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In our previous work (Wang et al., 1997), the simplified hole theory equation of state was successfully used for the estimation of the pressure−volume−temperature relationship and vapor−liquid equi...

We study the possibility of the recognition of surface heterogeneities with surfactant adsorption by performing Monte Carlo simulations. It is found that when each patch size of a heterogeneous surface is capable of being commensurate with the size of aggregates adsorbed on the constituent homogeneous surfaces, the adsorption isotherm of the system will display both adsorption characteristics for each homogeneous surface. Otherwise, one or more adsorption characteristics will be spoiled or destroyed. Therefore, the adsorption isotherm of surfactants on a heterogeneous surface provides a signal of recognition.

The group contribution (GC) approach was incorporated into the simplified hole theory equation of state (SHT EOS) for polymers, solvents, and polymer–solvent solutions, proposed by the authors previously. The group parameters for polymers and solvents were obtained for the description of the PVT relationship for 59 polymers and 59 solvents with remarkably better prediction accuracy, compared with the GC-Flory and GCLF EOSs. Furthermore, a binary group interaction parameter matrix containing 110 parameters were recommended for the prediction of weight fraction activity coefficients (WFACs) for polymer–solvent solutions. The prediction results for 96 data sets indicate that the GCSHT EOS is superior to the GCLF EOS with the grand average 6.7% against 14.5% for the latter.

A method for deriving the Stockmayer potential parameters for polar fluids from phase-coexistence data has been developed. The parameters for a polar fluid can be determined by correlations in terms of the critical temperature, the saturated liquid density and the saturated vapor pressure at a specific reduced temperature, T r = 0.75. With the potential parameters, Gibbs Ensemble Monte Carlo (GEMC) simulations for hydrochlorofluorocarbons (HCFCs)/hydrofluorocarbons (HFCs) were carried out at different temperature. Simulated molar volumes of both the vapor and liquid phases, saturated vapor pressures, and enthalpy of vaporization are all in good agreement with the experimental data, which indicates that the so-called effective Stockmayer potential with the parameters proposed in this work is capable of predicting accurately the vapor-liquid equilibria for the environment-related HCFC HFC substances.

In the simplified hole theory equation of state proposed by our group (Zhong, C.; Wang, W.; Lu, H. Fluid Phase Equilib. 1993, 86, 137), the occupied site fraction for the Simha−Somcynsky equation of state (Simha, R.; Somcynsky, T. Macromolecules 1969, 2, 342) was derived as a simple exponential function of temperature alone, in terms of the theory for an imperfect crystal with thermal defects. In this work, the simplified hole theory equation of state has been applied to an accurate description of the pressure−volume−temperature relationship for 67 liquid polymers and 61 solvents and compared with four commonly used equations of state. An approximate expression for the activity coefficient of a solvent in polymer−solvent solutions has been derived, which enables one to calculate the activity coefficient for the solvent analytically. The grand absolute average deviation between the calculated and experimental solvent activity coefficients for 95 data sets is 2.4%, which indicates that this equation of stat...

Using Gibbs ensemble Monte Carlo simulations, we investigated the vapour - liquid equilibria of a number of binary mixtures, some containing Lennard-Jones (LJ) and Stockmayer (SM) components, and others containing two SM components with different reduced dipole moments. Our results show that the phase coexistence properties of the mixtures are sensitive to the difference between the reduced dipole moments of the two components: an increase in this difference causes the phase envelope to widen for both the LJ - SM and SM - SM mixtures. Comparison of our results to vapour - liquid equilibria data simulated using an angle-averaged approximation of the long-range dipolar interaction, the Keesom potential, suggests that the Keesom potential is not suitable to approximate the dipolar interactions for mixtures when the dipolar interaction is dominant.

A quasi-two-dimensional (2D) Stockmayer model is developed in which the center of mass of the molecule is confined on a plane while the dipole of the molecule can rotate freely in three dimensional space. This model entails essential characteristics of systems such as dipolar molecules physisorbed on a solid surface, or a Langmuir monolayer consisting of short-chain molecules with a dipolar tail. The Gibbs ensemble Monte Carlo technique is employed to determine the vapor–liquid equilibria of the model fluids. An Ewald sum for this quasi-2D model is formulated to account for the long-range dipolar interactions. Three systems with different reduced dipole moments were studied. The critical point of each system is determined by fitting the vapor–liquid coexistence data to a 2D scaling law and the rectilinear law. We find that in general the critical temperature of the system is reduced due to the confinement and is sensitive to the strength of the dipole moment, whereas the critical density is not. The effec...

