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Enhancing the Prediction Capability of a Literature COx Methanation Kinetic Model Научная публикация

Журнал Fuel
ISSN: 0016-2361 , E-ISSN: 1873-7153
Вых. Данные Год: 2026, Том: 410, Номер статьи : 137834, Страниц : 11 DOI: 10.1016/j.fuel.2025.137834
Ключевые слова COx methanation; Kinetic modeling; Reactor simulation; Power-to-Gas
Авторы Ríos Juan J. 1 , Ancheyta Jorge 2,3 , Mantilla Angeles 1 , Elyshev Andrey 3 , Zagoruiko Andrey 4
Организации
1 Instituto Politecnico Nacional, Centro de Investigacion en Ciencia Aplicada y Tecnología Avanzada, Unidad Legaria. Legaria 694, Col. Irrigacion, 11500 Ciudad de Mexico, Mexico
2 ESIQIE, Instituto Politecnico Nacional, UPALM, Zacatenco, Mexico City 07738, Mexico
3 Tyumen State University, 625003 Tyumen, Russia
4 Boreskov Institute of Catalysis, Siberian Branch, Russian Academy of Sciences, 630090 Novosibirsk Russia

Информация о финансировании (2)

1 Министерство науки и высшего образования Российской Федерации (с 15 мая 2018) FEWZ-2024-0015
2 Ministry of Science and Innovation

Реферат: A kinetic model for COx methanation based on the reactions of methanation of CO and CO2, and reverse water–gas shift is compared with a literature kinetic model that only considers the methanation of CO and reverse water–gas shift. The model is assessed under non-isothermal plug flow reactor conditions. To validate the predictive capability, temperature profiles, species molar fractions, and methane production were simulated and compared with experimental data. The proposed model includes mechanistic expressions accounting for competitive adsorption and product inhibition effects, which significantly improve its accuracy in capturing the system thermal and reactive behavior. Statistical validation through residual analysis and parity plot, along with regression metrics, confirms the superior performance of the proposed model. Notably, the inclusion of the CO2 methanation pathway led to a 15% increase in CH4 yield which adjusted better to the experimental data, emphasizing its importance in reactor modeling for COx hydrogenation. These results underscore the relevance of complete kinetic formulations in supporting process design, optimization, and scale-up in Power-to-Gas and synthetic natural gas production.
Библиографическая ссылка: Ríos J.J. , Ancheyta J. , Mantilla A. , Elyshev A. , Zagoruiko A.
Enhancing the Prediction Capability of a Literature COx Methanation Kinetic Model
Fuel. 2026. V.410. 137834 :1-11. DOI: 10.1016/j.fuel.2025.137834
Даты:
Поступила в редакцию: 12 авг. 2025 г.
Принята к публикации: 1 дек. 2025 г.
Идентификаторы БД: Нет идентификаторов
Цитирование в БД: Пока нет цитирований
Альметрики: