Simulation of a thermoelectric gas sensor that determines hydrocarbon concentrations in exhausts and the light-off temperature of catalyst materials

Abstract. Catalyst materials can be characterized with a thermoelectric gas sensor. Screen-printed thermopiles measure the temperature difference between an inert part of the planar sensor and a part that is coated with the catalyst material to be analyzed. If the overall sensor temperature is modulated, the catalytic activity of the material can be varied. Exothermic reactions that occur at the catalyst layer cause a temperature increase that can then be measured as a sensor voltage due to the Seebeck coefficient of the thermopiles. This mechanism can also be employed at stationary conditions at constant sensor temperature to measure gas concentrations. Then, the sensor signal changes linearly with the analyte concentration. Many variables influence the sensing performance, for example, the offset voltage due to asymmetric inflow and the resulting inhomogeneous temperature distributions are an issue. For even better understanding of the whole sensing principle, it is simulated in this study by a 3-D finite element model. By coupling all influencing physical effects (fluid flow, gas diffusion, heat transfer, chemical reactions, and electrical properties) a model was set up that is able to mirror the sensor behavior precisely, as the comparison with experimental data shows. A challenging task was to mesh the geometry due to scaling problems regarding the resolution of the thin catalyst layer in the much larger gas tube. Therefore, a coupling of a 3-D and a 1-D geometry is shown. This enables to calculate the overall temperature distribution, fluid flow, and gas concentration distribution in the 3-D model, while a very accurate calculation of the chemical reactions is possible in a 1-D dimension. This work does not only give insight into the results at stationary conditions for varying feed gas concentrations and used substrate materials but shows also how various exhaust gas species behave under transient temperature modulation.

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Numerical Investigation of Fluid Flow Inside the Porous Medium of GDL

ASME 2010 8th International Conference on Nanochannels, Microchannels, and Minichannels: Parts A and B ◽

10.1115/fedsm-icnmm2010-30594 ◽

2010 ◽

Author(s):

Mehdi Shahraeeni ◽

Mina Hoorfar

Keyword(s):

Porous Medium ◽

Fluid Flow ◽

Fuel Cell ◽

Transient Flow ◽

Catalyst Layer ◽

Pem Fuel Cell ◽

Gas Diffusion ◽

Pore Network Model ◽

Temporal Response ◽

Hydrophobic Agent

A pore-network model is developed to study numerically the transient flow of fluid through the gas diffusion layer (GDL) of the PEM fuel cell. It is shown that the agglomeration of water droplet on the interface of the GDL and catalyst layer occurs faster for the samples with smaller pore diameters and lower contents of the hydrophobic agent. The study suggests that analysis of the temporal response of the GDL is a useful tool to evaluate its performance against transporting liquids.

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Numerical study of the flow of a mixture of reacting gases in an inhomogeneous catalyst layer

Proceedings of the Mavlyutov Institute of Mechanics ◽

10.21662/uim2003.1.018 ◽

2003 ◽

Vol 3 ◽

pp. 246-254

Author(s):

C.I. Mikhaylenko ◽

S.F. Urmancheev

Keyword(s):

Velocity Field ◽

Chemical Reactions ◽

Porous Layer ◽

Computational Experiment ◽

Numerical Study ◽

Fluid Velocity ◽

Catalyst Layer ◽

Granular Catalyst ◽

Fluid Velocity Field

The behavior of a liquid flowing through a fixed bulk porous layer of a granular catalyst is considered. The effects of the nonuniformity of the fluid velocity field, which arise when the surface of the layer is curved, and the effect of the resulting inhomogeneity on the speed and nature of the course of chemical reactions are investigated by the methods of a computational experiment.

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Influence of Catalyst Layer and Gas Diffusion Layer Porosity in Proton Exchange Membrane Fuel Cell Performance

Electrochimica Acta ◽

10.1016/j.electacta.2021.138793 ◽

2021 ◽

pp. 138793

Author(s):

Prince Abraham B ◽

Kalidasa Murugavel K

Keyword(s):

Fuel Cell ◽

Diffusion Layer ◽

Proton Exchange Membrane ◽

Catalyst Layer ◽

Gas Diffusion Layer ◽

Gas Diffusion ◽

Proton Exchange ◽

Cell Performance ◽

Fuel Cell Performance ◽

Exchange Membrane

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Modelling of the deformation-dependent fluid flow in the fibrous gas diffusion layer of fuel cells

PAMM ◽

10.1002/pamm.201710219 ◽

2017 ◽

Vol 17 (1) ◽

pp. 499-500

Author(s):

Mohamad Chaaban ◽

Yousef Heider ◽

Bernd Markert

Keyword(s):

Fluid Flow ◽

Fuel Cells ◽

Diffusion Layer ◽

Gas Diffusion Layer ◽

Gas Diffusion

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Novel Method of Temperature Modulation for Enhancing Catalytic Gas Sensor Selectivity

10.1109/sas51076.2021.9530079 ◽

2021 ◽

Author(s):

