AI-Based Modelling and Processing Technologies for Hydrogen Creation

Abstract

This research aims to thoroughly analyse recent advancements in method demonstration and the implementation of Artificial Intelligence (AI) in integrated hydrogen production and carbon capture. The primary objective is to offer a detailed account of the anticipated role of AI in shaping future research endeavours related to blue hydrogen production and carbon capture. This involves a focus on Machine Learning (ML) applications in material development and process optimisation. The research provides an overview of AI and cycle demonstration in a relevant context, accompanied by a concise examination of recent developments in blue hydrogen production. The foundational instruments of AI modelling and processing are briefly outlined, and their application in blue hydrogen creation is discussed, considering both advantages and drawbacks. Ultimately, the research aims to deliver a comprehensive overview of the advancements in ML, emphasising its substantial contribution to accelerating blue hydrogen generation, particularly in the realms of material and process development. AI modelling and processing technologies are preferred for hydrogen creation due to their superior ability to optimise complex, data-intensive processes and accelerate material innovation, overcoming the limitations of traditional modelling methods.