scholarly journals Complex Reaction Network Thermodynamic and Kinetic Autoconstruction Based on Ab Initio Statistical Mechanics: A Case Study of O2 Activation on Ag4 Clusters

Author(s):  
Weiqi Wang ◽  
Xiangyue Liu ◽  
Jesús Pérez-Ríos
2017 ◽  
Vol 19 (39) ◽  
pp. 26986-26995 ◽  
Author(s):  
Ru-Fang Zhao ◽  
Le Yu ◽  
Fu-Qiang Zhou ◽  
Jin-Feng Li ◽  
Bing Yin

A combined ab initio and DFT study is performed in this work to explore the superhalogen properties of polynuclear structures based on the ligands of –OH, –OOH and –OF.


Author(s):  
Tangjie Gu ◽  
Wen Zhu ◽  
Bo Yang

Ethanol steam reforming is one of the most widely used processes for hydrogen production, but the mechanism of the whole reaction pathway from ethanol to CO and CO2 has not...


2013 ◽  
Vol 117 (43) ◽  
pp. 11072-11085 ◽  
Author(s):  
Donghyun Lee ◽  
Loren Greenman ◽  
Mohan Sarovar ◽  
K. Birgitta Whaley

2016 ◽  
Vol 195 ◽  
pp. 497-520 ◽  
Author(s):  
Jonny Proppe ◽  
Tamara Husch ◽  
Gregor N. Simm ◽  
Markus Reiher

For the quantitative understanding of complex chemical reaction mechanisms, it is, in general, necessary to accurately determine the corresponding free energy surface and to solve the resulting continuous-time reaction rate equations for a continuous state space. For a general (complex) reaction network, it is computationally hard to fulfill these two requirements. However, it is possible to approximately address these challenges in a physically consistent way. On the one hand, it may be sufficient to consider approximate free energies if a reliable uncertainty measure can be provided. On the other hand, a highly resolved time evolution may not be necessary to still determine quantitative fluxes in a reaction network if one is interested in specific time scales. In this paper, we present discrete-time kinetic simulations in discrete state space taking free energy uncertainties into account. The method builds upon thermo-chemical data obtained from electronic structure calculations in a condensed-phase model. Our kinetic approach supports the analysis of general reaction networks spanning multiple time scales, which is here demonstrated for the example of the formose reaction. An important application of our approach is the detection of regions in a reaction network which require further investigation, given the uncertainties introduced by both approximate electronic structure methods and kinetic models. Such cases can then be studied in greater detail with more sophisticated first-principles calculations and kinetic simulations.


Author(s):  
L. K. Doraiswamy

Procedures were formulated in Chapter 5 for treating complex reactions. We now turn to the design of reactors for such reactions. Continuing with the ethylation reaction, we consider the following reactor types for which design procedures were formulated earlier in Chapter 4 for simple reactions: batch reactors, continuous stirred reactors (or mixed-flow reactors), and plug-flow reactors. However, we use the following less formal nomenclature: A = aniline, B = ethanol, C = monoethyaniline, D = water, E = diethylaniline, F = diethyl ether, and G = ethylene. The four independent reactions then become Using this set of equations as the basis, we now formulate design equations for various reactor types. Detailed expositions of the theory are presented in a number of books, in particular Aris (1965, 1969) and Nauman (1987). Consider a reaction network consisting of N components and M reactions. A set of N ordinary differential equations, one for each component, would be necessary to mathematically describe this system. They may be concisely expressed in the form of Equation 5.5 (Chapter 5), or . . . d(cV)/dt = vrV (11.1) . . . The use of this equation in developing batch reactor equations for a typical complex reaction is illustrated in Example 11.1.


2014 ◽  
Vol 70 (a1) ◽  
pp. C927-C927
Author(s):  
Marie Colmont ◽  
Lukas Palatinus ◽  
Marielle Huvé ◽  
Olivier Mentré ◽  
Pascal Roussel

This communication will present the case study of ALa5O5(VO4)2 (A= Li, Na, K, Rb), example of the use of a combination of Precession Electron and X-ray Powder Data for the solution and the refinement of new materials. Indeed, an original structural type has been evidenced in the system (A, La, V, O) with A=Li, Na, K, Rb. Attempts to solve the structure ab initio on X-ray powder data were unsuccessful (more particularly because the powder was a mixture of the title compound and of unreacted precursors). The structure was finally solved by charge flipping using Precession Electron Data (3D tomography) on a nanocrystal, enabling a posteriori the good formulation of a pure powder. This powder was then classically refined by Rietveld method showing the correctness of the electron-solved structure. It crystallizes in a monoclinic unit cell with space group C2/m and a=20.2282(14) b=5.8639(4) c=12.6060(9) Å and β=117.64(1)0. The ALa5O5(VO4)2 structure is built of (OLa4) tetrahedral units creating Crenel-like 2D ribbons. These ribbons, surrounded by four isolated VO4 tetrahedra, are creating channels parallel to b axis in which A+ ions are located.


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