Effects of Processing Factors on Microstructure and Diffusivity of Diethylbenzene Dehydrogenation Catalyst

2010 ◽  
Vol 297-301 ◽  
pp. 233-238
Author(s):  
Mohammad Ebrahim Zeynali ◽  
I. Soltani
Keyword(s):  
Grain Size ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Bulk Diffusion ◽  
Effective Diffusivity ◽  
Catalyst Pellet ◽  
Different Types ◽  
Effective Diffusivities ◽  
Processing Factors

In this study, different mechanisms of diffusion such as Knudsen and bulk were investigated for diethylbenzene diffusion into a catalyst and it was concluded that the pore sizes should be in the range that permit transitional diffusion (both Knudsen and bulk diffusion). The catalyst grain size can be controlled and varied by different parameters such as speed and time of mixing, type of alkali, temperature and pH. Particle size distribution experiments were conducted for different types of alkali and speed of mixing to characterize the catalyst. The effects of grain size formed during coprecipitation on pore size distribution of the catalyst pellet which affect the effective diffusivity were discussed. Pore size distribution of the model catalyst was obtained and the effective diffusivities were calculated by numerical integration of Johanson-Stewart equation.

A Realistic Method to Describe the Role of Diffusion in Catalyst Design

2009 ◽  
Vol 294 ◽  
pp. 65-76
Author(s):  
Mohammad Ebrahim Zeynali
Keyword(s):  
Grain Size ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Nitrate Solution ◽  
Effective Diffusivity ◽  
Catalyst Design ◽  
Internal Surface Area ◽  
Co Precipitation

The dehydrogenation of diethylbenzene to divinylbenzene is a catalytic reaction. The catalyst for the dehydrogenation was prepared by co-precipitation of iron and chromium hydroxide from nitrate solution, followed by doping with potassium carbonate and drying. To make available the internal surface area of the catalyst for the reactant, the pores must be of the proper sizes to allow the reactant to diffuse and penetrate inside the catalyst pellets. The prepared catalyst was considered as a model for investigating the role of diffusion in catalyst design. In this study, different mechanisms of diffusion, such as Knudsen and bulk, were investigated for the case of diethylbenzene diffusion into the catalyst and it was concluded that the pore sizes should be in a range that permits transitional diffusion (both Knudsen and bulk diffusion). The catalyst grain size can be controlled and varied by acting on parameters such as the speed and time of mixing, type of alkali, temperature and pH. Particle size distribution experiments were conducted for different types of alkali and speeds of mixing in order to characterize the catalyst. The effects of the grain size, formed during co-precipitation, upon the pore size distribution of the catalyst pellet which affects the effective diffusivity were discussed. The pore size distribution of the model catalyst was obtained and the effective diffusivities were calculated by numerical integration of the Johanson-Stewart equation.

scholarly journals The Effects of Nano-SiO2 and Nano-TiO2 Addition on the Durability and Deterioration of Concrete Subject to Freezing and Thawing Cycles

Materials ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 3608 ◽  
Author(s):  
Fang Liu ◽  
Tonghuan Zhang ◽  
Tao Luo ◽  
Mengzhen Zhou ◽  
Weiwei Ma ◽  
...  
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Nano Particles ◽  
Nano Particle ◽  
Freezing And Thawing ◽  
Nano Tio2 ◽  
Industrial Computed Tomography ◽  
Different Types ◽  
Freezing And Thawing Cycles

The objective of this manuscript is to study the effects of nano-particle addition on the durability and internal deterioration of concrete subject to freezing and thawing cycles (FTCs). Fifteen nm of SiO2, 30 nm of SiO2, and 30 nm of TiO2 were added to concrete to prepare specimens with different contents. All the specimens were subjected to FTCs from 0 to 75. The mass of each specimen was measured once the FTCs reached 25, 50, and 75. Then the freezing and thawing resistance of the concrete was evaluated by computing the mass loss ratio. The pore fluid size distribution of the concrete was detected using nuclear magnetic resonance (NMR). The deterioration of the concrete subjected to FTCs was detected by industrial computed tomography (CT). The effect of different nano-particle sizes, different contents of nano-particles, and different types of nano-particles on the freezing and thawing resistance, the pore size, distribution, and the deterioration of the concrete were analyzed. The effects of FTCs on the pore size distribution and the internal deterioration of concrete were also studied. Compared to 30 nm-Nono-SiO2 (NS), 15 nm-NS had a better effect in improving the internal structure for concrete, and 30 nm-Nano-TiO2 (NT) also had a better effect in preventing pore and crack expansion.

