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Sorption-enhanced Steam Methane Reforming for Combined CO2 Capture and Hydrogen Production: A State-of-the-Art Review

Abstract

The European Commission have just stated that hydrogen would play a major role in the economic recovery of post-COVID-19 EU countries. Hydrogen is recognised as one of the key players in a fossil fuel-free world in decades to come. However, commercially practiced pathways to hydrogen production todays, are associated with a considerable amount of carbon emissions. The Paris Climate Change Agreement has set out plans for an international commitment to reduce carbon emissions within the forthcoming decades. A sustainable hydrogen future would only be achievable if hydrogen production is “designed” to capture such emissions. Today, nearly 98% of global hydrogen production relies on the utilisation of fossil fuels. Among these, steam methane reforming (SMR) boasts the biggest share of nearly 3 50% of the global generation. SMR processes correspond to a significant amount of carbon emissions at various points throughout the process. Despite the dark side of the SMR processes, they are projected to play a major role in hydrogen production by the first half of this century. This that a sustainable, yet clean short/medium-term hydrogen production is only possible by devising a plan to efficiently capture this co-produced carbon as stated in the latest International Energy Agency (IEA) reports. Here, we have carried out an in-depth technical review of the processes employed in sorption-enhanced steam methane reforming (SE-SMR), an emerging technology in low-carbon SMR, for combined carbon capture and hydrogen production. This paper aims to provide an in-depth review on two key challenging elements of SE-SMR i.e. the advancements in catalysts/adsorbents preparation, and current approaches in process synthesis and optimisation including the employment of artificial intelligence in SE-SMR processes. To the best of the authors‟ knowledge, there is a clear gap in the literature where the above areas have been scrutinised in a systematic and coherent fashion. The gap is even more pronounced in the application of AI in SE-SMR technologies. As a result, this work aims to fill this gap within the scientific literature.

Funding source: This work has been funded by the UK Engineering and Physical Sci- ences Research Council (EPSRC) under the project titled “Multiphysics and multiscale modelling for safe and feasible CO2 capture and storage - EP/T033940/1”. The authors would like to acknowledge EPSRC and UK Research and Innovation (UKRI) for their financial support throughout this project
Related subjects: Production & Supply Chain
Countries: Kuwait ; United Kingdom
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2021-10-02
2022-10-01
http://instance.metastore.ingenta.com/content/journal2504
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