Artificial Intelligence (AI) has revolutionized various industries and reaction engineering is no exception. As the demand for efficient and sustainable processes grows, researchers and engineers are turning to smart approaches enabled by AI to optimize reaction engineering processes. This synergy between AI and reaction engineering holds the promise of enhancing efficiency, reducing costs and minimizing environmental impact. AI, particularly machine learning (ML) and neural networks, has brought about a paradigm shift in process modeling. These advanced algorithms excel at recognizing patterns and relationships within large and intricate data sets. In the context of reaction engineering, AI-driven models can learn from experimental data to create more accurate and predictive representations of chemical processes.
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