We investigated the dependence of the solute residual chemical potential on soluteto-solvent molecule size ratio in infinitely dilute Lennard-Jones fluids. A minimum on the μA r∞/eBB ∼ (σAB/σBB)3 curve has been found at high solvent densities ρσBB 3 = 0•75 and 0•8 (σ and e are the Lennard-Jones size and energy parameters, respectively, μA r∞ is the solute residual chemical potential in an infinitely dilute solution, A and B denote solute and solvent, respectively, and ρ is the solvent molecule density). Such a minimum commonly has been observed in supercritical fluids, but obtaining one from computer simulation of subcritical fluids is challenging since a very high solvent density or a large solute size is needed. This study seems to provide the first simulation evidence of such a minimum at a subcritical temperature. The position of this minimum is very sensitive to solvent density as well as temperature. An umbrella sampling Monte Carlo method was adopted to compute the solute residual chemical potentia...

A deposition reaction mechanism for Si 1−x Ge x epitaxial growth from silane/gemane mixtures is proposed. The resulting growth rate expression, the parameters of which are determined with a least square method, is consistent with available data and it predicts all three distinctive trends observed: decreasing growth rates with increasing germanium content at high temperatures, increasing growth rates with increasing germanium content at low temperatures, and a maximum of the growth rate with increasing germanium content at intermediate temperature ranges. A two-dimensional model of a low-pressure chemical vapor deposition (LPCVD) reactor is developed so that relationships between epitaxial thin film properties and processing environments can be obtained. The model includes three regions, the entry length region, the annular region, and the inter-wafer one. Experimental data of epitaxial silicon thin films from dichlorosilane obtained in the Purdue LPCVD reactor are seen to be in satisfactory agreement with our theoretical predictions. Simulation results of the Si 1−x Ge x growth in the Purdue reactor result in deposition rates on the order of about 0.01–0.1 μm/min at the conditions investigated.

The open-cell model equation of state (OCM EOS) proposed in the preceding paper by the authors has been extended to polymer-solvent and polymer blend systems, covering a variety properties, including P-V-T relations, the excess volume and enthalpy, the activity of solvents, and phase diagrams. Compared with the well-recognized Simha and Somcynsky EOS, the OCM EOS presents a better description of P-V-T relations and phase diagrams. Besides, through a set of proper binary interaction parameters, good correlation of the excess properties can be achieved. In conclusion, as an improvement over the existing hole theory EOSs, the OCM EOS is capable of describing liquid mixture properties with satisfactory accuracy.

A compact generator producing 2.2-ns 1.5 GW high-voltage pulses was developed. The generator employed a 27.6 Ω, 0.9 ns pulse-forming-line (PFL), which was charged by an iron core transformer with a turn ratio of 2:33.5 and a coefficient of 0.94. A 1.2 μF, 20 kV capacitor and a hydrogen thyratron were used in the primary circuit. When the thyratron closed at 14.5 kV, 3.4% of the energy stored in the capacitor was delivered to the PFL in 850 ns, producing a peak voltage of up to ∼500 kV. In addition, the principle of triple resonance transformation was employed by adding a 50 pF tuning capacitor and a 1.15 mH inductor between the transformer and the PFL, which led to a significant reduction of the duration and peak value of the transformer voltage without reducing that in the PFL. Meanwhile, an adjustable self-break oil switch was applied. By using transmission lines with impedance overmatched to that of the PFL, the generator delivered a 512 kV pulse across an electron beam diode, generating radiation with a dose of 20 mR/pulse at 20 cm ahead of the diode. The generator provides an excellent ultra-short radiation pulse source for the studies on radiation physics.

