Storage Structure Research Articles

A Universal Method for Regulating Carbon Microcrystalline Structure for High-Capacity Sodium Storage: Binding Energy As Descriptor.

Sodium-ion batteries (SIBs) are attracting worldwide attention due to their multiple merits including abundant reserve and safety. However, industrialization is challenged by the scarcity of high-performance carbon anodes with high specific capacities. Here, we report the metal-assisted microcrystalline structure regulation of carbon materials to achieve high-capacity sodium storage. Systematic investigations of in situ thermal-treatment X-ray diffraction and multiple spectroscopies uncover the regulation mechanism of constructing steric hindrance (C-O-C bonds) to restrain the aromatic polycondensation reaction. The carbon precursor of polycyclic aromatic hydrocarbon-type pitch contributes to a high carbon yield rate (40%) compared with those of resin and biomass precursors. The as-synthesized carbon materials deliver high capacities of up to 390 mAh g-1, surpassing many reported carbon anodes for SIBs. Through correlating specific capacity with ID/IG values in Raman spectra and theoretical calculation of carbon materials regulated by different metal elements (Mn, Nb, Ce, Cr, and V), we identify and propose the binding energy as the descriptor for characterizing the capability of regulating the carbon microcrystalline structure to promote sodium storage. This work provides a universal method for regulating the carbon structure, which may lead to the controlled design and fabrication of carbon materials for energy storage and conversion and beyond.

FE modeling of the reconstructed Bituminated radioactive waste storage of Ignalina NPP

Decommissioning of nuclear facilities is a complex of various activities strongly related to safety. In 2004 and 2005, both reactors of Ignalina NPP were closed. One of the tasks that must be solved is what to do with the radioactive waste storage facility (Ignalina AE Building 158). Possible solutions: – complete destruction of the radioactive waste storage with the need to empty the canyons and store the waste in a special place or, as an alternative, turning the storage into a repository. Converting storage to repository also has many different options. The installation of protective barriers of different thicknesses or even the construction of a sarcophagus is possible. The cheapest way to form a protective barrier on an existing building structure. The problem is the relatively high weight of the barrier structure, which must be supported by the existing building structure.The article presents an analysis of the durability of the structures of the radioactive waste storage, assessing the influence of the self-weight of the building's reinforced concrete structural elements and the mass of the bituminous radioactive waste stored in the canyons, as well as the effect of additional loads acting on the floor and roof of the first floor during the planned conversion of the storage facility into the repository. Numerical simulation was performed using ANSYS computer code and the results were compared with the relevant standards and norms in order to assess the building's ability to undergo such transformations.Spatial volumetric geometric and calculation models of the construction structures of the 158 building were created. These models have been modified after considering future changes during the transformation of the building into a repository. Perform calculations of the state of stresses and strains of the landfill under the load of the self-weight of the structural elements and the hydrostatic pressure of the bituminous waste. On the basis of the results of the calculations, conclusions were formulated about the level of load on the construction structures of the building and the margin under the current operating loads.The developed numerical models can be easily extended to evaluate the effects of new building elements and additional loads on structures (specifically walls and ceilings) after the transformation of a waste storage into a repository.The article presents not only the idea of reorganizing the waste storage structure to repository but also the methodology of modelling such a structure by assessing the age of the building's soil and additional loads. This methodology can be useful and applied to the closure of other nuclear power plants when it is necessary to turn the radioactive waste storage into a repository.

A new tree-based approach to mine sequential patterns

Generic sequential pattern mining problem aims to mine the set of sequential patterns from a sequential database that satisfies a minimum support or occurrence threshold constraint. The main challenges that affect the efficiency of a solution lie in reducing the pattern search space, early detecting the infrequent patterns, representing the database in an efficient format, etc. Also, additional challenges get included when the problem environment transitions from static to incremental database leading to not to re-mine but efficiently tracking the effect of the incremental portion over the complete updated database. In this article, we introduce a new tree-based solution to the sequential pattern mining problem, including two sets of novel solutions for static and incremental sequential databases. We propose two new structures, SP-Tree and IncSP-Tree, and design two efficient algorithms, Tree-Miner and IncTree-Miner to mine the complete set of sequential patterns from static and incremental databases respectively. The proposed novel structures provide an efficient manner to store the complete sequential database maintaining “build-once-mine-many” property and giving scope to perform interactive mining. Additionally, we also design a new breath-first based support counting technique to efficiently identify the infrequent patterns at early stages and a new heuristic pruning strategy to reduce pattern search space. We also design a new pattern storage structure BPFSP-Tree to store the frequent patterns during successive iterations in incremental mining to reduce the number of database scans and to remove the infrequent patterns efficiently. A novel structure named Sequence Summarizer is also introduced to efficiently calculate and update the co-occurrence information of the items, especially in an incremental environment. Experimental results from various real-life and synthetic datasets demonstrate the efficiency of our work in comparison with the related state-of-the-art approaches.

