Thermal Stability of Metal-Organic Frameworks (MOFs): Concept, Determination, and Model Prediction Using Computational Chemistry and Machine Learning

The indubitable rise of metal-organic framework (MOF)technology has opened the potential for commercialization as alternativematerials with a versatile number of applications that range from catalysis togreenhouse gas capture. However, there are several factors that constrain thedirect scale-up of MOFs from laboratory to industrial plant given theinsufficient knowledge about the overall safety in synthesis processes. Thisarticle focuses on the study of MOF thermal stability, from concept toprediction, and the factors that influence such stability. The core of this workis a thermal stability prediction model for MOFs. This model can be appliedto existing and new MOF structures, and it will allow for an estimation of thethermal stability temperature range of MOFs. This work contributes to theoverall advancement of MOF technology and the efforts for its commercialuse at industrial scale, combining both experimental data and computationaltechniques