  The conversion of natural gas (methane) to ethane and ethylene (OCM:
oxidative coupling of methane) facilitates its transportation and provides a
way to synthesize higher value chemicals. The search for high-performance
catalysts to achieve this conversion is the main scope of most corresponding
studies in the field of OCM. Here, we present a general data-driven strategy
for the search of novel catalytic materials, focusing particularly on materials
useful for the OCM reaction. Our strategy is based on consistent experimental
measurements and includes ab initio thermodynamics calculations and active
screening. Based on our experiments, which showed unique volcano-type
dependence of the performance on the stability of formed carbonates attributed
to the site isolation concept, we developed a method for efficient and
inexpensive DFT calculations of the formation energies of carbonates with
prediction accuracy 0.2 eV. This method was implemented into a high-throughput
screening scheme, which includes both general requirements for catalyst
candidates and an actively done artificial intelligence part. Experimental
validation of some of the candidates obtained during the screening showed
successful reproduction of the initial volcano dependence. Moreover, several
new materials were found to outperform standard OCM catalysts, specifically at
lower temperatures.
