Development of bimetallic catalysts for (sorption-enhanced) steam methane reforming

Date published

2023-12

Free to read from

Journal Title

Journal ISSN

Volume Title

Publisher

Cranfield University

Department

SWEE

Type

Thesis

ISSN

Format

Citation

Abstract

Hydrogen has gained increasing attention in recent years as one of the most promising solutions to decarbonize the energy sector, as it emits zero carbon when combusted. The demand for clean hydrogen continues to rise as government, industry, and academia endeavour to meet the net zero goal by the year 2050. Steam methane reforming is currently the predominant hydrogen production pathway and is predicted to remain so for the years to come. Many techniques exist for the optimization and decarbonization of the steam methane reforming process. Two of the most widely employed methods include using more efficient and stable catalysts and adding in an in-situ carbon capture step using solid CO₂ sorbents. The overall aim of this PhD study is to develop and evaluate the performance of novel bimetallic catalysts for the (sorption-enhanced) steam methane reforming process. Starting from a comprehensive literature review, recent advances in the field of bimetallic SMR catalysts were summarized and reviewed, based on their catalytic activity, stability, and physical-chemical properties. Based on the review, three bimetallic catalysts (Ni₃M ₁ /Al₂ O₃, M = Cu, Fe, and Ge) were synthesized, characterized using different techniques, and tested in a laboratory-scale fixed bed reactor under typical steam methane reforming conditions. CaO particles were then added to the system and the performance of the catalysts under sorption-enhanced steam methane reforming conditions was evaluated. A study on the influence of Cu loading on the bimetallic Ni-Cu catalysts was also carried out. The experimental studies were also accompanied by Density Functional Theory calculations of the carbon and oxygen adsorption energies on the bimetallic surfaces, and microkinetic modelling of the SMR reaction based on previous literature on its reaction mechanism. Finally, machine learning models were developed for the prediction of atomic adsorption energies using readily available elemental properties. Together with the previously developed microkinetic model, a fast high throughput screening of bimetallic alloys was carried out and catalysts with high sulphur resistance were successfully identified. Overall, the addition of Cu was found to be highly beneficial for promoting the catalytic activity of the conventional Ni catalysts, and the addition of Ge promotes the activity and can potentially improve the sulphur resistance of the catalysts. The wide application of these cost-effective and highly active bimetallic catalysts will contribute significantly to the decarbonisation of the energy sector by enabling the efficient production of hydrogen.

Description

Nabavi, Seyed Ali - Associate Supervisor

Software Description

Software Language

Github

Keywords

Hydrogen production, Density Functional Theory, Microkinetic Modelling, Machine Learning, Sulphur resistant catalysts, TECHNOLOGY::Chemical engineering::Chemical process and manufacturing engineering::Materials chemistry

DOI

Rights

© Cranfield University, 2023. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.

Relationships

Relationships

Supplements

Funder/s