Effect of Catalyst Diffusion Coefficient on Ethylbenzene Dehydrogenation

2011 ◽  
Vol 312-315 ◽  
pp. 1-6
Author(s):  
Mohammad Ebrahim Zeynali ◽  
Feridoon Mohammadi
Keyword(s):  
Diffusion Coefficient ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Effective Diffusion ◽  
Ethylbenzene Dehydrogenation ◽  
Catalyst Pellet ◽  
Effectiveness Factors ◽  
Pore Size Distributions ◽  
And Diffusion

The effective diffusion coefficients for a single catalyst pellet were determined by numerical integration of the Johnson-Stewart equation for bimodal and unimodal pore size distributions assuming a transitional diffusion regime. The effectiveness factors of a spherical catalyst pellet were determined at various pore size distribution probability density functions. Using effectiveness factors the production rates were determined. The results showed that the effectiveness factor and production rate are sensitive to catalyst pore size distribution and diffusion coefficient.

scholarly journals Mathematical modeling and simulation of gel drying with supercritical carbon dioxide

2005 ◽  
Vol 70 (1) ◽  
pp. 125-136 ◽  
Author(s):  
Aleksandar Orlovic ◽  
Stojan Petrovic ◽  
Dejan Skala
Keyword(s):  
Experimental Data ◽  
Carbon Dioxide ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Silica Gel ◽  
Particle Diameter ◽  
Effective Diffusivity ◽  
Supercritical Drying ◽  
Drying Time

Mathematical models of alumina/silica gel supercritical drying with carbon dioxide were studied using supercritical drying experimental data. An alumina/silica gel with zinc chloride was synthesized and dried with superciritical carbon dioxide, and its weight change was monitored as a function of drying time. The pore size distribution of the obtained aerogel was determined using the BET method and nitrogen adsorption/ desorption. The mathematical model of the supercritical drying of the wet gel was represented as unsteady and one-dimensional diffusion of solvent through the aerogel pores filled with supercitical carbon dioxide. Parallel pore model and pores in series model were developed on the basis of the measured porous structure of the aerogel. It was found that these models which use different effective diffusivity value for each pore size were in much better agreement with the experimental data than models which use an overall effective diffusivity. The local effective diffusivity coefficients were calculated using different tortuosity values for each pore size, and they were distributed according to the pore size distribution data. Model simulations of the superciritical drying with carbon dioxide confirmed that the drying temperature and gel particle diameter have a significant influence on the drying time.

scholarly journals Influence of Soil Pore System Properties on the Degradation Rates of Organic Substances during Soil Aquifer Treatment (SAT)

2019 ◽  
Vol 9 (3) ◽  
pp. 496 ◽  
Author(s):  
Thomas Fichtner ◽  
Nora Goersmeyer ◽  
Catalin Stefan
Keyword(s):  
Grain Size ◽  
Organic Matter ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Soil Layer ◽  
Size Fraction ◽  
Synthetic Wastewater ◽  
Soil Aquifer Treatment ◽  
Degradation Rates

Soil aquifer treatment (SAT) is a nature-inspired solution for improving the water quality through soil percolation. The biodegradation of organic matter typically occurs in the shallowest soil layer and it depends on the contaminant’s characteristics (water solubility, molecular structure) and specific soil properties (pore size distribution). The present study aims at identifying which grain size fraction of typically used sandy soils in the shallowest layer of SAT systems can provide the optimal conditions for microbiological growth that can be reached by a trade-off between soil moisture as well as nutrients and oxygen supply. For this, soil columns were used at a laboratory scale to determine the relationship between the pore size distribution of four different grain size fractions and biodegradation rates of organic matter from synthetic wastewater. The results obtained from this experimental setup indicate that bacterial colonies reached optimum growth when about 60% of the available pore space was filled with water. For the selected soil, this was achieved by the fraction with grain sizes in the range of 630 µm to 1000 µm, having pore diameters between 87 µm and 320 µm and a mean pore diameter of 230 µm.