The composition-dependent equilibrium structure and thermal stability of Pd-Pt clusters with the size of 55 atoms, and CO, O, OH, and O(2) adsorption on these clusters have been studied using molecular simulation based on the Gupta empirical potential and density functional theory (DFT) calculations. It is found that Pd(43)Pt(12) with a three-shell onionlike structure (TS-cluster) exhibits the highest relative stability in both DFT and Gupta levels and also the highest melting point at the Gupta level among these Pd-Pt clusters. In addition, the Pd(43)Pt(12) TS-cluster possesses the weakest CO, O, OH, and O(2) adsorption strength, compared to the Pt(55), Pd(55), and Pd(13)Pt(42) clusters, indicating good catalytic activities toward the oxygen reduction reaction (ORR) among these Pd-Pt clusters considered. We expect that this kind of DFT-guided strategy by controlling the composition could provide a simple way for possibly searching new electrocatalysts.

The simplified hole theory equation of state has been extended to polymer-solvent and polymer-polymer systems for the calculation of the P-V-T relations for five binary systems with good accuracy. Moreover, to test the equations proposed, the spinodal curves for two polymer-solvent systems have been estimated. Comparisons have been made between the calculated results of this work and the estimations from the well-recognized Simha and Somcynsky equation of state, which shows that the equations proposed are of the same quality as the latter, but much simpler in computation.

An open-cell model equation of state has been proposed, which relaxes the restrictions of the cell theory and allows more flexibilities in describing the structure of liquids. To test its capability, this equation has been applied to a variety of liquids, including 17 heavy molecular weight hydrocarbons, 10 organic solvents, and 15 polymers, in particular. The calculated density grand average AADp for the equation proposed here are 0.062, 0.057, and 0.054 per cent against the results for the equation of state by Simha and Somcynsky, 0.081, 0.093, and 0.072 percent for the above three groups of liquids, respectively

The ultrafine amorphous Fe 56 Zr 5 B 39 and Fe 68 B 32 powders prepared by borohydride reduction were investigated using the Mossbauer spectroscopy for a comparative study. The hyperfine field distribution P ( H ) of the Fe 56 Zr 5 B 39 powder shows a double-maxima function of H with a high-field component at 210 kOe and a low-field component at 48 kOe. The EXAFS investigation on the Fe 56 Zr 5 B 39 powders revealed the short-range order structure in the powders, which coincides with the behavior of P ( H ).

The Gibbs-ensemble Monte Carlo simulation method was applied to calculate the enthalpies of the argon (1) + methane (2) system at 150.72 and 164.0 K. The Lennard-Jones (LJ) potential function was adopted to describe the intermolecular interactions. Three hundred spherical, isotropic particles were used in all simulation runs. A new particle transfer method is proposed that has been found to be more efficient than the random insertion method. A satisfactory agreement was obtained between our simulation results and the predictions by the Soave and Peng-Robinson equations of state (EOSs).

Zhong, C., Wang, W. and Lu, H., 1993. Simplified hole theory equation of state for polymer liquids. Fluid Phase Equilibria, 86: 137-146 A simple exponential relation between the occupied-site fraction in the lattice and the reduced temperature is proposed, based on the statistical theory for the thermal defects of an imperfect crystal. Following the approach of Simha and Somcynsky (1969), [Simha, R. and Somcynsky, T., 1969. On the statistical thermodynamics of spherical and chain molecule fluids. Macromolecules, 2: 342-351], a simplified hole theory equation of state (EOS) for polymer liquids has been derived. For 11 polymer liquids, the calculated P-V-T results show that the equation proposed is of the same quality as the Simha-Somcynsky equation of state. Moreover, with much less computing effort, this equation can be easily extended to polymer solutions.

In this communication two conventional excess Gibbs energy models, the Wang—Chao and NRTL equations, are used to represent the classical properties. Three models are introduced for the transformation of coordinates. After the transformation, results for five ternary partially miscible systems show good improvement over those for the original models, covering the regions near to and remote from the plait points. From the one parameter damping function model proposed here, the results are satisfactory with much less computing effort.

Reservoir inflow forecasting plays an essential role in reservoir management to ensure efficient water supply and more high accuracy inflow forecasting can lead to more effective use of water resources. In this study, support vector machine (SVM) with particle swarm optimization (PSO) for reservoir annual inflow forecasting is presented, among which PSO is used to find out the best parameter value of SVM model. According to study data, the optimum SVM model is obtained and its performance is compared with Artificial Neural Networks (ANNs). It can be concluded that the performance of SVM model outperforms those of ANN, for the data set available, which indicates that the SVM model has better forecasting performance.

