Solubility of benzil in binary alkane + dibutyl ether solvent mixtures. Comparison of predictive expressions derived from the nearly ideal binary solvent model

Experimental solubilities are reported for benzil dissolved in six binary mixtures containing dibutyl ether with hexane, heptane, octane, cyclohexane, methylcyclohexane, and 2,2,4-trimethylpentane at 25°C. Results of these measurements are compared to the predictions of equations developed previously for solubility in systems of nonspecific interactions. The most successful equation in terms of goodness of fit involved a volume fraction average of the excess Gibbs energies relative to the Flory-Huggins model, and predicted the experimental solubilities in the six systems studied to within an overall average absolute deviation of 3.4% and with a maximum deviation of 6.0%.     

Bridging the Green Gap: Metal–Organic Framework Heteromultilayers Assembled from Porphyrinic Linkers Identified by Using Computational Screening

In organic photovoltaics, porphyrins (PPs) are among the most promising compounds owing to their large absorption cross-section, wide spectral range, and stability. Nevertheless, a precise adjustment of absorption band positions to reach a full coverage of the so-called green gap has not been achieved yet. We demonstrate that a tuning of the PP Q- and Soret bands can be carried out by using a computational approach for which substitution patterns are optimized in silico. The most promising candidate structures were then synthesized. The experimental UV/Vis data for the solvated compounds were in excellent agreement with the theoretical predictions. By attaching further functionalities, which allow the use of PP chromophores as linkers for the assembly of metal-organic frameworks (MOFs), we were able to exploit packing effects resulting in pronounced redshifts, which allowed further optimization of the photophysical properties of PP assemblies. Finally, we use a layer-by-layer method to assemble the PP linkers into surface-mounted MOFs (SURMOFs), thus obtaining high optical quality, homogeneous and crystalline multilayer films. Experimental results are in full accord with the calculations, demonstrating the huge potential of computational screening methods in tailoring MOF and SURMOF photophysical properties.     

An AB Initio Correlated Computation of Vibrations in the CIONO2 Molecule

Abstract

ClONO₂ is treated ab initio by the second order M?ller-Plesset perturbation approach with the 6-31G? basis set. The minimum-energy structure is planar (C_s symmetry) while in the activated complex for internal rotation around the NO bond the Cl atom exhibits torsion by 90° but the structure has the C_s symmetry, too. For both structures harmonic vibrational frequencies and IR intensities are calculated. The agreement with available observed data from matrix isolation is very good. The MP₂ frequencies are mostly somewhat lower comparing to related SCF values. The energetics is also evaluated in the MP4 fourth order perturbation treatment. The best value found for the barrier of internal rotation is 31 kJ/mol, i.e. significantly low.     

Predicting DAX trends from Dow Jones data by methods of the mathematical theory of democracy

The mathematical theory of democracy operates on the indices of popularity and universality which are used to find socially optimal representatives and representative bodies. Regarded mathematically, neither the ‘society’, nor its ‘representatives’ are necessarily human, so that some objects can represent the behavior of other objects. This idea is applied to predicting the DAX-trends (German stock index) from the actual Dow-Jones data; the current fluctuations of stock prices in New York are regarded as representative indicators of future stock price fluctuations in Frankfurt. In particular, it is found that American Express anticipates on the average the price ±fluctuations of 2/3 of the DAX stocks. The statistical significance of the null hypothesis that such a bias from the uncertainty 50% can occur by chance is only 3.5%.     

森林地表火火行为预测预报系统

本文从地表火蔓延的本质入手，建立了一整套求解地表火行为特征量的数学模型，并运用现代软件编制技术，成功地编制出预测预报地表火行为的计算机软件。该系统能预测复杂地形、气象条件和可燃物分布情形下，火蔓延过程中不同阶段的火行为状况。算例结果表明，系统在预测结果的合理性和准确性等方面优于美国的BEHAVE程序。     

Numerical aspects of calculation of confined swirling flows with internal recirculation

Predictions were performed for two different confined swirling flows with internal recirculation zones. The convection terms in the elliptic governing equations were discretized using three different finite differencing schemes: hybrid, quadratic upwind interpolation and skew upwind differencing. For each flow case, calculations were carried out with these schemes and successively refined grids were employed. For the turbulent flow case the k-ε turbulence model was used. The predicted cases were a laminar swirling flow investigated by Bornstein and Escudier, and a turbulent low-swirl case studied by Roback and Johnson. In both cases an internal recirculation zone was present. The laminar case is well predicted when account is taken of the estimated radial velocity component at the chosen inlet plane. The quadratic upwind interpolation and skew upwind schemes predict the main features of the internal recirculation zone also with a coarse grid. The turbulent case is well predicted with the coarse as well as the finer grids, the skew upwind and quadratic upwind interpolation schemes yielding results very close to the measurements. It is concluded that the skew upwind scheme reaches grid independence slightly before the quadratic upwind scheme, both considerably earlier than the hybrid scheme.     

Modelling of particle-wall collisions in confined gas-particle flows

This paper demonstrates that numerical simulations of confined particulate two-phase flows require a detailed modelling of particle—wall collisions which includes the wall surface structure and the particle shape. These effects are taken into account by “irregular bouncing” models which are based on the statistical treatment of the collision process. In this study, results obtained using various “irregular bouncing” models based on the impulse equations for a particle—wall collision are considered and compared with experimental observations. The wall roughness is simulated by assuming that the particle collides with a virtual wall which has a randomly distributed inclination with respect to the plane, smooth wall. A Gaussian distribution for this random inclination showed the best agreement with experimental results. Numerical predictions of a turbulent two—phase flow in a vertical channel, where the particle phase is treated using a Lagrangian approach, showed that the different models applied for a particle-wall collision have a strong effect on the particle velocity fluctuations and the mass flux profiles in the region of fully developed flow. The numerical simulations using the irregular bouncing models yielded considerably higher values for the particle velocity fluctuations, which also agreed better with the experimental values. This effect was most pronounced for large particles, where the distance they need to respond to the fluid flow is larger than the characteristic dimension of the confinement. On the other hand, the motion of small particles is less affected by the choice of the wall-collision model. These effects of the wall roughness on the velocity fluctuations of the dispersed phase have not been considered in previous studies using irregular bouncing models.     

Enhanced conformational sampling method for proteins based on the TaBoo SeArch algorithm: Application to the folding of a mini‐protein,chignolin

The conformational samplings are indispensible for obtaining reliable canonical ensembles, which provide statistical averages of physical quantities such as free energies. However, the samplings of vast conformational space of biomacromolecules by conventional molecular dynamics (MD) simulations might be insufficient, due to their inadequate accessible time‐scales for investigating biological functions. Therefore, the development of methodologies for enhancing the conformational sampling of biomacromolecules still remains as a challenging issue in computational biology. To tackle this problem, we newly propose an efficient conformational search method, which is referred as TaBoo SeArch (TBSA) algorithm. In TBSA, an inverse energy histogram is used to select seeds for the conformational resampling so that states with high frequencies are inhibited, while states with low frequencies are efficiently sampled to explore the unvisited conformational space. As a demonstration, TBSA was applied to the folding of a mini‐protein, chignolin, and automatically sampled the native structure (C_α root mean square deviation < 1.0 Å) with nanosecond order computational costs started from a completely extended structure, although a long‐time 1‐µs normal MD simulation failed to sample the native structure. Furthermore, a multiscale free energy landscape method based on the conformational sampling of TBSA were quantitatively evaluated through free energy calculations with both implicit and explicit solvent models, which enable us to find several metastable states on the folding landscape. © 2015 Wiley Periodicals, Inc.