The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application

Abstract

The theoretical predictions of endpoints related to nanomaterials are attractive and moreefficient alternatives for their experimental determinations. Such type of calculations for the "usual"substances (i.e. non nanomaterials) can be carried out with molecular graphs. However, in the case ofnanomaterials, descriptors traditionally used for the quantitative structure - property/activityrelationships (QSPRs/QSARs) do not provide reliable results since the molecular structure ofnanomaterials, as a rule, cannot be expressed by the molecular graph. Innovative principles ofcomputational prediction of endpoints related to nanomaterials extracted from available eclectic data(technological attributes, conditions of the synthesis, etc.) are suggested, applied to two different sets of data, anddiscussed in this work.