Management Information System Design Village Finance (case study of kelambir v kebun village)

Fund allocation for each village is adjusted to a number of criteria. The problem that arises is that the mechanism and use of funds have not been properly recorded. This problem can be overcome by presenting good and transparent information, for this reason a village fund information system is needed for managing village funds using the waterfall method. This information system is very useful for monitoring village funds and absorption carried out by each village in real time, as well as providing information for the village head and policy makers in Klambir Lima Kebun Village to determine a policy. The system built is a system that discusses the Information System for managing village funds in Klambir Lima Kebun Village, a system design model in the form of a use case diagram, data storage structure and application display design using the PHP programming language and a database using MySQL, where the system has been built, the village officials of the five plantations will find it easier to process managing village funds and village fund allocation so that it is faster, more effective, effective, efficient and transparent. This system can handle the process of filling in data, changing data, deleting data, searching for data and reporting money data as well as providing information on village fund management in the village of Kelambir Lima Kebun.

Vertically grown MoS2 nanosheets on graphene with defect-rich structure for efficient sodium storage

Vertically grown MoS2 nanosheets on graphene with defect-rich structure for efficient sodium storage

Experimentally validated numerical analyses on the seismic responses of extra-large LNG storage structures

Extra-large liquefied natural gas (LNG) storage tanks are comprised by a steel inner tank and an outer protective tank of prestressed reinforced concrete (PRC), both being very thin. These important lifeline infrastructures are prone to damage and even failure under earthquake during their service life. Convincing numerical simulation, verified by shake table tests, is a feasible tool to quantify the seismic responses and to mitigate the potential damage/failure of LNG storage structures. This work addresses systematically the three-dimensional finite element (FE) modeling, experimental validation and numerical simulations of such structures, with the soil–pile interaction of the foundation, the fluid–structure interaction of the inner tank and damage of the outer tank all properly accounted for. For the sake of computational efficiency with no loss of too much precision, the soil–pile interaction is described by the mass–damper–spring model, and the fluid–structure interaction by the mass–spring model with both the convective and impulsive components accounted for. Moreover, the nonlinear mechanical behavior of concrete is considered by the damaged-plasticity model regularized with the fracture energy. The concrete–steel interaction in PRC is practically dealt with by modifying the constitutive relations of concrete and steel rebars/tendons properly with the equilibrium and compatibility conditions accounted for. The FE modeling strategy is validated against the recently conducted benchmark shaking table test of a scaled extra-large LNG storage structure. The capability in capturing the overall dynamic responses, e.g., the hydrodynamic pressure and structural vibrations under seismic actions, etc., is sufficiently verified. Finally, the dynamic responses and structural reliability of an extra-large LNG storage tank under deterministic and stochastic seismic actions are numerically studied in details.

Tuning the porous graphene interlayer structure for compact energy storage towards high volumetric performance of Zn-ion capacitor

For most consumer electronics, the volumetric performance of energy storage devices is usually more significant than traditional gravimetric performance. Zinc-ion capacitors (ZICs) are regarded as one of the most promising energy storage devices with high energy and power density. However, the low volumetric performance of the cathode is a serious problem that hinders its practical application. Herein, in this work, a compact freestanding graphene film was designed by tuning the interlayer structure of flame reduced graphene oxide sheets (FRGO) using graphene oxides (GO) via a self-assembly strategy. When the mass ratio of FRGO and GO is 75%:25%, the optimum of graphene film between density and electrochemical performance was achieved. The graphene film owns a bulk density of 0.82 g cm−3 and precisely regulated abundant mesoporous around 3.8 nm, which provides more active sites for ion storage. Profiting from the pseudocapacitance reaction between C=O and Zn2+, the compact graphene film with a thickness of 35 μm as ZICs cathode can deliver a high volumetric energy density of 113.1 Wh L-1 and outstanding gravimetric performance of 118.7 Wh kg−1 with a bulk density of 0.95 g cm−3, achieving the balance of the gravimetric and volumetric characteristics. The ZIC also presents a maximum volumetric power density of 21.2 kW L-1 at 7.9 Wh L-1 and 96.4% capacity retention after 8000 cycles, revealing excellent compact energy storage and cyclability. Moreover, the soft-package ZIC devices present admirable scalability, further exposing the application potential of the compact graphene film in the ZIC field.

