Text Mining Metal–Organic Framework Papers

We have developed
a simple text mining algorithm that allows us
to identify surface area and pore volumes of metal–organic
frameworks (MOFs) using manuscript html files as inputs. The algorithm
searches for common units (e.g., m2/g, cm3/g)
associated with these two quantities to facilitate the search. From
the sample set data of over 200 MOFs, the algorithm managed to identify
90% and 88.8% of the correct surface area and pore volume values.
Further application to a test set of randomly chosen MOF html files
yielded 73.2% and 85.1% accuracies for the two respective quantities.
Most of the errors stem from unorthodox sentence structures that made
it difficult to identify the correct data as well as bolded notations
of MOFs (e.g., 1a) that made it difficult identify its
real name. These types of tools will become useful when it comes to
discovering structure–property relationships among MOFs as
well as collecting a large set of data for references.