Optimal reservoir operation of systems is important for effective and efficient management of available water resources for maximum system benefit. Although some optimization techniques have been applied to obtain optimal reservoir scheduling rule, an efficient method in optimal operation of reservoir systems still remain to be required owing to complexity of reservoir system. In this paper, Particle swarm optimization (PSO) with Adaptive random inertia weight (ARIW) is presented for optimizing reservoir operation, which can adjust the probability distribution of random inertia. A case study with actual data from previous literature, the results shows an excellent performance in terms of its optimization results and it has potential in application to complex river systems.

In this work, we studied the flow boundary conditions for the interface between two immiscible liquids under the condition of low shear rates in the presence or absence of surfactants. Our simulation results indicate that the boundary conditions are substantially changed by the presence of surfactants. Similar to the liquid-solid boundary, several boundary conditions at immiscible liquid-liquid interfaces, including slip, no-slip, and locking boundary conditions, are observed depending on the interfacial surfactant concentration. The slip boundary condition is achieved only at zero or lower surfactant concentration. The locking boundary condition is observed when the surfactant concentration is large enough to form a fully developed monolayer whereas the no-slip condition occurs for systems with intermediate values of surfactant concentration. The slip, no-slip, and locking boundary conditions yield the positive, zero, and negative slip lengths, respectively. We also investigated the dependence of boundary slip on shear rate at different interfacial surfactant concentrations. Compared to the systems without surfactants, the increase in slip with shear rate slows down because of the presence of surfactants, and consequently, the linear dependence of slip length changes to a nonlinear dependence. Simulation results also indicate that the shear rate also affects the surfactant distribution. In particular, when the surfactant concentration is high enough to form a fully developed monolayer, the higher shear rate would make the monolayer rupture.

Using first-principles calculations, we have systematically studied the quantum size effects of ultrathin Pb(111) films on the adsorption energies and diffusion energy barriers of oxygen atoms. For the on-surface adsorption of oxygen atoms at different coverages, all the adsorption energies are found to show bilayer oscillation behaviors. It is also found that the work function of Pb(111) films still keeps the bilayer-oscillation behavior after the adsorption of oxygen atoms, with the values being enlarged by 2.10 to 2.62 eV. For the diffusion and penetration of the adsorbed oxygen atoms, it is found that the most energetically favored paths are the same on different Pb(111) films. And because of the modulation of quantum size effects, the corresponding energy barriers are all oscillating with a bilayer period on different Pb(111) films. Our studies indicate that the quantum size effect in ultrathin metal films can modulate a lot of processes during surface oxidation.

The accurate parameter estimation for Muskingum model is to be useful to give the flood forecasting for flood control in water resources planning and management. Although some methods have been used to estimate the parameters for Muskingum model, an efficient method for parameter estimation in the calibration process is still lacking. In order to reduce the computational amount and improve the computational precision for parameter estimation, a modified particle swarm algorithm (MPSO) is presented for parameter optimization of Muskingum model. The technique found the best parameter values compared to previous results in terms of the sum of least residual absolute value. Empirical results that involve historical data from existed paper reveal the proposed MPSO outperforms other approaches in the literature.

Polymer nanocomposites (PNCs) often exhibit excellent mechanical, thermal, electrical and optical properties, because they combine the performances of both polymers and inorganic or organic nanoparticles. Recently, computer modeling and simulation are playing an important role in exploring the reinforcement mechanism of the PNCs and even the design of functional PNCs. This report provides an overview of the progress made in past decades in the investigation of the static, rheological and mechanical properties of polymer nanocomposites studied by computer modeling and simulation. Emphases are placed on exploring the mechanisms at the molecular level for the dispersion of nanoparticles in nanocomposites, the effects of nanoparticles on chain conformation and glass transition temperature (T(g)), as well as viscoelastic and mechanical properties. Finally, some future challenges and opportunities in computer modeling and simulation of PNCs are addressed.

