  Nowadays there are algorithms, methods, and platforms that are being created
to accelerate the discovery of materials that are able to absorb or adsorb
$CO_2$ molecules that are in the atmosphere or during the combustion in power
plants, for instance. In this work an asynchronous REST API is described to
accelerate the creation of Carbon figures of merit knowledge, called Carbon
Tables, because the knowledge is created from tables in scientific PDF
documents and stored in knowledge graphs. The figures of merit knowledge
creation solution uses a hybrid approach, in which heuristics and machine
learning are part of. As a result, one can search the knowledge with mature and
sophisticated cognitive tools, and create more with regards to Carbon figures
of merit.
