scholarly journals Evaluating the effective diffusion coefficient of reactant gas in the catalyst layer of PEMFC using the fractal method considering the pore size distribution

Nano Select ◽  
2020 ◽  
Author(s):  
Yan Yin ◽  
Shiyu Wu ◽  
Yanzhou Qin ◽  
Yuwen Liu ◽  
Junfeng Zhang
Keyword(s):  
Diffusion Coefficient ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Effective Diffusion Coefficient ◽  
Effective Diffusion ◽  
Catalyst Layer ◽  
Fractal Method

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.

Diffusion of Heavy Oil in SiO2 Model Catalyst and FCC Catalyst

2012 ◽  
Vol 550-553 ◽  
pp. 158-163 ◽  
Author(s):  
Zi Yuan Liu ◽  
Sheng Li Chen ◽  
Peng Dong ◽  
Xiu Jun Ge
Keyword(s):  
Diffusion Coefficient ◽  
Pore Size ◽  
Effective Diffusion Coefficient ◽  
Pore Diameter ◽  
Effective Diffusion ◽  
Model Catalyst ◽  
Average Pore ◽  
Diffusion Factor ◽  
Fcc Catalyst ◽  
Fcc Catalysts

Through the measured effective diffusion coefficients of Dagang vacuum residue supercritical fluid extraction and fractionation (SFEF) fractions in FCC catalysts and SiO2model catalysts, the relation between pore size of catalyst and effective diffusion coefficient was researched and the restricted diffusion factor was calculated. The restricted diffusion factor in FCC catalysts is less than 1 and it is 1~2 times larger in catalyst with polystyrene (PS) template than in conventional FCC catalyst without template, indicating that the diffusion of SFEF fractions in the two FCC catalysts is restricted by the pore. When the average molecular diameter is less than 1.8 nm, the diffusion of SFEF fractions in SiO2model catalyst which average pore diameter larger than 5.6 nm is unrestricted. The diffusion is restricted in the catalyst pores of less than 8 nm for SFEF fractions which diameter more than 1.8 nm. The tortuosity factor of SiO2model catalyst is obtained to be 2.87, within the range of empirical value. The effective diffusion coefficient of the SFEF fractions in SiO2model catalyst is two orders of magnitude larger than that in FCC catalyst with the same average pore diameter. This indicate that besides the ratio of molecular diameter to the pore diameter λ, the effective diffusion coefficient is also closely related to the pore structure of catalyst. Because SiO2model catalyst has uniform pore size, the diffusion coefficient can be precisely correlated with pore size of catalyst, so it is a good model material for catalyst internal diffusion investigation.

Dissolution and precipitation reactions during acidic fluid percolation through different limestone samples

2020 ◽  
Author(s):  
Linda Luquot
Keyword(s):  
Diffusion Coefficient ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Transport Properties ◽  
Size Distribution ◽  
High Capacity ◽  
Co2 Injection ◽  
Geometrical Parameters ◽  
Calcite Dissolution ◽  
Geological Formation

<p>CO2 sequestration in deep geological formation is considered an option to reduce CO2 emissions in the atmosphere. After injection, the CO2 will slowly dissolve into the pore water producing low pH fluids with a high capacity for dissolving carbonates. Limestone rock dissolution induces geometrical parameters changes such as porosity, pore size distribution, or tortuosity which may consequently modify transport properties (permeability, diffusion coefficient). Characterizing these changes is essential for modelling flow and CO2 transport during and after the CO2 injection. Indeed, these changes can affect the storage capacity and injectivity of the formation.</p><p>Very few published studies evaluate the transport properties changes (porosity, permeability, pore size distribution, diffusion coefficient) due to fluid-rock interactions (dissolution and/or precipitation).</p><p>Here we report experimental results from the injection of acidic fluids (some of them equilibrated with gypsum) into limestone core samples of 25.4 mm diameter and around 25 mm length. We studied two different limestone samples: one composed of 73% of calcite and 27% of quartz, and the second one of 100% of dolomite. Experiments were realized at room temperature. Before and after each acidic rock attack, we measure the sample porosity, the diffusion coefficient and the pore size distribution.</p><p>We also imaged the 3D pore network by X-ray microtomography to evaluate the same parameters. During percolation experiments, the permeability changes are recorded and chemical samples taken to evaluate calcite dissolution and gypsum precipitation. Several dissolution/precipitation-characterization cycles are performed on each sample in order to study the evolution and relation of the different parameters.</p><p>These experiments show different dissolution regimes depending of the fluid acidity and of the</p><p>limestone samples in particular the initial local heterogeneity, and pore size distribution.</p>

scholarly journals Calculating structural and geometrical parameters by laboratory experiments and X-Ray microtomography: a comparative study applied to a limestone sample

2015 ◽  
Vol 7 (4) ◽  
pp. 3293-3337
Author(s):  
L. Luquot ◽  
V. Hebert ◽  
O. Rodriguez
Keyword(s):  
Diffusion Coefficient ◽  
Pore Size ◽  
Effective Diffusion Coefficient ◽  
Laboratory Experiments ◽  
Rock Sample ◽  
Effective Diffusion ◽  
X Ray ◽  
Rock Heterogeneity ◽  
Limestone Sample ◽  
Limestone Rock

Abstract. The aim of this study is to compare the structural, geometrical and transport parameters of a limestone rock sample determined by X-ray microtomography (XMT) images and laboratory experiments. Total and effective porosity, surface-to-volume ratio, pore size distribution, permeability, tortuosity and effective diffusion coefficient have been estimated. Sensitivity analyses of the segmentation parameters have been performed. The limestone rock sample studied here have been characterized using both approaches before and after a reactive percolation experiment. Strong dissolution process occured during the percolation, promoting a wormhole formation. This strong heterogeneity formed after the percolation step allows to apply our methodology to two different samples and enhance the use of experimental techniques or XMT images depending on the rock heterogeneity. We established that for most of the parameters calculated here, the values obtained by computing XMT images are in agreement with the classical laboratory measurements. We demonstrated that the computational porosity is more informative than the laboratory one. We observed that pore size distributions obtained by XMT images and laboratory experiments are slightly different but complementary. Regarding the effective diffusion coefficient, we concluded that both approaches are valuable and give similar results. Nevertheless, we wrapped up that computing XMT images to determine transport, geometrical and petrophysical parameters provides similar results than the one measured at the laboratory but with much shorter durations.