By using the first-principles DFT calculations, we design a novel hydrogen storage material, Li(12)Si(60)H(60) composite, and validate its geometric stability. It is found that the adsorbed Li atoms do not cluster on the Si(60)H(60) fullerene unlike other metals such as Ti, owing to the relatively low Li-Li binding energy and the inhibition of Si-H bonds. Our results show that the Li-doping enhances the hydrogen adsorption ability of Si(60)H(60) significantly, owing to the charge transfer from the doped Li atoms to the host material and the polarization of the adsorbed H(2) molecules. By combining the first-principles calculation and grand canonical Monte Carlo simulation, we further investigate the hydrogen storage capacity of the simulation-synthesized exohedral Li(12)Si(60)H(60) composite at T = 77 K. As the vdW gap (i.e., the separation between the surfaces of two Li(12)Si(60)H(60) fullerenes) is equal to 8.2 A, the total hydrogen uptake of the square-arranged Li(12)Si(60)H(60) array reaches 12.83 wt % at p = 10 MPa, while the excess hydrogen uptake shows a maximum of 7.46 wt % at p = 6 MPa. Impressively, at T = 298 K and p = 10 MPa, the Li(12)Si(60)H(60) array still exhibits a total hydrogen uptake of 3.88 wt % at the vdW gap of 8.2 A. These results clearly indicate that the composite, Li(12)Si(60)H(60) fullerene, is a promising candidate for hydrogen storage.

In this work, lattice Monte Carlo was used to study the effects of crowding on the self-assembly of surfactants. Simulation results show that crowding strongly shifts the critical micelle concentration (CMC) of surfactants from the bulk value. Two effects originated from crowding are found to govern the CMC shift: one is the depletion effect by crowding agents and the other is the available volume for micelle formation. The depletion effects inevitably result in the enrichment of surfactants in crowding-free regions and cause the decrease in CMC. On the other hand, the appearance of crowding agents decreases the available volume for micelle formation, which reduces the conformational entropy and impedes the micelle formation. Three factors, including the radius of crowding agents, the arrangement of crowding agents, and the volume fraction of crowding agents, are considered in this work to study the crowding effects. The trends of CMC shifts are interpreted from the competition between the depletion effects and the available volume for micelle formation.

In this work, we propose a method to stabilize a nucleus in the framework of lattice density-functional theory (LDFT) by imposing a suitable constraint. Using this method, the shape of critical nucleus and height of the nucleation barrier can be determined without using a predefined nucleus as input. As an application of this method, we study the nucleation behavior of vapor-liquid transition in nanosquare pores with infinite length and relate the observed hysteresis loop on an adsorption isotherm to the nucleation mechanism. According to the dependence of hysteresis and the nucleation mechanism on the fluid-wall interaction, $w$, in this work, we have classified $w$ into three regions ($wg0.9$, $0.1\ensuremath{\le}w\ensuremath{\le}0.9$, and $wl0.1$), which are denoted as strongly, moderately, and weakly attractive fluid-wall interaction, respectively. The dependence of hysteresis on the fluid-wall interaction is interpreted by the different nucleation mechanisms. Our constrained LDFT calculations also show that the different transition paths may induce different nucleation behaviors. The transition path dependence should be considered if morphological transition of nuclei exists during a nucleation process.

Accurate flood routing is essential for flood control in water resources planning and management. The Muskingum model continues to be popular method for flood routing. Its parameter estimation is a global optimization problem with the main objective to find a set of optimal model parameter values that attains a best fit between observed and computed flow. In order to improve the flood routing precision, a hybrid chaotic genetic algorithm (HCGA) based on chaotic sequence and GA is proposed for parameter estimation of Muskingum model. Empirical results that involve historical data from existed paper reveal the proposed HCGA outperforms other approaches in the literature.

It is known that the thermoacidophilic archaebacterium Sulfolobus acidocaldarius can grow in hot springs at 65-80 degrees C and live in acidic environments (pH 2-3); however, the origin of its unusual thermal stability remains unclear. In this work, using a vesicle as a model, we study the thermal stability and rupture of archaebacterial cell membrane. We perform a simulation investigation of the structure-property relationship of monolayer membrane formed by bolaform lipids and compare it with that of bilayer membrane formed by monopolar lipids. The origin of the unusually thermal stability of archaebacterial cell and the mechanism for its rupture are presented in molecular details.

In recent years, artificial neural networks (ANN) have emerged as a novel identification technique for the forecasting of hydrological time series. However, they represent their knowledge in terms of a weight matrix that is not accessible to human understanding at present. The purpose of this study is to develop a flow prediction method, based on the genetic programming (GP), which is an evolutionary computing method that provides ‘transparent’ and structured system identification. In terms of statistical characteristic of reservoir inflow sequence data, the autocorrelation function is employed to make certain amount of lagged input variables and the root mean square error is adopted as fitness of evaluation. The GP model is examined using the long-term observations of monthly river flow discharges. Through the comparison of its performance with those of the ANN, it is demonstrated that the GP model is an effective algorithm to forecast the long-term discharges.

