Unique role of non-mercapto groups in thiol-pinning-mediated Ag growth on Au nanoparticles

Owing to the strong affinity of thiols to Au and Ag, they are often employed to modify the surfaces of nanoparticles (NPs). Recently, these strong ligand-interface interactions have been employed to control NP growth, and this technique has emerged as a unique modulation strategy for creating unconventional plasmonic hybrid nanostructures. In these systems, the roles of the non-mercapto components of the thiol molecules and their structures are still unknown. Therefore, we herein present our investigation into this phenomenon. Primary amino (–NH₂) groups in thiols are found to play a key role in regulating growth kinetics, i.e., in accelerating Ag deposition on Au NPs. The–NH₂ groups are thought to bring Ag ions to the particle surface by coordinating to them, and thereby assist their reduction. The effect of molecular structure is non-trivial and thus provides the possibility of selective thiol detection. Based on the dependence of kinetic modulation on the non-mercapto components and molecular structures of molecules, we demonstrate the highly sensitive and specific detection of cysteine (limit of detection: 6 nM) in a mixture of 19 natural amino acids based on Ag growth on Au nanospheres. In addition, based on this modulation effect, we reveal the entrapping of chiral thiols within the growth layer through their plasmonic circular dichroism (PCD) responses. We believe that thiol-based growth regulation has great potential for creating plasmonic nanostructures with novel functionalities.

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Synthesis of ultrathin semicircle-shaped copper nanowires in ethanol solution for low haze flexible transparent conductors

Nano Research - Copper nanowires (CuNWs) are becoming an indispensable item for next-generation transparent optical devices due to their excellent conductivity and transparency. In this work,...     

Reliability analysis on systems with self-healing and self-repairing under different environments and shock models

Inspired by the process of self-healing of biological damage, high technology materials with self-healing and self-repairing mechanisms have been developed for high reliability and long lifetime. Therefore, the reliability modeling on intelligent systems with healing performance has become a research hotspot. Based on the diversity of healing mechanisms, this paper proposes a two-phase reliability model method on self-healing and self-repairing systems. Impacts of environments, shock loads, self-healing, and self-repairing mechanisms are taken into account in this novel model. Besides, system lifetime and some reliability indexes under two shock models are derived, respectively. Moreover, Monte Carlo simulations are conducted to verify the accuracy of reliability under two models. Finally, an engineering case of metallized film capacitor is provided to illustrate the effectiveness and applicability of the proposed models by comparing numerical results and simulation results.     

二溴对甲基偶氮甲磺光度法测定钢中微量锶

研究了二溴对甲基偶氮甲磺与锶生成2:1兰色络合物进行钢中微量锶的测定.该法λ_(max)=638nm,摩尔吸光系数E_(638)=5.01×10~4,锶量在0.02～0.34μg/L范围内服从比尔定律.方法已用于钢中微量锶的测定,结果满意.     

A nonlinear geometric approach to power system excitation control and stabilization

In this paper, a unified approach to the design of a nonlinear excitation controller/power system stabilizer for a synchronous generator/infinite bus power system is presented. The approach is based on a form of state feedback linearization, known as input–output feedback linearization, which provides an exact semi-global state transformation that is valid for a large class of operating points of the power system. With this transformation, the terminal voltage becomes a linear function of the control input. The excitation controller/power system stabilizer is then synthesized by using linear controller design techniques. The controller is proven to provide small signal stability and to provide local asymptotic tracking of admissible constant reference signals for a large class of operating points. A procedure is given to tune the controller gains to provide significant damping of the power angle oscillations.     

"震网"引发网络安全新思考

本文概述了近期发生的"震网"事件.同时分析了"震网"的特点和行为特征.并根据我国的具体情况给出了安全警示和安全防范建议.     

Stability analysis for multi-agent systems using the incidence matrix: Quantized communication and formation control

The spectral properties of the incidence matrix of the communication graph are exploited to provide solutions to two multi-agent control problems. In particular, we consider the problem of state agreement with quantized communication and the problem of distance-based formation control. In both cases, stabilizing control laws are provided when the communication graph is a tree. It is shown how the relation between tree graphs and the null space of the corresponding incidence matrix encode fundamental properties for these two multi-agent control problems.     

Multi-level hierarchical interface-based supervisory control

Hierarchical Interface-Based Supervisory Control employs interfaces that allow properties of a monolithic system to be verified through local analysis. By avoiding the need to verify properties globally, significant computational savings can be achieved. In this paper we provide local requirements for a multi-level architecture employing command-pair type interfaces. This multi-level architecture allows for a greater reduction in complexity and improved reconfigurability over the two-level case that has been previously studied since it allows the global system to be partitioned into smaller modules. This paper also provides results for synthesizing supervisors in the multi-level architecture that are locally maximally permissive with respect to a given specification and set of interfaces.     

A level set method based on the Bayesian risk for medical image segmentation

This paper proposes an alternative criterion derived from the Bayesian risk classification error for image segmentation. The proposed model introduces a region-based force determined through the difference of the posterior image densities for the different classes, a term based on the prior probability derived from Kullback-Leibler information number, and a regularity term adopted to avoid the generation of excessively irregular and small segmented regions. Compared with other level set methods, the proposed approach relies on the optimum decision of pixel classification and the estimates of prior probabilities; thus the approach has more reliability in theory and practice. Experiments show that the proposed approach is able to extract the complicated shapes of targets and robust for various types of medical images. Moreover, the algorithm can be easily extendable for multiphase segmentation.     

An improved method for voice pathology detection by means of a HMM-based feature space transformation

This paper presents new a feature transformation technique applied to improve the screening accuracy for the automatic detection of pathological voices. The statistical transformation is based on Hidden Markov Models, obtaining a transformation and classification stage simultaneously and adjusting the parameters of the model with a criterion that minimizes the classification error. The original feature vectors are built up using classic short-term noise parameters and mel-frequency cepstral coefficients. With respect to conventional approaches found in the literature of automatic detection of pathological voices, the proposed feature space transformation technique demonstrates a significant improvement of the performance with no addition of new features to the original input space. In view of the results, it is expected that this technique could provide good results in other areas such as speaker verification and/or identification.