The coupling of reaction and diffusion between neighboring active sites in the catalyst pore leads to the spatiotemporal fluctuation in component concentration, which is very important to catalyst performance and hence its optimal design. Molecular dynamics simulation with hard-sphere and pseudo-particle modeling has previously revealed the non-stochastic concentration fluctuation of the reactant/product near isolated active site due to such coupling, using a simple model reaction of A → B in 2D pores. The topic is further developed in this work by studying the concentration fluctuation due to such coupling between neighboring active sites in 3D pores. Two 3D pore models containing an isolated active site and two adjacent active sites were constructed, respectively. For the isolated site, the concentration fluctuation intensifies for larger pores, but the product yield decreases, and for a given pore size, the product yield reaches a peak at a certain reactant concentration. For two neighboring sites, their distance (d) is found to have little effect on the reaction, but significant to the diffusion. For the same reaction competing at both sites, larger d leads to more efficient diffusion and better overall performance. However, for sequential reactions at the two sites, higher overall performance presents at a smaller d. The results should be helpful to the catalyst design and reaction control in the relevant processes. 相似文献
Microorganisms such as bacteria and fungi play essential roles in many application fields, like biotechnique, medical technique and industrial domain. Microorganism counting techniques are crucial in microorganism analysis, helping biologists and related researchers quantitatively analyze the microorganisms and calculate their characteristics, such as biomass concentration and biological activity. However, traditional microorganism manual counting methods, such as plate counting method, hemocytometry and turbidimetry, are time-consuming, subjective and need complex operations, which are difficult to be applied in large-scale applications. In order to improve this situation, image analysis is applied for microorganism counting since the 1980s, which consists of digital image processing, image segmentation, image classification and suchlike. Image analysis-based microorganism counting methods are efficient comparing with traditional plate counting methods. In this article, we have studied the development of microorganism counting methods using digital image analysis. Firstly, the microorganisms are grouped as bacteria and other microorganisms. Then, the related articles are summarized based on image segmentation methods. Each part of the article is reviewed by methodologies. Moreover, commonly used image processing methods for microorganism counting are summarized and analyzed to find common technological points. More than 144 papers are outlined in this article. In conclusion, this paper provides new ideas for the future development trend of microorganism counting, and provides systematic suggestions for implementing integrated microorganism counting systems in the future. Researchers in other fields can refer to the techniques analyzed in this paper.