surface reaction kinetics
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Fuel ◽  
2021 ◽  
Vol 287 ◽  
pp. 119503
Author(s):  
Ahmed Hassan ◽  
Taraneh Sayadi ◽  
Martin Schiemann ◽  
Viktor Scherer

Author(s):  
Bruno Lacerda de Oliveira Campos ◽  
Karla Herrera Delgado ◽  
Stefan Wild ◽  
Felix Studt ◽  
Stephan Pitter ◽  
...  

Correction for ‘Surface reaction kinetics of the methanol synthesis and the water gas shift reaction on Cu/ZnO/Al2O3’ by Bruno Lacerda de Oliveira Campos et al., React. Chem. Eng., 2021, 6, 868–887; DOI: 10.1039/D1RE00040C


Author(s):  
Bruno Lacerda de Oliveira Campos ◽  
Karla Herrera Delgado ◽  
Stefan Wild ◽  
Felix Studt ◽  
Stephan Pitter ◽  
...  

A three-site mean-field extended microkinetic model was developed based on ab initio DFT calculations from the literature, in order to simulate the conversion of syngas (H2/CO/CO2) to methanol on Cu...


2021 ◽  
Author(s):  
Shenglong Gan ◽  
Min Deng ◽  
Dongfang Hou ◽  
Lei Huang ◽  
XiuQing Qaio ◽  
...  

Optimization of cocatalyst is promising and of great significance in enhancing photocatalytic H2 generation from the perspective of understanding the charge separation, surface reaction kinetics, and distribution of active sites....


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Joonhyuck Park ◽  
Arun Jayaraman ◽  
Alex W. Schrader ◽  
Gyu Weon Hwang ◽  
Hee-Sun Han

AbstractThe optical and electronic performance of quantum dots (QDs) are affected by their size distribution and structural quality. Although the synthetic strategies for size control are well established and widely applicable to various QD systems, the structural characteristics of QDs, such as morphology and crystallinity, are tuned mostly by trial and error in a material-specific manner. Here, we show that reaction temperature and precursor reactivity, the two parameters governing the surface-reaction kinetics during growth, govern the structural quality of QDs. For conventional precursors, their reactivity is determined by their chemical structure. Therefore, a variation of precursor reactivity requires the synthesis of different precursor molecules. As a result, existing precursor selections often have significant gaps in reactivity or require synthesis of precursor libraries comprising a large number of variants. We designed a sulfur precursor employing a boron-sulfur bond, which enables controllable modulation of their reactivity using commercially available Lewis bases. This precursor chemistry allows systematic optimization of the reaction temperature and precursor reactivity using a single precursor and grows high-quality QDs from cores of various sizes and materials. This work provides critical insights into the nanoparticle growth process and precursor designs, enabling the systematic preparation of high-quality QD of any sizes and materials.


Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1744
Author(s):  
Changsun Eun

We present a simple reaction model to study the influence of the size, number, and spatial arrangement of reactive patches on a reactant placed on a plane. Specifically, we consider a reactant whose surface has an N × N square grid structure, with each square cell (or patch) being chemically reactive or inert for partner reactant molecules approaching the cell via diffusion. We calculate the rate constant for various cases with different reactive N × N square patterns using the finite element method. For N = 2, 3, we determine the reaction kinetics of all possible reactive patterns in the absence and presence of periodic boundary conditions, and from the analysis, we find that the dependences of the kinetics on the size, number, and spatial arrangement are similar to those observed in reactive patches on a sphere. Furthermore, using square reactant models, we present a method to significantly increase the rate constant by sequentially breaking the patches into smaller patches and arranging them symmetrically. Interestingly, we find that a reactant with a symmetric patch distribution has a power–law relation between the rate constant and the number of reactive patches and show that this works well when the total reactive area is much less than the total surface area of the reactant. Since our N × N discrete models enable us to examine all possible reactive cases completely, they provide a solid understanding of the surface reaction kinetics, which would be helpful for understanding the fundamental aspects of the competitions between reactive patches arising in real applications.


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