In a major development, all KIM Model Pages now include citation information for the interatomic potentials archived in openkim.org. This effort is done in collaboration with the Allen Institute for AI through the Semantic Scholar project, which provides OpenKIM with the citation information and the full text, when available, that is used for machine learning processing.
The KIM Model page of a given potential displays the list of all articles that cite it together with a bar chart showing citations per year since the potential was published.
The articles can be sorted in different ways (by date, by number of citations, etc.) and can be searched based on the their titles, authors, reference, and abstracts.
A machine learning algorithm based on natural language processing (NLP) technology developed by the KIM Team is used to determine whether the article citing the potential actually used it in computation or simply provides it as a background reference. "Using articles" are marked by a green star.
IMPORTANT NOTE: Usage can only be determined for articles for which Semantic Scholar can provide OpenKIM with full text. Where this is not the case, the article is marked by an orange "?". Users who know whether an article did or did not use a potential are encouraged to let us know by clicking the cloud icon by the article and completing a one question form.
A word cloud is generated from the abstracts of the using articles to give a sense of the types of physical phenomena to which this interatomic potential is applied.
Check out the citation panels by going to the Model Page of any interatomic potential (click on an element on the periodic table on the openkim.org front page, and then click on any potential in the list).