Denis Spirjakin ◽

Alexander Baranov ◽

Saba Akbari ◽

C.T. Phong ◽

N.N. Tuan

Keyword(s):

Gas Sensor ◽

Temperature Modulation ◽

Novel Method

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Electrical, Diffusional, and Hydraulic Tortuosity Anisotropy Quantification Using 3D CT-Scan Image Data

10.2118/206109-ms ◽

2021 ◽

Author(s):

Andres Gonzalez ◽

Zoya Heidari ◽

Olivier Lopez

Keyword(s):

Porous Media ◽

Fluid Flow ◽

Ct Scan ◽

Numerical Simulations ◽

Potential Distribution ◽

Image Data ◽

Gas Diffusion ◽

Depth Interval ◽

Micro Ct ◽

Multi Scale

Abstract Depositional mechanisms of sediments and post-depositional process often cause spatial variation and heterogeneity in rock fabric, which can impact the directional dependency of petrophysical, electrical, and mechanical properties. Quantification of the directional dependency of the aforementioned properties is fundamental for the appropriate characterization of hydrocarbon-bearing reservoirs. Anisotropy quantification can be accomplished through numerical simulations of physical phenomena such as fluid flow, gas diffusion, and electric current conduction in porous media using multi-scale image data. Typically, the outcome of these simulations is a transport property (e.g., permeability). However, it is also possible to quantify the tortuosity of the media used as simulation domain, which is a fundamental descriptor of the microstructure of the rock. The objectives of this paper are (a) to quantify tortuosity anisotropy of porous media using multi-scale image data (i.e., whole-core CT-scan and micro-CT-scan image stacks) through simulation of electrical potential distribution, diffusion, and fluid flow, and (b) to compare electrical, diffusional, and hydraulic tortuosity. First, we pre-process the images (i.e., CT-scan images) to remove non-rock material visual elements (e.g., core barrel). Then, we perform image analysis to identify different phases in the raw images. Then, we proceed with the numerical simulations of electric potential distribution. The simulation results are utilized as inputs for a streamline algorithm and subsequent direction-dependent electrical tortuosity estimation. Next, we conduct numerical simulation of diffusion using a random walk algorithm. The distance covered by each walker in each cartesian direction is used to compute the direction-dependent diffusional tortuosity. Finally, we conduct fluid-flow simulations to obtain the velocity distribution and compute the direction-dependent hydraulic tortuosity. The simulations are conducted in the most continuous phase of the segmented whole-core CT-scan image stacks and in the segmented pore-space of the micro-CT-scan image stacks. Finally, the direction-dependent tortuosity values obtained with each technique are employed to assess the anisotropy of the evaluated samples. We tested the introduced workflow on dual energy whole-core CT-scan images and on smaller scale micro-CT-scan images. The whole-core CT-scan images were obtained from a siliciclastic depth interval, composed mainly by spiculites. Micro-CT-scan images we obtained from Berea Sandstone and Austin Chalk formations. We observed numerical differences in the estimates of direction-dependent electrical, diffusional, and hydraulic tortuosity for both types of image data employed. The highest numerical differences were observed when comparing electrical and hydraulic tortuosity with diffusional tortuosity. The observed differences were significant specially in anisotropic samples. The documented comparison provides useful insight in the selection process of techniques for estimation of tortuosity. The use of core-scale image data in the proposed workflow provides semi-continuous estimates of tortuosity and tortuosity anisotropy which is typically not attainable when using pore-scale images. Additionally, the semi-continuous nature of the tortuosity and tortuosity anisotropy estimates in whole-core CT-scan image data provides an excellent tool for the selection of core plugs coring locations.

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Predicting Liquid Water Saturation Through Differently Structured Cathode Gas Diffusion Media of a Proton Exchange Membrane Fuel Cell

Journal of Fuel Cell Science and Technology ◽

10.1115/1.4005617 ◽

2012 ◽

Vol 9 (2) ◽

Cited By ~ 2

Author(s):

N. Akhtar ◽

P. J. A. M. Kerkhof

Keyword(s):

Fuel Cell ◽

Liquid Water ◽

Proton Exchange Membrane ◽

Water Saturation ◽

Catalyst Layer ◽

Gas Diffusion ◽

Proton Exchange ◽

Diffusion Media ◽

Exchange Membrane

The role of gas diffusion media with differently structured properties have been examined with emphasis on the liquid water saturation within the cathode of a proton exchange membrane fuel cell (PEMFC). The cathode electrode consists of a gas diffusion layer (GDL), a micro-porous layer and a catalyst layer (CL). The liquid water saturation profiles have been calculated for varying structural and physical properties, i.e., porosity, permeability, thickness and contact angle for each of these layers. It has been observed that each layer has its own role in determining the liquid water saturation within the CL. Among all the layers, the GDL is the most influential layer that governs the transport phenomena within the PEMFC cathode. Besides, the thickness of the CL also affects the liquid water saturation and it should be carefully controlled.

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