Effect of the Agglomerate Geometry on the Effective Electrical Conductivity of a Porous Electrode
The study of the microstructure of random heterogeneous materials, related to an electrochemical device, is relevant because their effective macroscopic properties, e.g., electrical or proton conductivity, are a function of their effective transport coefficients (ETC). The magnitude of ETC depends o...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Membranes |
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| Online Access: | https://www.mdpi.com/2077-0375/11/5/357 |
| _version_ | 1797534160488759296 |
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| author | Abimael Rodriguez Roger Pool Jaime Ortegon Beatriz Escobar Romeli Barbosa |
| author_facet | Abimael Rodriguez Roger Pool Jaime Ortegon Beatriz Escobar Romeli Barbosa |
| author_sort | Abimael Rodriguez |
| collection | DOAJ |
| description | The study of the microstructure of random heterogeneous materials, related to an electrochemical device, is relevant because their effective macroscopic properties, e.g., electrical or proton conductivity, are a function of their effective transport coefficients (ETC). The magnitude of ETC depends on the distribution and properties of the material phase. In this work, an algorithm is developed to generate stochastic two-phase (binary) image configurations with multiple geometries and polydispersed particle sizes. The recognizable geometry in the images is represented by the white phase dispersed and characterized by statistical descriptors (two-point and line-path correlation functions). Percolation is obtained for the geometries by identifying an infinite cluster to guarantee the connection between the edges of the microstructures. Finally, the finite volume method is used to determine the ETC. Agglomerate phase results show that the geometry with the highest local current distribution is the triangular geometry. In the matrix phase, the most significant results are obtained by circular geometry, while the lowest is obtained by the 3-sided polygon. The proposed methodology allows to establish criteria based on percolation and surface fraction to assure effective electrical conduction according to their geometric distribution; results provide an insight for the microstructure development with high projection to be used to improve the electrode of a Membrane Electrode Assembly (MEA). |
| first_indexed | 2024-03-10T11:25:39Z |
| format | Article |
| id | doaj.art-3e72bd061188485f8db796df993ac46c |
| institution | Directory Open Access Journal |
| issn | 2077-0375 |
| language | English |
| last_indexed | 2024-03-10T11:25:39Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Membranes |
| spelling | doaj.art-3e72bd061188485f8db796df993ac46c2023-11-21T19:39:56ZengMDPI AGMembranes2077-03752021-05-0111535710.3390/membranes11050357Effect of the Agglomerate Geometry on the Effective Electrical Conductivity of a Porous ElectrodeAbimael Rodriguez0Roger Pool1Jaime Ortegon2Beatriz Escobar3Romeli Barbosa4División de Ciencias e Ingeniería, Universidad de Quintana Roo, Boulevard Bahía s/n, Chetumal 77019, Quintana Roo, MexicoDivisión de Ciencias e Ingeniería, Universidad de Quintana Roo, Boulevard Bahía s/n, Chetumal 77019, Quintana Roo, MexicoDivisión de Ciencias e Ingeniería, Universidad de Quintana Roo, Boulevard Bahía s/n, Chetumal 77019, Quintana Roo, MexicoUnidad de Energía Renovable, Centro de Investigación Científica de Yucatán, C 43 No 130, Chuburná de Hidalgo, Mérida 97200, Yucatán, MexicoDivisión de Ciencias e Ingeniería, Universidad de Quintana Roo, Boulevard Bahía s/n, Chetumal 77019, Quintana Roo, MexicoThe study of the microstructure of random heterogeneous materials, related to an electrochemical device, is relevant because their effective macroscopic properties, e.g., electrical or proton conductivity, are a function of their effective transport coefficients (ETC). The magnitude of ETC depends on the distribution and properties of the material phase. In this work, an algorithm is developed to generate stochastic two-phase (binary) image configurations with multiple geometries and polydispersed particle sizes. The recognizable geometry in the images is represented by the white phase dispersed and characterized by statistical descriptors (two-point and line-path correlation functions). Percolation is obtained for the geometries by identifying an infinite cluster to guarantee the connection between the edges of the microstructures. Finally, the finite volume method is used to determine the ETC. Agglomerate phase results show that the geometry with the highest local current distribution is the triangular geometry. In the matrix phase, the most significant results are obtained by circular geometry, while the lowest is obtained by the 3-sided polygon. The proposed methodology allows to establish criteria based on percolation and surface fraction to assure effective electrical conduction according to their geometric distribution; results provide an insight for the microstructure development with high projection to be used to improve the electrode of a Membrane Electrode Assembly (MEA).https://www.mdpi.com/2077-0375/11/5/357effective transport coefficientspercolationpolygonal synthetic imagesstatistical descriptors |
| spellingShingle | Abimael Rodriguez Roger Pool Jaime Ortegon Beatriz Escobar Romeli Barbosa Effect of the Agglomerate Geometry on the Effective Electrical Conductivity of a Porous Electrode Membranes effective transport coefficients percolation polygonal synthetic images statistical descriptors |
| title | Effect of the Agglomerate Geometry on the Effective Electrical Conductivity of a Porous Electrode |
| title_full | Effect of the Agglomerate Geometry on the Effective Electrical Conductivity of a Porous Electrode |
| title_fullStr | Effect of the Agglomerate Geometry on the Effective Electrical Conductivity of a Porous Electrode |
| title_full_unstemmed | Effect of the Agglomerate Geometry on the Effective Electrical Conductivity of a Porous Electrode |
| title_short | Effect of the Agglomerate Geometry on the Effective Electrical Conductivity of a Porous Electrode |
| title_sort | effect of the agglomerate geometry on the effective electrical conductivity of a porous electrode |
| topic | effective transport coefficients percolation polygonal synthetic images statistical descriptors |
| url | https://www.mdpi.com/2077-0375/11/5/357 |
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