Study of hexane adsorption in nanoporous MCM-41 silica

We study here the adsorption of hexane on nanoporous MCM-41 silica at 303,313, and 323 K, for various pore diameters between 2.40 and 4.24 nm. Adsorption equilibria, measured thermogravimetrically, show that all the isotherms, that are somewhat akin to those of type V, exhibit remarkably sharp capillary adsorption phase transition steps and are reversible. The position of the phase transition step gradually shifts from low to high relative pressure with an increase in the temperature as well as the pore sizes. The isosteric heats of adsorption derived from the equilibrium information using the Clapeyron equation reveal a gradual decrease with increasing adsorbed amount because of the surface heterogeneity but approach a constant value near the phase transition. A decrease in the pore size results in an increase in the isosteric heat of adsorption because of the increased dispersion forces. A simple strategy, based on the Broekhoff and De Boer adsorption theory, successfully interprets the hexane adsorption isotherms for the different pore size MCM-41 samples. The parameters of an empirical expression, used to represent the potential of interaction between the adsorbate and adsorbent, are obtained by fitting the monolayer region prior to capillary condensation and the experimental phase transition simultaneously, for some pore sizes. Subsequently, the parameters are used to predict the adsorption isotherm on other pore size samples, which showed good agreement with experimental data.     

应用反向传播神经网络预测化合物脑血分配系数

选用27种三维结构性质描述符对脑血分配系数预测建立神经网络模型.网络模型选用典型的适合函数逼近的两层结构神经网络对脑血分配系数(lgBB,BB为脑血浓度比)进行预测,计算中采用的模型具有一个双曲正切型激活函数的隐含层和一个线性激活函数的输出层.计算表明,使用小心选择的反向传播神经网络模型对化合物脑血分配系数具有较好的预测能力.     

The relation between the number of leaves of a tree and its diameter

Czechoslovak Mathematical Journal - Let L(n, d) denote the minimum possible number of leaves in a tree of order n and diameter d. Lesniak (1975) gave the lower bound B(n,d) = ⌈2(n −...     

Limit cycle analysis of a class of strongly nonlinear oscillation equations

The limit cycle of a class of strongly nonlinear oscillation equations of the form % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXafv3ySLgzGmvETj2BSbqefm0B1jxALjhiov2D% aebbfv3ySLgzGueE0jxyaibaiGc9yrFr0xXdbba91rFfpec8Eeeu0x% Xdbba9frFj0-OqFfea0dXdd9vqaq-JfrVkFHe9pgea0dXdar-Jb9hs% 0dXdbPYxe9vr0-vr0-vqpWqaaeaabiGaciaacaqabeaadaqaaqGaaO% qaaiqadwhagaWaaiabgUcaRmXvP5wqonvsaeHbbjxAHXgiofMCY92D% aGqbciab-DgaNjab-HcaOiaadwhacqWFPaqkcqWF9aqpcqaH1oqzca% WGMbGaaiikaiaadwhacaGGSaGabmyDayaacaGaaiykaaaa!50B8!\[\ddot u + g(u) = \varepsilon f(u,\dot u)\] is investigated by means of a modified version of the KBM method, where is a positive small parameter. The advantage of our method is its straightforwardness and effectiveness, which is suitable for the above equation, where g(u) need not be restricted to an odd function of u, provided that the reduced equation, corresponding to =0, has a periodic solution. A specific example is presented to demonstrate the validity and accuracy of our 09 method by comparing our results with numerical ones, which are in good agreement with each other even for relatively large .