Theoretical investigation of intrinsic point defects and the oxygen migration behavior in rare earth hafnates

In this work, the composition-dependent point defect types and formation energies of RE₂Hf₂O₇ (RE = La, Ce, Pr, Nd, Pm, Sm, Eu and Gd) as well as the oxygen diffusion behavior are systematically investigated by first-principles calculations. The possible defect reactions and dominant defect complexes under stoichiometric and non-stoichiometric conditions are revealed. It is found that O Frenkel pairs are the predominant defect in stoichiometric pyrochlore hafnates. Hf-RE cation anti-site defects, accompanied by RE vacancies and/or oxygen interstitials, are stable in the non-stoichiometric case of HfO₂ excess. On the other hand, RE-Hf anti-site defects together with oxygen vacancies and/or RE interstitials are preferable in the case of RE₂O₃ excess. The energy barriers for the migration along the V_O48f - V_O48f pathway of pyrochlore hafnates were calculated to be between 0.81 eV and 0.89 eV. Based on these results, a defect engineering strategy is proposed and the pyrochlore hafnates investigated here are predicted to exhibit potential oxygen ionic conductivity.     

Eco-friendly and degradable red phosphorus nanoparticles for rapid microbial sterilization under visible light

Pathogens pose a serious challenge to environmental sanitation and a threat to public health.The frequent use of chemicals for sterilization in recent years has not only caused secondary damage to the environment but also increased pathogen resistance to drugs,which further threatens public health.To address this issue,the use of non-chemical antibacterial means has become a new trend for environmental disinfection.In this study,we developed red phosphorus nanoparticles(RPNPs),a safe and degradable photosensitive material with good photocatalytic and photothermal properties.The red phosphorus nanoparticles were prepared using a template method and ultrasonication.Under the irradiation of simulated sunlight for 20 min,the RPNPs exhibited an efficiency of 99.98%in killing Staphylococcus aureus due to their excellent photocatalytic and photothermal abilities.Transmission electron microscopy and ultraviolet–visible spectroscopy revealed that the RPNPs exhibited degradability within eight weeks.Both the RPNPs and their degradation products were nontoxic to fibroblast cells.Therefore,such RPNPs are expected to be used as a new type of low-cost,efficient,degradable,biocompatible,and eco-friendly photosensitive material for environmental disinfection.     

基于1D CNN与XGBoost的恶意代码纹理检测

恶意代码数量已经呈现爆炸式增长,对于恶意代码的检测防护显得尤为重要.近几年,基于深度学习的恶意代码检测方法开始出现,基于此,提出一种新的检测方法,将恶意代码二进制文件转化为十进制数组,并利用一维卷积神经网络(1 Dimention Convolutional Neural Networks,1D CNN)对数组进行分类和识别.针对代码家族之间数量不平衡的现象,该算法选择在分类预测上表现良好的XGBoost,并对Vision Research Lab中的25个不同恶意软件家族的9458个恶意软件样本进行了实验.实验结果表明,所提的方法分类预测精度达到了97％.     

The effect of alkali metal oxide on the properties of borosilicate fireproof glass: Structure,thermal properties,viscosity, chemical stability

The purpose of the current work was to research the effect of alkali metal oxide on the structure, thermal properties, viscosity and chemical stability in the glass system (R₂O–CaO–B₂O₃–SiO₂) systematically. Because the glass would emulsify when Li₂O was added to the glass batch, this article did not discuss Li₂O. The results showed that when the amount of Na₂O was less than 4 mol.%, there was a higher interconnectivity of borate and silicate sub-networks in glass, as more mixed Si–O–B bonds were present in glass. The glass samples exhibited excellent thermal properties and chemical stabilities. As the amount of Na₂O exceeded 4 mol.%, the interconnectivity of borate and silicate sub-networks was weakened. The thermal properties and chemical stabilities of the glass samples were reduced. The connectivity of the silicate sub-network was weakened slightly as the Na/K ratio varied, and the coefficient of thermal expansion (CTE) of the glass samples gradually increased, and the resistance to thermal shock (RTS) value gradually decreased. Moreover, the viscosity of the glass samples decreased with the ratio of Na/Si and Na/K increased.     

Enhanced electrochemical performance of LiNi0.8Co0.1Mn0.1O2 via titanium and boron co-doping

Titanium and boron are simultaneously introduced into LiNi_0.8Co_0.1Mn_0.1O₂ to improve the structural stability and electrochemical performance of the material. X-ray diffraction studies reveal that Ti⁴⁺ ion replaces Li⁺ ion and reduces the cation mixing; B³⁺ ion enters the tetrahedron of the transition metal layers and enlarges the distance of the [LiO₆] layers. The co-doped sample has spherical secondary particles with elongated and enlarged primary particles, in which Ti and B elements distribute uniformly. Electrochemical studies reveal the co-doped sample has improved rate performance (183.1 mAh·g^-1 at 1 C and 155.5 mAh·g^-1 at 10 C) and cycle stability (capacity retention of 94.7% after 100 cycles at 1 C). EIS and CV disclose that Ti and B co-doping reduces charge transfer impedance and suppresses phase change of LiNi_0.8Co_0.1Mn_0.1O_2.     

Deacetylated Cellulose Acetate/Polyurethane Composite Nanofiber Membranes with Highly Efficient Oil/Water Separation and Excellent Mechanical Properties

Nowadays, oil pollution has become more serious, which causes great threats both to the ecological environment and human life. In this study, a novel type of multifunctional deacetylated cellulose acetate/polyurethane (d-M_CA:M_TPU) composite nanofiber membranes for oil/water separation are successfully fabricated by electrospinning, which show super-amphiphilicity in air, super-hydrophilicity in oil, and oleophobicity in water. All the d-M_CA:M_TPU composite nanofiber membranes with different mass ratios can be used as water-removing, oil-removing, and emulsion separation substance only by gravity driving force. The highest separation flux for water and oil reaches up to 37 000 and 74 000 L m⁻² h⁻¹, respectively, and all the separation efficiencies are more than 99%. They have outstanding comprehensive mechanics performance, which can be controlled by simply adjusting the mass ratios. They show excellent antifouling and self-cleaning ability, endowing powerful cyclic stability and reusability. Those results show that d-M_CA:M_TPU composite nanofiber membranes have great application prospects in oil/water separation.     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.