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 alternative materials
with a versatile number of applications that range from catalysis
to greenhouse gas capture. However, there are several factors that
constrain the direct scale-up of MOFs from laboratory to industrial
plant given the insufficient knowledge about the overall safety in
synthesis processes. This article focuses on the study of MOF thermal
stability, from concept to prediction, and the factors that influence
such stability. The core of this work is a thermal stability prediction
model for MOFs. This model can be applied to existing and new MOF
structures, and it will allow for an estimation of the thermal stability
temperature range of MOFs. This work contributes to the overall advancement
of MOF technology and the efforts for its commercial use at industrial
scale, combining both experimental data and computational techniques.