A model with temperature-independent parameters is proposed for the calculation of viscosities for liquid mixtures. It is used to estimate and predict the viscosities for diverse binary and ternary mixtures, including aqueous and partially miscible systems. For 70 binaries (2033 data points), the grand absolute average deviation percent (AAD) is 1.60 from use of the parameters regressed from the data at a constant temperature. Moreover, for 23 ternaries (560 data points) the AAD is 2.76

On the basis of the coarse-grained model, we performed Brownian dynamics simulations to investigate behavior of the polyelectrolyte (PE)-macroion complexations in 1:1 and 3:1 salt contents. Our simulation results show that in 3:1 salt content there exists a critical salt concentration (CSC), which is determined by the charge stoichiometry, for the breakup of the PE-macroion complexations. Beyond the CSC concentration, an obvious depletion appears in the macroion-macroion and macroion-PE interactions, which is absent in 1:1 salt content. Both the mobilities of macroions and PEs increase monotonically with increasing the salt concentration in 1:1 and 3:1 salt contents. And the mobility in 3:1 salt content is always larger than that in corresponding 1:1 salt content, which is due to the fact that in 3:1 salt content the PE-macroion complexations are looser than those in 1:1 salt content. Moreover, we observed the collapse and re-expansion of PE chains with the increase of the salt concentration in the PEs-macroions systems of 3:1 salt content, which is due to the charge inversion of PE chains induced by the adsorption of trivalent cations. In addition, we also explored the effects of salt concentration and the length and charge density of PE chains. Our simulation results show that the effects of the length and charge density of PE chains in both salt contents on the radial distribution functions (RDFs) between macroions and between a macroion and a PE segment are similar to these in salt free solution basically. However, we observed an interesting phenomenon that the gyration radius of PE chains in the system of 3:1 salt content is not affected significantly by its charge density, while that in 1:1 salt content increases monotonically.

We propose a density-functional theory for inhomogeneous polyatomic fluids with complex architecture by introducing a different representation for the polymers. This representation gives an efficient hierarchical algorithm to calculate the direct bonding connectivity integral for polymers with complex architecture, such as linear, star, branched, and dendritic structures. A comparison with the available simulated data for linear and star polymers confirms the accuracy of the present theory in reproducing the density profiles of the two types of polymer in the slits. By using the proposed algorithm, we also explore partitioning coefficients of polymers of different architectures in a slit, and find that the partitioning coefficients of branched, star, and dendrimer forms of 22-mers decrease to a minimum at extremely low packing fraction, and then increase monotonically with packing fraction. Moreover, it is found that it is more difficult for a linear polymer of 22-mers to enter the slit than for branched, star, and dendritic polymers. In addition, we also investigate the self-assembly of diblock copolymers with different tails in a slit. It is found that the linear copolymer self-assembles into a trilayer film structure, while copolymers with branched and dendritic tails self-assemble into a five-layer film structure. Interestingly, the copolymer with a star tail self-assembles into a trilayer film structure, and then the trilayer structure evolves into a five-layer structure with increase of the bulk packing fraction in the case studied.

A Brownian dynamics (BD) simulation is performed to investigate the effect of the bridging conformation of a polyelectrolyte (PE) with two charged heads (two-heads PE) on the radial distribution function (RDF) and diffusion behavior of macroions on the basis of the coarse grained model. For comparison, the system containing macroions and the PE with only one charged head (one-head PE) is also investigated. The simulation results indicate that, at low concentrations, the bridging effect of the two-heads PE chain leads to correlation of macroions. The reason is that at low concentration the gyration radius of the PE chain is less than the average distance between two macroions. When the two-heads PE chains are adsorbed on different macroions, the bridging effect of the PE chain dominates the RDF and diffusion behavior of the macroions. With the increase of the concentration of the system, when the gyration radius of the PE chain is greater than the average distance between two macroions, the bridging effect of the PE chain becomes trivial. By investigating the mechanism of the two-heads PE chain affecting the static and dynamic properties of the macroions, we can provide useful information for the synthesis of stabilizers and destabilizers of colloidal particles.

