due to a lack of reliable synthesis methods, despite being theorized to outperform their carbide counterparts. In this presentation, I will present on the oxygen-assisted molten salt fluoride synthesis method developed in my group to produce phase-pure nitride MXenes. Along with this, I will provide evidence of the enhanced capabilities of the nitride family of MXenes compared to carbides, sulfides, and oxides, when applied in the nitrogen reduction reaction (NRR), hydrogen evolution reaction (HER), and supercapacitor applications. In each of these fields, the enhanced performance is investigated using in-situ/operando spectroelectrochemical techniques. I will wrap up by discussing the future directions in the field of MXenes that require further attention for the full exploitation of their properties in electrochemical energy storage and conversion systems to attain carbon-neutral energy.

3D Printing‐Directed Synergistic Design of High‐Performance Zinc‐Ion Hybrid Capacitors and Nanogenerators for All‐In‐One Self‐Powered Energy Wristband

AbstractAdvanced wearable self‐powered energy systems that simultaneously achieve energy harvesting and energy storage offer exciting opportunities for flexible electronics, information communication, and even intelligent environmental monitoring. However, building and integrating synergistic energy storage from energy harvester unit into a single power source is highly challenging. Herein, a unique 3D printing‐directed synergistic design of high‐performance zinc‐ion hybrid capacitors (ZIHCs) and triboelectric nanogenerators (TENGs) is proposed for the all‐in‐one self‐powered wearable energy wristband. With advanced ink design, high‐performance flexible ZIHCs are built up as the excellent energy storage unit with remarkable electrochemical behaviors and synergistic matching from TENGs. An exceptional device capacitance of 239.0 mF cm−2, moderate potential window, high‐rate capability, robust cycling stability, and excellent flexibility are achieved. Intrinsic charge storage process is also revealed, further demonstrating the outstanding electrochemical stability of the in‐plane flexible ZIHCs. Moreover, using 3D printing‐directed synergistic design, an advanced all‐in‐one self‐powered energy wristband is developed, where an efficient harvesting of body vibration/movement energy and a reliable storage of harvested energy are simultaneously realized, representing a substantial step toward future practical applications in portable and wearable electronics.

ClimInonda: A Web Application for Climate Data Management: A Case Study of the Bayech Basin (Southwestern Tunisia)

The Bayech basin is located in southwestern Tunisia, a highly prone region to flooding risks. The Bayech basin is characterized by wadis that adopt a wide, sometimes ill-defined bed, often intersected by low-lying areas, resulting in a semi-endoreismo, greatly disrupting the flow regimes. The Bayech basin drains the slopes of the Nementchas and Tebessa mountains in Algeria, collecting water from the Medjen Bel Abbes plain in its middle course before crossing the Gafsa djebls chain at the Gafsa gap. In this basin, flooding is generally caused by high-intensity storms and is often relatively limited in extent. The slope shape and soil type can promote rapid surface runoff during intense rainfall. Therefore, the purpose of creating a web application, labeled ClimInonda, is to respond to a critical need of readily available information on climatic, environmental, and land use data collected in this basin and its morphometric characteristics using recent methods. The application consists of three essential components: the front-end, back-end, and database. The front-end focuses on the user interface, allowing users to interact with the application’s features. It communicates with the back-end through Hypertext Transfer Protocol requests for data processing and retrieval. The back-end handles the server-side operations, processes requests, and provides responses by retrieving data from the database. The database stores and manages the application’s data, ensuring integrity and efficient access. This modular architecture ensures a user-friendly interface, seamless data processing, and reliable data storage. Visualizations can include different types of data, such as satellite imagery, weather data, and terrain data, and can be displayed using various techniques, such as heat maps, contour maps, and 3D models, by providing easy-to-understand visualizations. ClimInonda is an application developed to expand upon existing platforms by providing a suite of exploratory data analysis features, including the ability to calculate the total precipitation depth recorded for any period, interpolate the annual recurrence interval for rainfall events, etc. A simple evaluation of the platform was performed to assess the usefulness and user satisfaction of the tool by professional users, and positive feedback was received. There is clear evidence that ClimInonda would provide the necessary basis for informed decision making by stakeholders and development agencies in arid and semi-arid Tunisia.

Blockchain-Based Secure Storage and Access Control Scheme for Supply Chain Ecological Business Data: A Case Study of the Automotive Industry.

