Modeling of Methanol Steam Reforming in a Monolith Reactor: Effects of Internal Diffusion, Substrate Parameters, and Operating Conditions

Methanol steam reforming is a promising method to achieve on-site hydrogen production for fuel cell applications. The characteristics of fluid flow, heat transfer, and mass transfer within advanced reactors still call for further investigation. A computational fluid dynamics simulation study of methanol steam reforming in a monolith reactor based on multiscale modeling is presented in this work. The washcoat model reveals that effectiveness factors decrease with increasing coating thickness and temperature, but H<sub>2</sub> production alleviates diffusion limitations, allowing such effects to be neglected in downstream regions. The reactor model shows that product selectivity is primarily governed by temperature, with higher temperatures promoting methanol decomposition and thereby increasing CO formation. Methanol conversion and H<sub>2</sub> yield are also strongly temperature-dependent, while the substrate of high thermal conductivity and larger length-to-diameter ratios improve thermal uniformity and performance. Additionally, methanol conversion declines with higher reactant flow rates, although higher flow rates enhance the absolute H<sub>2</sub> yield. Honeycomb substrates should be designed to possess high cell density and thin channel walls, which poses challenges for mechanical properties and manufacturing. In addition, under conditions of low flow velocity, diffusion phenomena at the reactor inlet require particular attention in numerical simulations.

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Publication Details

Journal
ACS Omega
Published
2026-03-03
DOI
https://doi.org/10.1021/acsomega.5c10513
Primary Topic
Catalysts for Methane Reforming
Type
article
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article

Modeling of Methanol Steam Reforming in a Monolith Reactor: Effects of Internal Diffusion, Substrate Parameters, and Operating Conditions

Yixing Li, Xianzhang Lei, Qi Zhang, Xiaoyuan Wang et al.
ACS Omega
Catalysts for Methane Reforming
article

Modeling of Methanol Steam Reforming in a Monolith Reactor: Effects of Internal Diffusion, Substrate Parameters, and Operating Conditions

Yixing Li, Xianzhang Lei, Qi Zhang, Xiaoyuan Wang, Ming Fang
article en

Abstract

Methanol steam reforming is a promising method to achieve on-site hydrogen production for fuel cell applications. The characteristics of fluid flow, heat transfer, and mass transfer within advanced reactors still call for further investigation. A computational fluid dynamics simulation study of methanol steam reforming in a monolith reactor based on multiscale modeling is presented in this work. The washcoat model reveals that effectiveness factors decrease with increasing coating thickness and temperature, but H<sub>2</sub> production alleviates diffusion limitations, allowing such effects to be neglected in downstream regions. The reactor model shows that product selectivity is primarily governed by temperature, with higher temperatures promoting methanol decomposition and thereby increasing CO formation. Methanol conversion and H<sub>2</sub> yield are also strongly temperature-dependent, while the substrate of high thermal conductivity and larger length-to-diameter ratios improve thermal uniformity and performance. Additionally, methanol conversion declines with higher reactant flow rates, although higher flow rates enhance the absolute H<sub>2</sub> yield. Honeycomb substrates should be designed to possess high cell density and thin channel walls, which poses challenges for mechanical properties and manufacturing. In addition, under conditions of low flow velocity, diffusion phenomena at the reactor inlet require particular attention in numerical simulations.

ACS OmegaVol. 11(10)
Nanjing Tech University (CN), Southwest Petroleum University (CN), National Institute of Clean and Low-Carbon Energy (CN)
Affordable and clean energy
Openalex Percentile: Top 36%
Catalysts for Methane Reforming
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Modeling of Methanol Steam Reforming in a Monolith Reactor: Effects of Internal Diffusion, Substrate Parameters, and Operating Conditions — Yixing Li, Xianzhang Lei, et al. · ACS Omega (2026) | TGRS Research Map | TGRS