In this work, the kinetic process of collision-driven solute exchange in an aqueous phase in which micelles are used as solute carriers is investigated by dissipative particle dynamics simulations. Here, we try to answer two questions about the exchange process of hydrophobic solute molecules: How the solute molecules are exchanged and what factors affect the process. For the first question, the simulation results indicate that, after a stage of intermittent collision between two neighboring aggregates, there are roughly three sequential events in a coalescence stage: (1) molecular contact, (2) neck formation, and (3) neck growth. The coalescence stage is followed by a stage of solute transfer and diffusion. It is found that there are two rate-limiting steps in the whole process of solute exchange, i.e., the break of the water film between two neighboring aggregates and the nucleation of a pore between two surfactant films. For the second question, the effects of the collision velocity, the surface tension, the repulsive interaction between the surfactant films of the colliding aggregates, as well as the steric repulsion are examined. For example, the simulation results show that the depletion force plays an important role during the coalescence stage, while the initial collision velocity basically does not change the fusion ratio. The results also demonstrate that the surface tension and interaction show different effects on the different stages of a solute exchange process.

In this work, we study the cooperative adsorption of fluids in a heterogeneous pore, in which the pore walls are composed of homogeneous substrates with chemical groups (CGs) decorating them. The adsorption caused by the homogeneous substrates alone and that by CGs do not add up to the overall adsorption, indicating the existence of a cooperative effect. The cooperative effect is the source of cooperative adsorption, and is characterized in this work by the ratio of the overall adsorption to the sum of adsorption by the substrate only and that by CGs. It is found that the cooperative adsorption does not depend monotonically on the substrate or the CGs. Two different origins of the cooperative adsorption play different roles depending on which one dominates the overall adsorption. Our simulations reveal that, when the homogeneous substrate dominates the overall adsorption, weakening of the attractive fluid-substrate interaction or alternatively strengthening of the fluid-CGs interaction leads to a stronger cooperative effect and enhances the cooperative adsorption. However, when CGs dominate the overall adsorption, weakening of the attractive fluid-CG interaction or strengthening the fluid-substrate interaction results in strong cooperative adsorption. In order to investigate the effects of the distribution of CGs on cooperative adsorption, a design-test method is generalized and used in this work. Simulation results show that the overall adsorption can be significantly affected by the CG distribution.

The accurate and robust short-term load forecasting (STLF) plays a significant role in electric power operation. The accuracy of STLF is greatly related to the selected the main relevant influential factors. However, how to select appropriate influential factor is a difficult task because of the randomness and uncertainties of the load demand and its influential factors. In this paper, a novel method of genetic programming (GP) with rough sets (RS) theory is developed to model STLF to improve the accuracy and enhance the robustness of load forecasting results. RS theory is employed to process large data and eliminate redundant information in order to find relevant factors to the short-term load, which are used as sample sets to establish forecasting model by means of GP evolutional algorithm. The presented model is applied to forecast short-term load using the actual data from GuiZhou power grid in China. The forecasted results are compared with BP artificial neural Network with RS theory, and it is shown that the presented forecasting method is more accurate and efficient.

In this communication, ternary square-well fluid mixtures are simulated using the Monte Carlo method at a variety of reduced densities, molecular size ratios, intermolecular energies and reduced temperatures. Based on the simulated results, radial distribution functions, coordination numbers and internal energies as well as the compressibility factors are reported, which provide the microstructure of the ternary fluids and the background for testing current thermodynamic models. Furthermore, three previous coordination number models for the binary square-well fluid mixtures are evaluated. A modified model is proposed to correlate binary and ternary data with satisfactory accuracy.

Based on the computer simulations of others of square-well mixtures, a predictive model for the coordination numbers has been proposed. This model and its modification have been extensively tested, and compared with the low density, Lee-Sandler and Lee-Chao models in terms of the Monte Carlo simulation data. For its simplicity and reasonable accuracy, the model can be used to predict the properties of square-well fluids and to develop equations of state that will be discussed in a subsequent paper.