The reliable circulation of automotive supply chain data is crucial for automotive manufacturers and related enterprises as it promotes efficient supply chain operations and enhances their competitiveness and sustainability. However, with the increasing prominence of privacy protection and information security issues, traditional data sharing solutions are no longer able to meet the requirements for highly reliable secure storage and flexible access control. In response to this demand, we propose a secure data storage and access control scheme for the supply chain ecosystem based on the enterprise-level blockchain platform Hyperledger Fabric. The design incorporates a dual-layer attribute-based auditable access control model for access control, with four smart contracts aimed at coordinating and implementing access policies. The experimental results demonstrate that the proposed approach exhibits significant advantages under large-scale data and multi-attribute conditions. It enables fine-grained, dynamic access control under ciphertext and maintains high throughput and security in simulated real-world operational scenarios.

Technical challenges and optimization of superconducting magnetic energy storage in electrical power systems

The main motivation for the study of superconducting magnetic energy storage (SMES) integrated into the electrical power system (EPS) is the electrical utilities' concern with eliminating Power Quality (PQ) issues and greenhouse gas emissions. This article aims to provide a thorough analysis of the SMES interface, which is crucial to the EPS. This article also discusses the development of SMES as a reliable energy storage system (ESS). Delivering outstanding performance to support the EPS in any upsetting scenario can help SMES achieve its goals. A few of the fascinating aspects of the application of SMES in this context are microgrids, transmission and distribution (T&D) grids, renewable energy sources (RES), and plug-in hybrid energy storage systems (HESS). However, power utilities must evaluate the effectiveness and enhance a better performance on PQ when presenting a highly efficient energy technology. This article examines the difficulties of integrating SMES into the electricity network as well as the performance effects of HESS and RES. Finally, by outlining the current state of knowledge and highlighting any gaps in the literature, the power protection strategies and difficulties for power networks using SMES are evaluated.

Perspective on imaging antiferromagnetic domains in thin films with the magneto-optical birefringence effect

Antiferromagnets are considered to be a promising host material for the next generation of magnetic storage due to their high stability and stray-field-free property. However, the absence of net magnetization in antiferromagnets renders conventional magnetometry ineffective, posing a great challenge in investigating microscopic antiferromagnetic (AFM) properties under magnetic or electric fields. In this Perspective, we provide an overview of various AFM domain imaging techniques and discuss the most promising optical imaging method based on the magneto-optical birefringence (MOB) effect. Additionally, we highlight recent advances in imaging AFM domains utilizing the MOB technique. This Perspective aims to provide a comprehensive review of the current research and potential future directions based on the MOB imaging technique, which could pave the way for the development of more efficient and reliable magnetic storage devices based on antiferromagnets.

Evaluating the Economic Potential for Geological Hydrogen Storage in Australia

Australia has ambitions to become a major global hydrogen producer by 2030. The establishment of Australia’s and the world’s hydrogen economy, however, will depend upon the availability of affordable and reliable hydrogen storage. Geological hydrogen storage is a practical solution for large scale storage requirements ensuring hydrogen supply can always meet demand, and excess renewable electricity can be stored for later use, improving electricity network reliability. Hosting thick, underground halite (salt) deposits and an abundance of onshore depleted gas fields, Australia is well placed to take advantage of geological hydrogen storage options to support its ambition of building a global hydrogen hub export industry. Using the Bluecap modelling software, we identify regions in Australia that are potentially profitable for large scale hydrogen production and storage. We use the results of this work to suggest high-potential regions for hydrogen development, supporting policymaker and investor decisions on the locations of new infrastructure and hydrogen projects in Australia.

A Review on Recent Progress Achieved in Boron Carbon Nitride Nanomaterials for Supercapacitor Applications

Supercapacitors are regarded as reliable energy storage devices to alleviate the energy crisis and environmental pollution. However, the relatively low capacitance and low energy density limit the practical application of supercapacitors. In this context, boron carbon nitride (BCN) nanomaterials have been extensively studied in the past decade due to their chemical and thermal stability, high mechanical strength, as well as tunable bandgap. The specific capacitance and energy density of supercapacitors can be significantly improved by fabricating nanostructured BCN-based electrode materials. In this review, the recent advances in the application of BCN-based materials in supercapacitors is presented. Strategies such as structure design, porosity/defect engineering, and hybrid nanostructure construction to boost the electrochemical performance of BCN-based materials are provided and, finally, promising research directions for novel energy storage materials are proposed.

PdNi biatomic clusters from metallene unlock record-low onset dehydrogenation temperature for bulk-MgH2.

