Strain facilitated small gas molecules sensing properties on Au doped SnSe2 monolayer

By the first-principles calculations, the sensitivity of CO, H₂O and NO adsorption on Au doped SnSe₂ monolayer surface is investigated. The results show that CO and H₂O molecules are physically adsorbed on Au doped SnSe₂ monolayer and act as donors to transfer 0.012 e and 0.044 e to the substrate, respectively. However, the NO molecule is chemically adsorbed on substrate and acts as an acceptor to obtain 0.116 e from the substrate. In addition, our results also show that the biaxial strain can effectively improve the adsorption energy and charge transfer of gas molecules adsorbed on the substrate surface. Also, the recovery time of desorbed gas molecules on the substrate surface is calculated, and the results indicate that the Au doped SnSe₂ is a perfect sensing material for detection and recovery of CO and NO under ?8% strain.     

Thermal expansion of CaAl4O7-based refractory compositions containing MgO and CaO additions

Various compositions of recently developed CaAl₄O₇-based ceramics are mentioned with special reference to those called “nonexpansive refractories” (=NER). The observed effect of deep depression of their thermal expansion is mainly ascribed to the creation of a specific microstructure resulting from high temperature reactions of CaAl₄O₇ with MgO or CaO additives yielding a CaAl₂O₄-based liquid. Some details characterizing the phase composition of the reaction zone are given. The effect of the calculated approximate content of CaAl₂O₄ in the specimens is interpreted graphically. Basing on the results of changes in the CaAl₄O₇ single crystal dimensions presented in comparison with some other expansion data, the presumable nature of the specific behavior of NER bodies on heating up to 500 °C is discussed. The NER products fired at 1620 °C are characterized by high strength and low open porosity.     

A Network Security Risk Assessment Method Based on a B_NAG Model

Computer networks face a variety of cyberattacks. Most network attacks are contagious and destructive, and these types of attacks can be harmful to society and computer network security. Security evaluation is an effective method to solve network security problems. For accurate assessment of the vulnerabilities of computer networks, this paper proposes a network security risk assessment method based on a Bayesian network attack graph (B_NAG) model. First, a new resource attack graph (RAG) and the algorithm E-Loop, which is applied to eliminate loops in the B_NAG, are proposed. Second, to distinguish the confusing relationships between nodes of the attack graph in the conversion process, a related algorithm is proposed to generate the B_NAG model. Finally, to analyze the reachability of paths in B_NAG, the measuring indexs such as node attack complexity and node state transition are defined, and an iterative algorithm for obtaining the probability of reaching the target node is presented. On this basis, the posterior probability of related nodes can be calculated. A simulation environment is set up to evaluate the effectiveness of the B_NAG model. The experimental results indicate that the B_NAG model is realistic and effective in evaluating vulnerabilities of computer networks and can accurately highlight the degree of vulnerability in a chaotic relationship.     

Augmented Lyapunov functional approach for stability of neutral systems with mixed delays

This paper is concerned with the neutral‐delay‐dependent and discrete‐delay‐dependent stability for uncertain neutral systems with mixed delays and norm‐bounded uncertainties. Through constructing a new augmented Lyapunov‐Krasovskii functional and proving its positive definiteness, introducing some slack matrices and using integral inequality, the improved delay‐dependent stability criteria are derived in terms of linear matrix inequalities. Numerical examples are given to illustrate the significant improvement on the conservatism of the delay bound over some existing results. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

RBF neural networks-based robust adaptive tracking control for switched uncertain nonlinear systems

In this paper, a robust adaptive H∞ control scheme is presented for a class of switched uncertain nonlinear systems. Radical basis function neural networks (RBF NNs) are employed to approximate unknown nonlinear functions and uncertain terms. A robust H∞ controller is designed to enhance robustness due to the existence of the compound disturbance which consists of approximation errors of the neural networks and external disturbance. Adaptive neural updated laws and switching signals are deducted from multiple Lyapunov function approach. It is proved that with the proposed control scheme, the resulting closed-loop switched system is robustly stable and uniformly ultimately bounded (UUB) such that good capabilities of tracking performance is attained and H∞ tracking error performance index is achieved. A practical example shows the effectiveness of the proposed control scheme.     

Improved stability conditions for systems with interval time-varying delay

The paper is concerned with the stability of linear systems with interval time-varying delay. Through constructing a new augmented Lyapunov-Krasovskii functional (LKF) which contains some quadruple-integral terms and estimating the time derivative of the LKF less conservatively, new stability criteria are derived without introducing any free matrices. Moreover, by proving the positive definiteness of the LKF with some integral inequalities, the constraints on some functional parameters are relaxed and the conservatism of the obtained results are further reduced. Numerical examples are also given to demonstrate the effectiveness and reduced conservatism of the obtained results.     

A dual-stimuli-responsive intelligent layered lanthanide hydroxide for application in information security and latent fingerprint identification

With the rapid changes in the field of information, the research and development of optical storage materials with high security and large storage capacity are particularly important in the development of contemporary society. However, conventional memory materials with static fluorescent outputs have the disadvantages of easy simulation and forgery, which limits their practical application in the protection of confidential information. In this research, a dual-stimuli-responsive intelligent fluorescent material based on Tb³⁺ and Eu³⁺ ions doped layered lanthanide hydroxide (LYH:Eu_xTb_1–xDPA) was fabricated, which can realize reversible multi-color luminescence conversion (from green to red) by varying the pH and temperature. Combined with the Morse code and security pattern, the multiple encryption and decryption of confidential information and anti-counterfeiting can also be realized. Therefore, the obtained intelligent fluorescent material has a great application prospect for information security. In addition, due to the excellent color tunability, the material can provide the possibility to obtain potential fingerprints with high contrast and no background interference on different color substrates. The unique dual-stimuli-responsive behavior of this material provides more ingenious design inspiration for the design of multi-color intelligent fluorescent devices.     

锌-锰合金镀层磷化工艺研究

为进一步提高Zn-M n合金镀层的抗蚀性,采用锌锰系磷化处理Zn-M n合金镀层,研究表明在相同镀层厚度下,Zn-M n合金镀层抗蚀能力是镀锌层的5倍,经磷化后的Zn-M n合金镀层的抗蚀能力是镀锌层的7~8倍。实验结果表明,Zn-M n合金镀层经锌锰系磷化后抗蚀性明显提高。