New coordination number models for square-well (SW) fluids are incorporated with the generalized van der Waals partition function to develop equations of state for both pure and mixture SW fluids. The equations of state have been extensively tested with the Monte Carlo simulation data, of which three sets (18 data points) for the pure SW fluids are produced in this work. The results show that, without any parameters, our model reasonably describes not only the PVT behaviors but also the second and third virial coefficients of the model fluids. In addition, a comprehensive comparison has been made between our models and the other equations of state derived from the Lee-Chao and Lee-Sandler coordination number correlations.

Catalyzed by phenylalanine ammonia-lyase from Rhodotorula glutinis, 2% trans-cinnamic acid and 0.5 mol/l (15NH4)2SO4 was bioconverted to 15NL-phenylalanine. The yield and the purity of 15NL-phenylalanine reached 71 and 99.3%, respectively. The results showed that 96% of 15N was labeled on the l-phenylalanine and 88% of (15NH4)2SO4 was recovered. The present paper provides a new and economic way for biosynthesis of 15NL-phenylalanine.

In this work, we first show that there are only five independent interchange parameters in the surfactant-solvent-interface system in Larson's model, and then adsorption and morphology transition of surfactants on hydrophobic surfaces are studied by extensive lattice Monte Carlo simulations. In our simulations, we found that there exist six adsorbed morphologies: (1) premature admicelle, (2) hemisphere, (3) hemisphere-hemicylinder mixture, (4) wormlike hemicylinder, (5) perforated monolayer, and (6) monolayer. The surface morphologies and the amount of adsorption on hydrophobic surfaces are found to be affected obviously by two interchange parameters. One is the attractive interaction between tail groups and surface (chiTS), and the other is the solubility of head groups in bulk (chiHW). Phase diagrams in chiHW versus chiTS planes for surfactants with different hydrophobicities (chiTW) and for surfactants with different molecular structures are determined in this work, from which the transitions of surface morphologies and adsorption behaviors are discussed.

A common computational method for the characterization of porous materials is to calculate the adsorption isotherm of fluids in the materials from the preassumed wall–fluid potential. If the wall–fluid potential is unknown, the common computational method becomes invalid. In a realistic experiment, however, it is common to know the experimental adsorption isotherm of nitrogen and not to know the wall–fluid potential. Here we propose a stepwise approximation for modeling wall–fluid potential under conditions where only the adsorption isotherm of nitrogen is measured experimentally. Based on the modeled wall–fluid potential, we can characterize the porous materials and predict the adsorption of other adsorbates on the materials. It is expected that the approach would provide a powerful means for the characterization of novel materials under conditions where only the experimental adsorption isotherm is available.

The meltinglike transition of the ${\mathrm{Cu}}_{1}{\mathrm{Au}}_{54}$ and ${\mathrm{Cu}}_{12}{\mathrm{Au}}_{43}$ clusters is investigated by canonical Monte Carlo simulations, based on the second-moment approximation of the tight-binding potentials. The structures of both the ${\mathrm{Cu}}_{1}{\mathrm{Au}}_{54}$ and ${\mathrm{Cu}}_{12}{\mathrm{Au}}_{43}$ clusters, shown to be icosahedral, are obtained from the so-called semi-grand-canonical ensemble Monte Carlo simulation at $100\phantom{\rule{0.3em}{0ex}}\mathrm{K}$. A core-shell structure is found in ${\mathrm{Cu}}_{1}{\mathrm{Au}}_{54}$, with a single Cu atom in the center and 54 Au atoms on the surface and in interior shells of the cluster. On the other hand, ${\mathrm{Cu}}_{12}{\mathrm{Au}}_{43}$ possesses a three-shell onionlike structure, with a single Au atom located in the center, 12 Cu atoms in the middle shell, and 42 Au atoms occupying the surface shell of the cluster. Melting characteristics are observed by the changes in the caloric curve, heat capacity, root-mean-square bond-length fluctuation, and deformation parameter. It is found that doping of ${\mathrm{Au}}_{55}$ with a single Cu atom can sharply raise the melting point of the cluster. In addition, the three-shell onionlike structure can be transformed into the core-shell structure at the higher temperatures after melting. It is also found that surface segregation of Au atoms in ${\mathrm{Cu}}_{1}{\mathrm{Au}}_{54}$ and ${\mathrm{Cu}}_{12}{\mathrm{Au}}_{43}$ occurs in the liquid phase. In addition, the simulation results show that the melting point increases with the concentration of Cu in the 55-atom Cu-Au bimetallic cluster.