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., <b>1a</b>) 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