The Impact of Kerogen Structure on Shale Permeability: Coupled Molecular Diffusion and Geomechanical Behavior Study

2021 ◽  
Author(s):  
Clement Chekwube Afagwu ◽  
Saad Fahaid Al-Afnan ◽  
Mohamed Mahmoud
Keyword(s):  
Mechanical Properties ◽  
Natural Gas ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Effective Stress ◽  
Poisson Ratio ◽  
Effective Diffusion ◽  
Stress Changes ◽  
The Impact

Abstract The advancements in production technologies have unlocked tremendous reserves of natural gas in shale formations. The ability to describe shale matrix dynamics during the production span is, however, at infancy stages. The complex mineralogy and the multiscale nature of shales require transport models beyond the classical Darcian framework. Shales primarily consist of clays, quartz, calcite, and some fragments of organic matters known as kerogen. The latter can be envisioned as naturally occurring nanoporous media where diffusion is believed to be the predominant transport mechanism. Moreover, kerogen exhibits different geo-mechanical behavior than typical clastic sedimentary rocks. Hence, kerogen responds to changes in the stress field differently during the production span and ultimately influences the transport. It is our aim in this paper to delineate the transport and geo-mechanical aspects of kerogen through molecular-based assessments. Realistic kerogen structures at some ranges of density were recreated on a computational platform for thorough investigations. The structures were analyzed for porosity, pore size distribution, and mechanical properties such as bulk modulus, shear modulus, Young's modulus, and Poisson ratio. The adsorption alongside self-diffusion calculations were performed on the configurations. Moreover, the assessment of diffusivity was linked to pore compressibility to address the impact of effective stress changes on the transport throughout typical production span. An effective diffusion model for kerogen was proposed, validated with molecular simulation data in the literature, and compared with the MD diffusion data of this study. The results revealed critical dependency of pore size distribution, and porosity on the effective stress, which severely alters the diffusive permeability. This work provides a novel methodology for linking kerogen microscale intricacies to some fundamental transport and mechanical properties to better describe the transport of natural gas from kerogen.

scholarly journals Calculating structural and geometrical parameters by laboratory measurements and X-ray microtomography: a comparative study applied to a limestone sample before and after a dissolution experiment

Solid Earth ◽  
2016 ◽  
Vol 7 (2) ◽  
pp. 441-456 ◽  
Author(s):  
Linda Luquot ◽  
Vanessa Hebert ◽  
Olivier Rodriguez
Keyword(s):  
Diffusion Coefficient ◽  
Pore Size ◽  
Effective Diffusion Coefficient ◽  
Laboratory Experiments ◽  
Rock Sample ◽  
Effective Diffusion ◽  
Laboratory Measurements ◽  
X Ray ◽  
Before And After ◽  
Limestone Rock

Abstract. The aim of this study is to compare the structural, geometrical and transport parameters of a limestone rock sample determined by X-ray microtomography (XMT) images and laboratory experiments. Total and effective porosity, pore-size distribution, tortuosity, and effective diffusion coefficient have been estimated. Sensitivity analyses of the segmentation parameters have been performed. The limestone rock sample studied here has been characterized using both approaches before and after a reactive percolation experiment. Strong dissolution process occurred during the percolation, promoting a wormhole formation. This strong heterogeneity formed after the percolation step allows us to apply our methodology to two different samples and enhance the use of experimental techniques or XMT images depending on the rock heterogeneity. We established that for most of the parameters calculated here, the values obtained by computing XMT images are in agreement with the classical laboratory measurements. We demonstrated that the computational porosity is more informative than the laboratory measurement. We observed that pore-size distributions obtained by XMT images and laboratory experiments are slightly different but complementary. Regarding the effective diffusion coefficient, we concluded that both approaches are valuable and give similar results. Nevertheless, we concluded that computing XMT images to determine transport, geometrical, and petrophysical parameters provide similar results to those measured at the laboratory but with much shorter durations.

Diffusion Processes Affecting the Performance of Heterogeneous Catalysts: Part 1

2011 ◽  
Vol 319-320 ◽  
pp. 107-115
Author(s):  
Mohammad Ebrahim Zeynali ◽  
S. Hakim
Keyword(s):  
Diffusion Coefficient ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Heterogeneous Catalysts ◽  
Molecular Diffusion ◽  
Diffusion Processes ◽  
Knudsen Diffusion ◽  
Catalytic Systems ◽  
Heterogeneous Catalytic

The diffusion processes taking place in heterogeneous catalytic systems have been discussed. Various diffusion mechanisms such as Knudsen diffusion, molecular diffusion, configurational diffusion and surface diffusion sensitivity in catalytic systems were investigated. The concentration gradients inside the catalyst pellet were obtained for various Thiele modulus. The Knudsen number was calculated and discussed for large and small pores. The transitional diffusion coefficient was determined for diethylbenzene. The experimental pore size distribution carves for an industrial and synthesized catalyst was obtained and the effect of pore size distribution on diffusion coefficient was discussed.

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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