Optimal catalyst texture in macromolecule conversion: A computational and experimental study

Semeykina, Viktoriya; Malkovich, Evgeny; Bazaikin, Y.; Лысиков, А. И.; Пархомчук, Е. В.

doi:10.1016/j.ces.2018.05.005

Cited by 11 publications

(4 citation statements)

References 22 publications

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“…A theoretical estimation of catalyst performance using geometrical characteristics of the porous media based on Monte Carlo methods and the graph theory was done on evolution of alumina catalyst texture during macromolecule conversion in heavy oil hydroprocessing [47]. In this study, a unimodal mesoporous structure of conventional catalyst and bimodal meso-/macroporous structure of the catalyst were modeled.…”

Section: Supported Solid Catalystmentioning

confidence: 99%

Catalysts for Hydroprocessing of Heavy Oils and Petroleum Residues

Tye¹

2019

Processing of Heavy Crude Oils - Challenges and Opportunities

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With the increasing demand of petroleum-derived products due to the world population and development, upgrading of crude oil with heavier quality and petroleum residues is unavoidable. Hydroprocessing is a preferable process for heavy oil upgrading. The process is operated with the presence of a catalyst, and catalysis plays an important role in the process. An overview regarding the catalyst design such as the catalyst active metal, active phase, support properties, and catalyst structure for heavy oil hydroprocessing is provided. There also include some recent advancements related to catalytic hydroprocessing of heavy oils and residue processes. Further catalyst performance improvement will likely come from catalyst optimization and better catalyst deactivation resistance resulting from metal poisoning and coke formation.

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Section: Supported Solid Catalystmentioning

confidence: 99%

Catalysts for Hydroprocessing of Heavy Oils and Petroleum Residues

Tye¹

2019

Processing of Heavy Crude Oils - Challenges and Opportunities

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“…To describe a pore network for a packing of monosize spheres Voronoi tessellation and random walk method were utilized by Richard et al [ 42 ], the results were well correlated with an experimental data obtained on the transverse diffusion. Semeykina et al [ 43 ] applied Voronoi diagram for tortuosity calculations to define the diffusion coefficient for the optimal catalyst texture via Dijkstra’s algorithm to find the shortest path and demonstrated the computational efficiency as well as relative simplicity in the implementation. However, the lack of appropriately reflected relationships between the compact morphology parameters and transport properties, in particular effective diffusivity, has led our study to aim at disclosing the relationship between Voronoi parameters and tortuosity which will allow anticipating optimum solutions for particle mixture characteristics in particular particle size ratio and mixture composition.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Tortuosity in Compacts of Ternary Mixtures of Spherical Particles

et al. 2020

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Herein, an approach is proposed to analyze the tortuosity of porous electrodes using the radical Voronoi tessellation. For this purpose, a series of particle compacts geometrically similar to the actual porous electrode were generated using discrete element method; the radical Voronoi tessellation was constructed for each compact to characterize the structural properties; the tortuosity of compact porous structure was simulated by applying the Dijkstra’s shortest path algorithm on radical Voronoi tessellation. Finally, the relationships were established between the tortuosity and the composition of the ternary particle mixture, and between the tortuosity and the radical Voronoi cell parameters. The following correlations between tortuosity values and radical Voronoi cell parameters were found: larger faces and longer edges of radical Voronoi cell leads to the increased fraction of larger values of tortuosity in the distribution, while smaller faces and shorter edges of radical Voronoi cell contribute to the increased fraction of smaller tortuosity values, being the tortuosity values more uniform with narrower distribution. Thus, the compacts with enhanced diffusion properties are expected to be obtained by packing particle mixtures with high volume fraction of small and medium particles. These results will help to design the well-packed particle compacts having improved diffusion properties for various applications including porous electrodes.

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“…Studies regarding the synthesis of hierarchical meso-macroporous alumina supported catalysts [26,27] and their performance in hydrodemetallization process [28,29] are ongoing.…”

Section: Introductionmentioning

confidence: 99%

Synthesis and Characterization of Multi‐Modal γ‐Al₂O₃: A Systematic Investigation on the Optimization of Hydrodemetallization Catalyst Preparation

Ghassabzaadeh

Niaei

Rashidzadeh³

2020

ChemistrySelect

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The pore structure of hydrodemetallization catalysts plays a vital role in their lifetime and thus, on the process economy. In this investigation, a multi-modal meso and macroporous alumina has been prepared by using aluminum alkoxides. To tune the alumina properties to the desired values, a systematic design of experiments was applied to propose correlations between the synthesis parameters and catalyst properties. Several factors, which are effective on the specifications of the prepared multi-modal alumina, were analyzed and the dominant factors were identified. The results predicted by the model were in agreement with the experimental data. The analysis of the results showed that the prepared optimal sample had an average pore diameter and specific surface area of 21.2 nm and 341 m 2 /gr, respectively. For the prepared catalyst, N 2 adsorption/desorption measurements showed a multimodal pore structure ranging from 2 to 100 nm in size.Finally, an HDM catalyst was prepared based on optimum alumina. The activity and performance of the prepared catalyst were compared with those of the commercial catalyst. At low space times, V-TPP conversion for commercial and prepared catalysts were 38.9 and 49.5 percent, respectively, showing a higher activity for the prepared catalyst.

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Optimal catalyst texture in macromolecule conversion: A computational and experimental study

Cited by 11 publications

References 22 publications

Catalysts for Hydroprocessing of Heavy Oils and Petroleum Residues

Catalysts for Hydroprocessing of Heavy Oils and Petroleum Residues

Analysis of Tortuosity in Compacts of Ternary Mixtures of Spherical Particles

Synthesis and Characterization of Multi‐Modal γ‐Al₂O₃: A Systematic Investigation on the Optimization of Hydrodemetallization Catalyst Preparation

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Optimal catalyst texture in macromolecule conversion: A computational and experimental study

Cited by 11 publications

References 22 publications

Catalysts for Hydroprocessing of Heavy Oils and Petroleum Residues

Catalysts for Hydroprocessing of Heavy Oils and Petroleum Residues

Analysis of Tortuosity in Compacts of Ternary Mixtures of Spherical Particles

Synthesis and Characterization of Multi‐Modal γ‐Al2O3: A Systematic Investigation on the Optimization of Hydrodemetallization Catalyst Preparation

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Synthesis and Characterization of Multi‐Modal γ‐Al₂O₃: A Systematic Investigation on the Optimization of Hydrodemetallization Catalyst Preparation