聚氨酯／聚甲基丙烯酸甲酯互穿聚合物网络的研究

本文对(蓖麻油-聚乙二醇)聚氨酯/聚甲基丙烯酸甲酯(PU/PMMA)互穿聚合物网络(IPN)体系进行了研究.实验结果表明:IPN的力学性能受网络化学构型控制.在PU/PMMA为25/75时,应力-应变曲线出现屈服点,产生类似皮革行为,并在此点抗张强度最高,表现明显的协同效应.动态力学性能及电镜均证明该体系相分离十分严重,通过加入扩链剂及网间交联剂能显著改善两组分相容性,其中网间交联剂效果最好。     

Event-triggered sliding mode control for switched genetic regulatory networks with persistent dwell time

This paper focus on the event-triggered sliding mode controller design for discrete-time switched genetic regulatory networks (GRNs) with persistent dwell time (PDT) switching. Firstly, the observation error dynamics of switched GRNs with PDT is constructed in the light of event-triggered sliding mode control (SMC) scheme. Next, sufficient conditions are derived to ensure the exponential stability of the augmented plant. Moreover, an event-triggered SMC law is synthesized to impel the system trajectories onto the sliding surface in a finite time. Finally, a verification example is provided to illustrate the effectiveness and potential of the proposed method.     

Retrieval and chaos in extremely dilutedQ-Ising neural networks

Using a probabilistic approach, the deterministic and the stochastic parallel dynamics of aQ-Ising neural network are studied at finiteQ and in the limitQ. Exact evolution equations are presented for the first time-step. These formulas constitute recursion relations for the parallel dynamics of the extremely diluted asymmetric versions of these networks. An explicit analysis of the retrieval properties is carried out in terms of the gain parameter, the loading capacity, and the temperature. The results for theQ network are compared with those for theQ=3 andQ=4 models. Possible chaotic microscopic behavior is studied using the time evolution of the distance between two network configurations. For arbitrary finiteQ the retrieval regime is always chaotic. In the limitQ the network exhibits a dynamical transition toward chaos.     

The least element property of center location on tree networks with applications to distance and precedence constrained problems

In the classicalp-center location model on a network there is a set of customers, and the primary objective is to selectp service centers that will minimize the maximum distance of a customer to a closest center. Suppose that thep centers receive their supplies from an existing central depot on the network, e.g. a warehouse. Thus, a secondary objective is to locate the centers that optimize the primary objective as close as possible to the central depot. We consider tree networks and twop-center models. We show that the set of optimal solutions to the primary objective has a semilattice structure with respect to some natural ordering. Using this property we prove that there is ap-center solution to the primary objective that simultaneously minimizes every secondary objective function which is monotone nondecreasing in the distances of thep centers from the existing central depot.Restricting the location models to a rooted path network (real line) we prove that the above results hold for the respective classicalp-median problems as well.     

Rigorous results on the thermodynamics of the dilute Hopfield model

We study the Hopfield model of an autoassociative memory on a random graph onN vertices where the probability of two vertices being joined by a link isp(N). Assuming thatp(N) goes to zero more slowly thanO(1/N), we prove the following results: (1) If the number of stored patternsm(N) is small enough such thatm(N)/Np(N) 0, asN, then the free energy of this model converges, upon proper rescaling, to that of the standard Curie-Weiss model, for almost all choices of the random graph and the random patterns. (2) If in additionm(N) < ln N/ln 2, we prove that there exists, forT< 1, a Gibbs measure associated to each original pattern, whereas for higher temperatures the Gibbs measure is unique. The basic technical result in the proofs is a uniform bound on the difference between the Hamiltonian on a random graph and its mean value.     

Crosslinking of vinyl‐terminated biphenyl and naphthalene side‐chain liquid‐crystalline poly(epichlorohydrin) derivatives

We performed the crosslinking of vinyl‐terminated biphenyl and naphthalene side‐chain liquid‐crystalline polyethers using peroxide‐type initiators with and without the addition of tertiary amine promoters. The crosslinking temperatures were chosen in the range of mesophase stability to allow the mesophase order to be frozen. The biphenyl derivatives, with a high isotropization temperature, were crosslinked to a large extent. This led to anisotropic thermosets. To crosslink naphthalene derivatives, amine promoters were needed, but degrees of crosslinking were lower, and anisotropic elastomers were obtained. Crosslinking processes were studied by differential scanning calorimetry, polarized optical microscopy, and Fourier transform infrared spectroscopy. The nature of the frozen mesophase was confirmed by X‐ray diffraction studies on mechanically oriented samples. © 2002 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 40: 2237–2244, 2002     

Miscible blends through hydrogen bonding: effects on polymer properties

Miscible blends through hydrogen bonding have been intensively studied. The effects of a variety of miscible hydrogen bonded polymer blends on properties such as thermal and thermal oxidative stability, moisture sensitivity, modulus and glass transition temperature are discussed. In addition, the preparation of semi-interpenetrating polymer networks (IPNs) and studies of the effect of crosslinking on the miscibility in hydrogen bonded polymer blends are reviewed.     

Prediction of Complexation Properties of Crown Ethers Using Computational Neural Networks

A computational neural network method was used for the prediction of stability constants of simple crown ether complexes. The essence of the method lies in the ability of a computer neural network to recognize the structure-property relationships in these host-guest systems. Testing of the computational method has demonstrated that stability constants of alkali metal cation (Na+, K+, Cs+)-crown ether complexes in methanol at 25 °C can be predicted with an average error of ±0.3 log K units based on the chemical structure of the crown ethers alone. The computer model was then used for the preliminary analysis of trends in the stabilities of the above complexes.     

基于支持向量机的羰基化合物红外光谱研究

设计了一个4层分等级分类系统，通过支持向量机技术对羰基化合物的红外光谱成功地进行了信息分类和提取，并与人工神经网络进行比较，结果表明：支持向量机对羰基类化合物红外光谱分类效果优于人工神经网络；另外详细探讨了表征酰胺类化合物的特征光谱峰片段对识圳伯仲叔酰胺的影响，证明了酰胺的N-H伸缩振动峰对识别伯仲叔酰胺贡献最大，为构建红外光谱智能解析系统提供了定量依据。