Photochemical preparation of ZnO nanoparticles

Preparation of zinc oxide nanoparticles from aqueous solutions containing zinc nitrate or formate using UV irradiation was investigated. Analysis of solid phase formed during irradiation confirmed the presence of zinc oxide or zinc peroxide nanoparticles ranging in size from 1 to 70 nm, depending on initial precursors. Annealing at temperatures 650–1000 °C results in forming of rice-like zinc oxide particles, up to hundreds of nm in size. Photochemical method yields material with high chemical purity and uniform particle size distribution. In addition, photo-induced doping of zinc oxide with lanthanum was studied. Presence of lanthanum in zinc oxide crystal lattice and post-preparation treatment in reduction atmosphere significantly increase the UV excitonic luminescence at 395 nm in radioluminescence spectra.     

Anchor points for the unified Brønsted acidity scale: the rCCC model for the calculation of standard Gibbs energies of proton solvation in eleven representative liquid media

The COSMO cluster-continuum (CCC) solvation model is introduced for the calculation of standard Gibbs solvation energies of protons. The solvation sphere of the proton is divided into an inner proton-solvent cluster with covalent interactions and an outer solvation sphere that interacts electrostatically with the cluster. Thus, the solvation of the proton is divided into two steps that are calculated separately: 1) The interaction of the proton with one or more solvent molecules is calculated in the gas phase with high-level quantum-chemical methods (modified G3 method). 2) The Gibbs solvation energy of the proton-solvent cluster is calculated by using the conductor-like screening model (COSMO). For every solvent, the solvation of the proton in at least two (and up to 11) proton-solvent clusters was calculated. The resulting Gibbs solvation energies of the proton were weighted by using Boltzmann statistics. The model was evaluated for the calculation of Gibbs solvation energies by using experimental data of water, MeCN, and DMSO as a reference. Allowing structural relaxation of the proton-solvent clusters and the use of structurally relaxed Gibbs solvation energies improved the accordance with experimental data especially for larger clusters. This variation is denoted as the relaxed COSMO cluster-continuum (rCCC) model, for which we estimate a 1σ error bar of 10 kJ mol(-1) . Gibbs solvation energies of protons in the following representative solvents were calculated: Water, acetonitrile, sulfur dioxide, dimethyl sulfoxide, benzene, diethyl ether, methylene chloride, 1,2-dichloroethane, sulfuric acid, fluorosulfonic acid, and hydrogen fluoride. The obtained values are absolute chemical standard potentials of the proton (pH=0 in this solvent). They are used to anchor the individual solvent specific acidity (pH) scales to our recently introduced absolute acidity scale.     

Fast calculation of multiobjective probability of improvement and expected improvement criteria for Pareto optimization

The use of surrogate based optimization (SBO) is widely spread in engineering design to reduce the number of computational expensive simulations. However, “real-world” problems often consist of multiple, conflicting objectives leading to a set of competitive solutions (the Pareto front). The objectives are often aggregated into a single cost function to reduce the computational cost, though a better approach is to use multiobjective optimization methods to directly identify a set of Pareto-optimal solutions, which can be used by the designer to make more efficient design decisions (instead of weighting and aggregating the costs upfront). Most of the work in multiobjective optimization is focused on multiobjective evolutionary algorithms (MOEAs). While MOEAs are well-suited to handle large, intractable design spaces, they typically require thousands of expensive simulations, which is prohibitively expensive for the problems under study. Therefore, the use of surrogate models in multiobjective optimization, denoted as multiobjective surrogate-based optimization, may prove to be even more worthwhile than SBO methods to expedite the optimization of computational expensive systems. In this paper, the authors propose the efficient multiobjective optimization (EMO) algorithm which uses Kriging models and multiobjective versions of the probability of improvement and expected improvement criteria to identify the Pareto front with a minimal number of expensive simulations. The EMO algorithm is applied on multiple standard benchmark problems and compared against the well-known NSGA-II, SPEA2 and SMS-EMOA multiobjective optimization methods.     

Towards a More General Concept of Inference

The main objective of this paper is to sketch unifying conceptual and formal framework for inference that is able to explain various proof techniques without implicitly changing the underlying notion of inference rules. We base this framework upon the so-called two-dimensional, i.e., deduction to deduction, account of inference introduced by Tichý in his seminal work The Foundation’s of Frege’s Logic (1988). Consequently, it will be argued that sequent calculus provides suitable basis for such general concept of inference and therefore should not be seen just as technical tool, but philosophically well-founded system that can rival natural deduction in terms of its “naturalness”.     

Evaluating the COSMO‐RS Method for Modeling Hydrogen Bonding in Solution

The ability of the Conductor‐like Screening Model for Realistic Solvation (COSMO‐RS) computational method to model hydrogen bond (HB) formation in solution is examined by comparing computational data with experimental data from literature. This is the first study of this kind where mixed solvents are also involved. Hydrogen bond formation is examined between neutral molecules, between acids and their anions, and between various anion receptor molecules and different anions in a number of aprotic solvents. HB formation equilibrium constants, the corresponding Gibbs’ free energies and, when available from the literature, enthalpies were calculated. The supermolecule (SM) approach and the contact probability (CP) approach were used. Both in the case of the SM and CP approach, good to very good correlations between the experiment and computations are found for complexes formed from neutral species, enabling quantitative predictions. When the HB acceptor is an anion, the correlations are poor and in some cases even qualitative predictions fail.     

Literatur

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Anwendung der Röntgenspektrographie für die Untersuchung kolloider Systeme

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