Private Set Intersection Based on Lightweight Oblivious Key-Value Storage Structure

At this stage, the application of Private Set Intersection (PSI) protocols is essential for smart homes. Oblivious Key-Value Stores (OKVS) can be used to design efficient PSI protocols. Constructing OKVS with a cuckoo hashing graph is a common approach. It increases the number of hash functions while reducing the possibility of collisions into rings. However, the existing OKVS construction scheme requires a high time overhead, and such an OKVS applied to PSI protocols would also have a high communication overhead. In this paper, we propose a method called 3-Hash Garbled Cuckoo Graph (3H-GCG) for constructing cuckoo hash graphs. Specifically, this method handles hash collisions between different keys more efficiently than existing methods, and it can also be used to construct an OKVS structure with less storage space. Based on the 3H-GCG, we design a PSI protocol using the Vector Oblivious Linear Evaluation (VOLE) and OKVS paradigm, which achieves semi-honest security and malicious security. Extensive experiments demonstrate the effectiveness of our method. When the set size is 218–220, our PSI protocol is less computationally intensive than other existing protocols. The experiments also show an increase in the ratio of raw to constructed data of about 7.5%. With the semi-honest security setting, our protocol achieves the fastest runtime with the set size of 218. With malicious security settings, our protocol has about 10% improvement in communication compared with other existing protocols.

Mechanical properties of coal-rock combined bodies under the action of ScCO2: A study of damage and failure mechanism

Injecting CO2 into deep unrecoverable coal seams can help achieve carbon sequestration targets and improve the coalbed methane output rate. However, CO2 reaches a supercritical in situ storage state that impacts the coal storage structure. Based on the independently developed ScCO2 soak system, RFPA3D numerical simulation, and theoretical calculations, the mechanical damage characteristics and failure mechanism of RCR samples with three types of coal seam thicknesses and three types of top and bottom plate lithologies under the action of ScCO2 are investigated. The study reveals that (1) under the action of ScCO2, with the increase in the coal thickness, the deterioration degree of compressive strength and modulus of elasticity of the RCR combined body gradually increases and decreases, respectively, (2) ScCO2 will promote the plastic failure of the coal mass and exacerbate the tendency of the RCR combined body to change from tensile splitting failure to shear plastic failure, and the degree of plastic failure of the RCR combined body has a positive correlation with the coal thickness and the rock-coal strength ratio, and (3) ScCO2 accelerates the failure of the RCR combined body, and the coal mass enters the plastic failure stage earlier, while the rock mass ends the elastic strain energy accumulation and unloads and releases energy earlier, reducing the accumulation and release of energy in the combined body. The research results can provide a theoretical reference for the geological storage of CO2 deep inaccessible coal seams.

Graduate Student Source Analysis Method Based on Annual Report Data of Degree-Granting Information

Based on the annual data of degree-granting information accumulated by degree-granting institutions, this paper analyzes the storage structure of the database, excavates the critical information in the degree-granting information data structure, and puts forward a multi-dimensional graduate source analysis method, such as first-choice admission rate, the admission rate of recommended students, pre-graduation institution type, residential registration origin and types of colleges and universities transferring students. The limitation of using a single index of first choice admission rate to evaluate the quality of student source is improved.

One-Step Synthesis of Multifunctional Bacterial Cellulose Film-Based Phase Change Materials with Cross-Linked Network Structure for Solar-Thermal Energy Conversion, Storage, and Utilization.