Hydrogen storage has long been a priority on the renewable energy research agenda. Due to its high volumetric and gravimetric hydrogen density, MgH2 is a desirable candidate for solid-state hydrogen storage. However, its practical use is constrained by high thermal stability and sluggish kinetics. Here, we report PdNi bilayer metallenes as catalysts for hydrogen storage of bulk-MgH2 near ambient temperature. Unprecedented 422 K beginning dehydrogenation temperature and up to 6.36wt.% reliable hydrogen storage capacity were achieved. Fast hydrogen desorption was also provided by the system (5.49wt.% in 1h, 523 K). The in-situ generated PdNi alloy clusters with suitable d-band centers were identified as the main active sites during the de/re-hydrogenation process by AC-TEM and theoretical simulations, while other active species including Pd/Ni pure phase clusters and Pd/Ni single atoms obtained via metallene ball milling, also enhance reaction. These findings present fundamental insights into active species identification and rational design of highly efficient hydrogen storage materials. This article is protected by copyright. All rights reserved.

SWEP-RF: Accuracy sliding window-based ensemble pruning method for latent sector error prediction in cloud storage computing

Latent sector errors (LSEs) in disk drives cause significant outages, data loss, and unreliability in large-scale cloud storage systems, posing not only technical challenges but also environmental concerns in the context of carbon recycling. Predicting LSEs can help avoid these problems and improve cloud reliability, while also contributing to a more sustainable cloud infrastructure. Ensemble classifiers typically outperform individual classifiers for LSE prediction with high accuracy but can lead to underfitting and incurring additional computational cost, complexity, and time and memory consumption. This research addresses this challenge by proposing a twofold solution: optimizing the ensemble diversity of the resulting Random Forest (RF) classifier through accuracy sliding window-based ensemble pruning (SWEP-RF) and using this pruned ensemble to predict LSEs in cloud storage. By effectively predicting and mitigating LSEs, this approach reduces unnecessary energy consumption and carbon emissions associated with data recovery and reprocessing, aligning with carbon recycling goals. SWEP-RF maximizes its lower margin distribution to adapt the RF prediction performance and produce a strong-performing and effective subensemble, further enhancing the overall energy efficiency of cloud systems. Our approach also reduces ensemble size while maintaining high prediction accuracy, leading to more sustainable resource utilization. We evaluate our algorithm using datasets from Baidu Inc and Backblaze datacenters. Experimental results demonstrate that our approach achieves over 98.6% prediction accuracy, a low false alarm rate (FAR) of 0.003%, and extended meantime to data loss (MTTDL) with lead time in advance (LTA) of up to 383.4 Hrs. and 474.3 Hrs., respectively. SWEP-RF outperforms classical models and current state-of-the-art techniques in prediction accuracy, FAR, MTTDL, processing time, memory consumption, and cloud availability, highlighting its significance in not only enhancing cloud storage reliability but also reducing the carbon footprint of cloud services. Our method is a promising solution for enhancing cloud storage reliability through proactive LSE prediction, while addressing the urgent need for sustainable practices and carbon recycling in cloud computing.

Disruption mitigation in the semiconductors supply chain by using public blockchains

Supply chain management has become increasingly complex, leading to information loss and delayed transmission, exacerbating the bullwhip effect. Furthermore, the need for more reliable information storage, traceability, and accountability has slowed supply chain management. In this context, blockchain technology (BCT) solves the bullwhip effect problem, as it supports distributed networking, information synchronization among nodes, digital encryption, traceable information, and unchangeable block content. This paper proposes using public blockchain to solve the bullwhip effect problem in the supply chain (SC), which has yet to be discussed in published academic research papers. To this end, a framework has been developed to determine the readiness of a supply chain for blockchain adoption. This framework includes a checklist to evaluate the motivation, timing, and appropriate platform for adopting blockchain. The framework has been validated using a case study of personal computer devices, which were affected by the Covid-19 pandemic and resulted in semiconductors supply chain disruption. The study involved polling four executives The study involved polling four executives (of large organizations in Egypt and some Middle Eastern countries) representing different stages in the supply chain, they are retail, distribution, manufacturing, and supply. The results showed that while the executives recognized the benefits of adopting blockchain, they were still determining if it was the right time for adoption and did not see the technology ready for their supply chains. Finally, some public blockchain platforms were introduced to help businesses choose the most suitable platform for adoption.

Thermally Driven Multilevel Non-Volatile Memory with Monolayer MoS2 for Brain-Inspired Artificial Learning.

