QUANTum mechAnicS for prediction and arTificial Intelligence for early thermal runaway deteCtion and mitigation

Thermal runaway remains a significant safety risk in the chemical industry, accounting for nearly 25% of accidents. The QUANTASTIC project aims to develop multifactorial kinetic models essential for identifying risks and optimizing chemical processes. It also seeks to innovate early detection by combining temperature signals with indicators such as pressure, utilizing artificial intelligence (AI) for enhanced monitoring. Additionally, the project will focus on optimizing exothermic processes through surrogate models and laboratory tests, incorporating agents to control thermal runaway. Biomass valorization processes are prone to thermal runaway, similar to petroleum-based processes. Among these, furfural—a key molecule in biorefineries—presents significant risks due to the exothermic nature of its hydrogenation and oxidation reactions. By concentrating on furfural valorization, QUANTASTIC will address high-risk reactions that produce valuable chemicals like maleic acid and 2-methyl THF. Traditional thermal risk assessments often rely on overly simplified models that ignore critical factors, including pressure evolution and secondary reactions. QUANTASTIC will develop kinetic models that account for these complexities, providing a more accurate representation of thermal behavior. The project will leverage Density Functional Theory to study thermal stability and decomposition pathways under various conditions. While several criteria exist for assessing thermal runaway risks, they often lack robustness. Therefore, QUANTASTIC aims to enhance detection and diagnosis through AI and machine learning, allowing for more effective safety measures. The project will also explore innovative mitigation strategies, such as using phase change materials (PCMs) to absorb excess heat. In summary, QUANTASTIC will develop methods to detect and mitigate thermal runaway risks in biomass valorization processes, advancing safety and contributing to more sustainable chemical processes.