As one of the important directions of solar energy utilization, the construction of composite photothermal phase change materials (PCM) with reasonable network support and low leakage in the simple method is important to solve the transient availability of solar energy and achieve long-lasting energy output. Here, a multifunctional silylated bacterial cellulose (BC)/hydroxylated carbon nanotube (HCNT)/polyethylene glycol (PEG) (SBTP) photothermal film-based PCM with cross-linked network structure is prepared by simple one-step synthesis. The formation of the cross-linked network structure achieves the enhancement of BC support network, prominent dispersion of HCNT and the direct introduction and perfect interlocking of PEG. Therefore, the optimal SBTP film exhibits high thermal enthalpy of 145.1Jg-1, enthalpy efficiency of over 94%, robust shape stability and low leakage of <1.2%. It also displays high photothermal conversion of over 80°C, photothermal storage of 394 sg-1 and excellent stability. Thus, it can demonstrate a maximum output voltage of 423mV and high power density of 30.26Wm-2 under three solar irradiations when applied in the solar-thermal-electric energy conversion field. Meanwhile, it also can apply in the thermal management of solar cell and light-emitting diode (LED) chip, and convert the waste heat into electricity, demonstrating multi-scene application capability.

F127 assisted fabrication of Ge/rGO/CNTs nanocomposites with three-dimensional network structure for efficient lithium storage

To solve the volume expansion and poor electrical conductivity of germanium-based anode materials, Ge/rGO/CNTs nanocomposites with three-dimensional network structure are fabricated through the dispersion of polyethylene-polypropylene glycol (F127) and reduction of hydrogen. An interesting phenomenon is discovered that F127 can break GeO2 polycrystalline microparticles into 100 nm nanoparticles by only physical interaction, which promotes the uniform dispersion of GeO2 in a carbon network structure composed of graphene (rGO) and carbon nanotubes (CNTs). As evaluated as anode material of Lithium-ion batteries, Ge/rGO/CNTs nanocomposites exhibit excellent lithium storage performance. The initial specific capacity is high to 1549.7 mAh/g at 0.2 A/g, and the reversible capacity still retains 972.4 mAh/g after 100 cycles. The improved lithium storage performance is attributed to that Ge nanoparticles can effectively slow down the volume expansion during charge and discharge processes, and three-dimensional carbon networks can improve electrical conductivity and accelerate lithium-ion transfer of anode materials.

Efficient-thermal conductivity, storage and application of bionic tree-ring composite phase change materials based on freeze casting

Thermal energy storage, management, and utilization with phase change materials have received increasing attention in industrial fields such as photo-thermal-electric conversion and integrated circuit cooling. However, the inherent low thermal conductivity and melting leakage are long-term bottlenecks that prevent their widespread commercial application. Herein, a novel composite phase change material (CPCM) with high-thermal conductivity and stability based on bionic porous SiC skeleton is proposed, which is oriented by optimized freeze casting to design vertical tree-ring porous structure for fast photo-thermal conversion and storage. The results demonstrate the novel bionic SiC skeleton can regulate the porosity (50%–70%) by changing the slurry solid content, which also exhibits good anisotropic thermal conductivity. SiC/paraffin CPCM's mass and latent enthalpy of attenuated merely by 0.87% and 1.5% after 200 repeated heat storage/exhaustion cycles, confirming its excellent longevity and stability. The high-temperature SiC/NaCl-MgCl2-KCl CPCM has a thermal conductivity of 12.54 W‧m−1‧K−1, an effective thermal-storage density per production cost of 74.5 kJ‧CNY-1, and a high photo-thermal storage efficiency of 91.8%. Finally, a variable-power chip dissipation experimental system was built to verify the thermal performance of the CPCM module in the paper. It could dissipate heat rapidly and maintain a lower temperature. This work provides a promising strategy for photo-thermal utilization and thermal management of electronic devices.

An AER-based spiking convolution neural network system for image classification with low latency and high energy efficiency

Spiking neural network is used to solve the problems of power consumption and computation requirement of the traditional artificial neural network. This paper proposes an event-driven multilayer spiking convolutional neural network (SCNN) hardware system for the image classification task. The proposed hardware system consists of a microcontroller unit (MCU) and an SCNN processor. Input images are temporally encoded to spike trains in the form of address event representation (AER) by MCU, and sent to the SCNN processor to execute AER-based spike-centric convolution in order to reduce redundant operations and get the classification result efficiently. By rearranging the storage structure of weights of synapses and membrane potential (MP) of spiking neurons, multi-channel parallel MP updating is realized to reduce latency. In addition, FIFOs are inserted between the spiking layers to construct a pipeline structure. The hardware architecture of the proposed system is implemented on the Xilinx ZYNQ-7000 platform. At the operating frequency of 100 MHz, the proposed SCNN processor has a speed of 400classifications/s and 80uJ/inference.

