An Intrinsically Nonflammable Electrolyte for Prominent-Safety Lithium Metal Batteries with High Energy Density and Cycling Stability

Nex-generation high-energy-density storage battery, assembled with lithium (Li)-metal anode and nickel-rich cathode, puts forward urgent demand for advanced electrolytes that simultaneously possess high security, wide electrochemical window, and good compatibility with electrode materials. Herein an intrinsically nonflammable electrolyte is designed by using 1 M lithium difluoro(oxalato)borate (LiDFOB) in triethyl phosphate (TEP) and N-methyl-N-propyl-pyrrolidinium bis(trifluoromethylsulfonyl)imide [Pyr₁₃][TFSI] ionic liquid (IL) solvents. The introduction of IL can bring plentiful organic cations and anions, which provides a cation shielding effect and regulates the Li⁺ solvation structure with plentiful Li⁺-DFOB⁻ and Li⁺-TFSI⁻ complexes. The unique Li⁺ solvation structure can induce stable anion-derived electrolyte/electrode interphases, which effectively inhibit Li dendrite growth and suppress side reactions between TEP and electrodes. Therefore, the LiNi_0.9Co_0.05Mn_0.05O₂ (NCM90)/Li coin cell with this electrolyte can deliver stable cycling even under 4.5 V and 60 °C. Moreover, a Li-metal battery with thick NCM90 cathode (≈ 15 mg cm⁻²) and thin Li-metal anode (≈ 50 µm) (N/P ≈ 3), also reveals stable cycling performance under 4.4 V. And a 2.2 Ah NCM90/Li pouch cell can simultaneously possess prominent safety with stably passing the nail penetration test, and high gravimetric energy density of 470 Wh kg⁻¹ at 4.4 V.     

Mitigating Surface Deficiencies of Perovskite Single Crystals Enables Efficient Solar Cells with Enhanced Moisture and Reverse-Bias Stability

Metal halide perovskite single crystals are promising for diverse optoelectronic applications due to their outstanding properties. In comparison to the bulk, the crystal surface suffers from high defect density and is moisture sensitive; however, surface modification strategies of perovskite single crystals are relatively deficient. Herein, solar cells based on methylammonium lead triiodide (MAPbI₃) thin single crystals are selected as a prototype to improve single-crystal perovskite devices by surface modification. The surface trap passivation and protection against moisture of MAPbI₃ thin single crystals are achieved by one bifunctional molecule 3-mercaptopropyl(dimethoxy)methylsilane (MDMS). The sulfur atom of MDMS can coordinate with bare Pb²⁺ of MAPbI₃ single crystals to reduce surface defect density and nonradiative recombination. As a result, the modified devices show a remarkable efficiency of 22.2%, which is the highest value for single-crystal MAPbI₃ solar cells. Moreover, MDMS modification mitigates surface ion migration, leading to enhanced reverse-bias stability. Finally, the cross-link of silane molecules forms a protective layer on the crystal surface, which results in enhanced moisture stability of both materials and devices. This work provides an effective way for surface modification of perovskite single crystals, which is important for improving the performance of single-crystal perovskite solar cells, photodetectors, X-ray detectors, etc.     

A survey on deploying mobile deep learning applications: A systemic and technical perspective

With the rapid development of mobile devices and deep learning, mobile smart applications using deep learning technology have sprung up. It satisfies multiple needs of users, network operators and service providers, and rapidly becomes a main research focus. In recent years, deep learning has achieved tremendous success in image processing, natural language processing, language analysis and other research fields. Despite the task performance has been greatly improved, the resources required to run these models have increased significantly. This poses a major challenge for deploying such applications on resource-restricted mobile devices. Mobile intelligence needs faster mobile processors, more storage space, smaller but more accurate models, and even the assistance of other network nodes. To help the readers establish a global concept of the entire research direction concisely, we classify the latest works in this field into two categories, which are local optimization on mobile devices and distributed optimization based on the computational position of machine learning tasks. We also list a few typical scenarios to make readers realize the importance and indispensability of mobile deep learning applications. Finally, we conjecture what the future may hold for deploying deep learning applications on mobile devices research, which may help to stimulate new ideas.     

Research advances on blockchain-as-a-service: architectures,applications and challenges

Due to the complexity of blockchain technology, it usually costs too much effort to build, maintain and monitor a blockchain system that supports a targeted application. To this end, the emerging “Blockchain as a Service” (BaaS) makes the blockchain and distributed ledgers more accessible, particularly for businesses, by reducing costs and overheads. BaaS combines the high computing power of cloud computing, the pervasiveness of IoT and the decentralization of blockchain, allowing people to build their own applications while ensuring the transparency and openness of the system. This paper surveys the research outputs of both academia and industry. First, it introduces the representative architectures of BaaS systems and then summarizes the research contributions of BaaS from the technologies for service provision, roles, container and virtualization, interfaces, customization and evaluation. The typical applications of BaaS in both academic and practical domains are also introduced. At present, the research on the blockchain is abundant, but research on BaaS is still in its infancy. Six challenges of BaaS are concluded in this paper for further study directions.     

Evaluation Model of Click Rate of Electronic Commerce Advertising Based on Fuzzy Genetic Algorithm

Mobile Networks and Applications - In order to improve the ability of quantitative evaluation of e-commerce advertising click rate, a model of e-commerce advertising click rate evaluation based on...     

n型单晶硅片的电阻率和扩散方阻对IBC太阳电池电性能的影响

叉指背接触式(IBC)太阳电池因正面没有金属栅线遮挡,具有较高的短路电流,且组件外观更加美观。但由于IBC太阳电池正负电极在背面交叉式分布,在制备过程中需要采用光刻掩模技术进行隔离,难以实现大规模生产。采用Quokka软件仿真模拟了电阻率和扩散方阻对n型IBC太阳电池效率的影响,并对不同电阻率和扩散方阻的电池片进行了实验验证,从n型单晶硅片电阻率的选择和扩散工艺优化方面为IBC太阳电池的规模化生产提供了理论基础。实验结果表明,电阻率为3~5Ω·cm、扩散方阻为70Ω/时,小批量生产的IBC太阳电池平均光电转换效率可达23.73%,开路电压为693 mV,短路电流密度为42.44 mA/cm²,填充因子为80.69%。     

Multinuclear NMR study of lanthanide(III) complexes of 1,2-PDTA in aqueous solution

The complexation of lanthanide(III) cations with 1,2-propanediaminetetraacetate (1,2-PDTA) in aqueous solution has been investigated by ¹⁰Na, ³⁵Cl, ²H and ¹¹O NMR shift measurements. It has been shown that the contact shifts are dominant for ¹⁷O, ¹⁶Cl and ²H (only for the heavier lanthanide series) and the pseudocontact shifts are dominant for ²⁵Na. It is suggested that the 1,2-PDTA ligand is bound pentadentately via the two nitrogens and the three carboxylates for the lighter lanthanide complexes, hexdentately via the two nitrogens and the four carboxylates for the heavier ones. The numbers of the water coordinated were determined. The small amount of chloride anion in inner coordination sphere was observed.