The demands of modern electronic components require advanced computing platforms for efficient information processing to realize in-memory operations with a high density of data storage capabilities toward developing alternatives to von Neumann architectures. Herein, we demonstrate the multifunctionality of monolayer MoS2 memtransistors, which can be used as a high-geared intrinsic transistor at room temperature; however, at a high temperature (>350 K), they exhibit synaptic multilevel memory operations. The temperature-dependent memory mechanism is governed by interfacial physics, which solely depends on the gate field modulated ion dynamics and charge transfer at the MoS2/dielectric interface. We have proposed a non-volatile memory application using a single Field Effect Transistor (FET) device where thermal energy can be ventured to aid the memory functions with multilevel (3-bit) storage capabilities. Furthermore, our devices exhibit linear and symmetry in conductance weight updates when subjected to electrical potentiation and depression. This feature has enabled us to attain a high classification accuracy while training and testing the Modified National Institute of Standards and Technology datasets through artificial neural network simulation. This work paves the way toward reliable data processing and storage using 2D semiconductors with high-packing density arrays for brain-inspired artificial learning.

Recent Advances in Rechargeable Metal-CO2 Batteries with Nonaqueous Electrolytes.

This review article discusses the recent advances in rechargeable metal-CO2 batteries (MCBs), which include the Li, Na, K, Mg, and Al-based rechargeable CO2 batteries, mainly with nonaqueous electrolytes. MCBs capture CO2 during discharge by the CO2 reduction reaction and release it during charging by the CO2 evolution reaction. MCBs are recognized as one of the most sophisticated artificial modes for CO2 fixation by electrical energy generation. However, extensive research and substantial developments are required before MCBs appear as reliable, sustainable, and safe energy storage systems. The rechargeable MCBs suffer from the hindrances like huge charging-discharging overpotential and poor cyclability due to the incomplete decomposition and piling of the insulating and chemically stable compounds, mainly carbonates. Efficient cathode catalysts and a suitable architectural design of the cathode catalysts are essential to address this issue. Besides, electrolytes also play a vital role in safety, ionic transportation, stable solid-electrolyte interphase formation, gas dissolution, leakage, corrosion, operational voltage window, etc. The highly electrochemically active metals like Li, Na, and K anodes severely suffer from parasitic reactions and dendrite formation. Recent research works on the aforementioned secondary MCBs have been categorically reviewed here, portraying the latest findings on the key aspects governing secondary MCB performances.

A Secured Data Storage in Cloud Computing by Using Block Design Based Key Agreement

Cloud computing has emerged as a dominant paradigm for storing and accessing data. In group data sharing scenarios, where multiple users collaborate and exchange sensitive information in the cloud, ensuring secure and efficient key agreement becomes crucial. This paper presents a comprehensive analysis of key agreement mechanisms for group data sharing in cloud computing environments. We explore various cryptographic techniques and protocols specifically designed for establishing secure communication channels among group members. The paper discusses the challenges associated with key agreement in the cloud, proposes potential solutions, and provides insights into the implementation and evaluation of such mechanisms. The proposed framework aims to protect data confidentiality, integrity, and availability, ensuring a robust and reliable cloud storage environment. We explore various cryptographic techniques, including encryption, key management, and authentication mechanisms, and discuss their application in securing cloud-based data storage. The framework addresses common security threats and provides guidelines for implementing a secure cloud storage solution.

Early prediction of remaining useful life for lithium-ion batteries based on CEEMDAN-transformer-DNN hybrid model

A reliable and safe energy storage system utilizing lithium-ion batteries relies on the early prediction of remaining useful life (RUL). Despite this, accurate capacity prediction can be challenging if little historical capacity data is available due to the capacity regeneration and the complexity of capacity degradation over multiple time scales. In this study, data decomposition, transformers, and deep neural networks (DNNs) are combined to develop a model of RUL prediction for lithium-ion batteries. Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is used for battery capacity sequential data to account for the capacity regeneration effect. The transformer networks are leveraged to predict each component of capacity regeneration thus improving the model's ability to handle long sequences while reducing the amount of data. The global degradation trend is predicted using a deep neural network. We validated the early prediction performance of the model using two publicly available battery datasets. Results show that the prediction model only uses 25%-30% data to achieve high accuracy. In the two public data sets, the RMSE errors were 0.0208 and 0.0337, respectively. A high level of accuracy is achieved with the model proposed in this study, which is based on fewer capacity data.