WITHDRAWN: Efficient fragmentation and allocation on clustering in distributed environment (FACE)

Distributed data processing systems require a reliable storage structure that ensures consistent, high-scale, and scalable data access for all users. Data fragmentation and subsequent allocation are important aspects of a flexible distributed database system. Existing techniques may result in significant data loss while performing data allocation and fragmentation. To overcome these issues a novel fragmentation and Allocation on Clustering in Distributed Environment (FACE) is proposed for reliable storage with scalable data access for all users. Initially, the user query is given to distributed database system (DDBS), then the query is fed to the query parser. The query parser parses and converts a textual query into a query object. After parsing the query data, it is passed to the query optimizer, which optimizes the query to access the data more efficiently. In the next step, the query is fragmented using dual (horizontal and vertical) fuzzy C means clustering. In Dual fuzzy C means clustering, the vertical fragmentation focuses on clustering attribute values that are frequently accessed together, and horizontal fragmentation focuses on grouping records that meet data selection criteria. After fragmentation, the query is allocated using sequential rule mining, in which queries occur in sequential order. The allocated query is optimized using the Efficient Fragment Security (EFS) algorithm to normalize the parameters to achieve better results. The performance metrics of the proposed techniques are calculated based on Final Prediction Error (FPE), and Execution time. The proposed FACE achieves a lower execution time of the 1.56 s. The result shows that the proposed FACE decreases the overall execution time lower than the 4.70 s, 4.46 s, 3.3 Sec, and 3.14 s in MAPA, DMA, BBE, and RATS-HM respectively.

NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams

Existing Graph Neural Network (GNN) training frameworks have been designed to help developers easily create performant GNN implementations. However, most existing GNN frameworks assume that the input graphs are static, but ignore that most real-world graphs are constantly evolving. Though many dynamic GNN models have emerged to learn from evolving graphs, the training process of these dynamic GNNs is dramatically different from traditional GNNs in that it captures both the spatial and temporal dependencies of graph updates. This poses new challenges for designing dynamic GNN training frameworks. First, the traditional batched training method fails to capture real-time structural evolution information. Second, the time-dependent nature makes parallel training hard to design. Third, it lacks system supports for users to efficiently implement dynamic GNNs. In this paper, we present NeutronStream, a framework for training dynamic GNN models. NeutronStream abstracts the input dynamic graph into a chronologically updated stream of events and processes the stream with an optimized sliding window to incrementally capture the spatial-temporal dependencies of events. Furthermore, NeutronStream provides a parallel execution engine to tackle the sequential event processing challenge to achieve high performance. NeutronStream also integrates a built-in graph storage structure that supports dynamic updates and provides a set of easy-to-use APIs that allow users to express their dynamic GNNs. Our experimental results demonstrate that, compared to state-of-the-art dynamic GNN implementations, NeutronStream achieves speedups ranging from 1.48X to 5.87X and an average accuracy improvement of 3.97%.

Dynamic saturation area and water balance modelling of karstic basins

AbstractWater balance models are known as major tools for simulation of basin‐wide water cycle components. Considering the complexity of the runoff generation processes in karstic basins, it is crucial to bring the model processes closer to the physical reality of karstic springs and their contribution to runoff formation. One of the challenges in basin‐scale modelling of karstic basins is that the basin response to precipitation is highly influenced by the soil saturation condition and its seasonal variability. One way to address this challenge is to include a dynamic structure for the water balance model. In this research, the structure of SAM‐KARST water balance model for estimation of monthly streamflows in the outlet of karst basins was presented. Moreover, to better simulate the basin response fluctuations in different seasons, the SAMdyn‐KARST model with a dynamic storage structure was introduced and developed. The results of the SAMdyn‐KARST model were compared with the saturation area model (SAM) and SAM‐KARST models for the Shapur river basin in southwest of Iran. The results confirmed the importance of considering larger saturation storage in the karst basins. The case study results also showed that SAMdyn‐KARST outperformed SAM‐KARST model and provided higher accuracy in estimating seasonal variations of surface streamflows at the basin outlet.

