The role that artificial intelligence can play in decarbonising the chemical industry is the subject of a new report by researchers at Tsinghua University.
Led by Professor Xiaonan Wang, the study, AI-enhanced multi-scale smart systems for decarbonisation in the chemical industry: a pathway to sustainable and efficient production, which was published in the Technology Review for Carbon Neutrality journal, highlights AI’s potential in ‘simplifying traditional mechanistic models, improving efficiency, and promoting resource conservation’.
Machine learning
At a microscopic level, machine learning aids in material design and performance prediction, have the potential to uncover complex chemical mechanisms, the researchers note, adding, however, that challenges exist related to data reliability.
‘At the mesoscale, AI-driven process modeling accelerates industrial applications of decarbonisation technologies, though scaling up digital integration remains a key hurdle,’ they state. ‘At the macro level, industrial symbiosis strategies optimise chemical parks by linking production with external markets and environmental factors, with digital twin technology enabling real-time operational adjustments.’
Hurdles to implementation
As such, the application of intelligent technologies such as AI in the chemical industry remains largely in the research phase for now, according to the study, with full-scale implementation facing a variety of technical, economic, social, and ethical hurdles, including concerns over data security, infrastructure compatibility, AI interpretability, workforce displacement, and regulatory compliance.
‘The study underscores the need for interdisciplinary collaboration and multi-stakeholder cooperation to address these challenges and accelerate the chemical industry’s transition to carbon neutrality,’ the researchers state. ‘By integrating AI and digital technologies across scales, the industry can advance toward a more efficient, sustainable, and low-carbon future.’
The research was supported by the National Key R&D Program of China, the Tsinghua University Initiative Scientific Research Program, and the National Natural Science Foundation of China. Read more here.
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