Evaluation of the Effect of Catalyst Pore-Size Distribution on the Effectiveness Factor in Ethylbenzene Dehydrogenation by Orthogonal Collocation

2011 ◽  
Vol 316-317 ◽  
pp. 155-169
Author(s):  
Mohammad Ebrahim Zeynali
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Average Pore Size ◽  
Effectiveness Factor ◽  
Orthogonal Collocation ◽  
Average Pore ◽  
Catalyst Pellet ◽  
Pore Size Distributions ◽  
Styrene Production

The mathematical model for multicomponent diffusion in styrene production is given considering all six reactions involved in styrene production. The diffusion coefficients for catalyst pellet are calculated for unimodal and bimodal pore size distributions using trapezoidal rule of integration. The effects of standard deviation and average pore size on the diffusion coefficient are determined. The differential equations are converted to algebraic equations and solved by the orthogonal collocation method. The effectiveness factor of catalyst pellet in styrene production is calculated for various pore sizes. It is seen that the average pore size and pore size distribution affects the production rate and effectiveness factor significantly.

Modeling of Injection-Induced Particle Movement Leading to the Development of Thief Zones

2021 ◽  
Author(s):  
Qianru Qi ◽  
Iraj Ershaghi
Keyword(s):  
Grain Size ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Size Exclusion ◽  
Published Data ◽  
Particle Movement ◽  
Grain Sizes ◽  
Modeling Approach

Abstract This paper is a contribution to failure prediction of unconsolidated intervals that could have a negative impact on injection efficiency because of susceptibility to structural changes under fluid injection processes. In unconsolidated formations, formation fines may be subjected to drag forces by injected water because of poor cementation. This results in small grain moments, and continuation can result in a gradual increase in permeability and eventual development of washed-out or thief zones. This paper presents a new modeling approach using information from profile surveys and grain and pore size distribution to model the process of injection and the induced particle movement. The motivation came from field observations and realization of permeability increase from profile surveys and substantial fines movement, leading to an increase in rock permeability. A series of case studies based on realistic published data on pore and grain size distribution are included to demonstrate the estimated increases in formation permeability. In our modeling approach, once we establish the range of grain sizes that fits the criterion for particle movement, a probabilistic algorithm, developed for the study, is applied to track changes in porosity and associated variations in permeability. This algorithm, presented for the first time, considers a stochastic approach to monitor the reservoir particle movements, pore size exclusion by particle accumulation and their resultant changes in rock properties. For this methodology, we ignored potential effects of wettability and clay swelling, and considered perfect spheres to represent the various grain sizes. Predictions made using various realizations of channel formation and petrophysical alterations show the significance of having access to three sources of information; pore size distribution, grain size distribution, and profile surveys. Through inverse modeling using these pieces of information for a particular formation, we demonstrate how we can predict realistic changes and map rock transport properties.

pyGAPS: A Python-Based Framework for Adsorption Isotherm Processing and Material Characterisation

2019 ◽  
Author(s):  
Paul Iacomi ◽  
Philip L. Llewellyn
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Surface Area ◽  
Isosteric Heat ◽  
Material Characterisation ◽  
Mixture Adsorption ◽  
Surface Energetics ◽  
Adsorption Processing ◽  
User Friendly

Material characterisation through adsorption is a widely-used laboratory technique. The isotherms obtained through volumetric or gravimetric experiments impart insight through their features but can also be analysed to determine material characteristics such as specific surface area, pore size distribution, surface energetics, or used for predicting mixture adsorption. The pyGAPS (python General Adsorption Processing Suite) framework was developed to address the need for high-throughput processing of such adsorption data, independent of the origin, while also being capable of presenting individual results in a user-friendly manner. It contains many common characterisation methods such as: BET and Langmuir surface area, t and α plots, pore size distribution calculations (BJH, Dollimore-Heal, Horvath-Kawazoe, DFT/NLDFT kernel fitting), isosteric heat calculations, IAST calculations, isotherm modelling and more, as well as the ability to import and store data from Excel, CSV, JSON and sqlite databases. In this work, a description of the capabilities of pyGAPS is presented. The code is then be used in two case studies: a routine characterisation of a UiO-66(Zr) sample and in the processing of an adsorption dataset of a commercial carbon (Takeda 5A) for applications in gas separation.

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