Structural model and capacity determination of underground reservoir in goaf: a case study of Shendong mining area in China

The large-scale extraction of coal resources in the western mining areas of China has resulted in a significant loss of water resources, which is a challenge for coordinating resource extraction with ecological preservation in the mining areas. Although underground reservoir technology can effectively solve this problem, measuring the storage capacity of underground reservoirs through engineering experiments is costly and time-consuming. Currently, there is a lack of accurate, reliable, and low-cost theoretical calculation solutions, which greatly restricts the promotion and application of underground reservoir technology. The theoretical calculation methods for underground reservoir capacity were studied based on parameters from the Shendong mining area in China. A water storage structure model for coal mine underground water reservoirs was established, taking into account the settlement boundaries of the bedrock and loose layers in shallow coal seams, based on the key layer theory and the spatial structure model of the mining roof. The mathematical expression for the load on the coal-rock mass in the goaf was derived considering the rock breaking characteristics of the mining roof. The model determined the range of each water storage area, including the zone of loose body, zone of gradual load, and the compacted zone, based on the strength of the water storage capacity. The key parameters for calculating the water storage capacity were determined using a modified model for shallow thick loose layers and thin bedrock movement. Finally, a calculation method for the storage capacity was obtained. Based on the real data from the 22,615 working face of a mine in the Shendong mining area, the water storage capacity of the underground reservoir in the goaf was jointly calculated using FLAC3D, Surfer 12.0 and the proposed calculation method. The calculated water storage capacity was approximately 1.0191 million m3. Although this result was 2.20% smaller than the on-site water pumping experiment data, it still verifies the feasibility of the above calculation method for determining the water storage capacity of underground water reservoirs.

Effect of structural characteristics on the transport characteristics of solid particles in the thermal storage and release system of circulating fluidized bed

Coal-fired power generation stands as the most economically viable modulating power source in present-day China. It holds the potential to offer prospective solutions to the challenges posed by the rapid expansion of intermittent, unpredictable, and unstable renewable energy sources. Solid particle thermal storage technology emerges as an effective means to enhance the flexibility of coal-fired circulating fluidized bed power units. To attain an optimized structure for the solid particle thermal storage and release system in circulating fluidized bed units, experimental research was conducted on a 0.1 MWth circulating fluidized bed test platform. This study delved into the impact of ash storage bin geometries and the shapes of their feed-discharge valves on the control properties of solid particle transportation. The experimental outcomes reveal that employing inverted m-shaped valve and dual U-shaped valves for feed control, alongside U-shaped valves and N-shaped valves for discharge control, both enable efficient and rapid storage and release of solid particles within the circulating fluidized bed. Under similar air distribution conditions, the inverted m-shaped valve exhibits lower conveying energy consumption than the dual U-shaped valves, while the N-shaped valve excels in control characteristics over the U-shaped valve. Furthermore, the inverted m-shaped valve and the N-shaped valve demonstrate optimal overflow port heights, and the ash storage bin exhibits an optimum height-to-diameter ratio.

Advanced Multilayered Electrode with Planar Building Blocks Structure for High-Performance Lithium-Ion Storage.

To achieve the high-performance of lithium-ion battery, the optimization of electrode materials has generally been considered as the one of the important methods. But most of those works pay attention to the new materials preparation or interface modification rather than the structural innovation. Here, an advanced electrode (GDY/BP/GDY-E) with multilevel layered architecture constructed by planar building blocks stacking structure has been designed and fabricated to explore the structure design of the electrode. This new structure is assembled by graphdiyne (GDY) and black phosphorus (BP) in parallel to form a building block (GDY/BP/GDY). The electric fields between the two GDY sides of the planar building block structure contribute to the superior migration dynamics of lithium ions and desirable pseudocapacitance behavior. Meanwhile, the planar stacking structure of GDY/BP/GDY can efficiently inhibit volume expansion of BP and a series of parasitic reactions of electrolytes during the long-term cycling. The advanced GDY/BP/GDY-E exhibits excellent high-rate performance (1418.8 mAh g-1 at 0.1 A g-1 ) and cycling stability (391.7 mAh g-1 after 5000 cycles at 10 A g-1 ). Such structural design of electrode materials shows a new way to develop high-performance electrodes.