Evaluation of chemical and physical properties of nanomaterials is of critical importance in a broad variety of
nanotechnology researches. There is an increasing interest in computational methods capable of predicting properties of
new and modified nanomaterials in the absence of time-consuming and costly experimental studies. Quantitative Structure-
Property Relationship (QSPR) approaches are progressive tools in modelling and prediction of many physicochemical
properties of nanomaterials, which are also known as nano-QSPR. This review provides insight into the concepts,
challenges and applications of QSPR modelling of carbon-based nanomaterials. First, we try to provide a general overview
of QSPR implications, by focusing on the difficulties and limitations on each step of the QSPR modelling of nanomaterials.
Then follows with the most significant achievements of QSPR methods in modelling of carbon-based nanomaterials
properties and their recent applications to generate predictive models. This review specifically addresses the QSPR
modelling of physicochemical properties of carbon-based nanomaterials including fullerenes, single-walled carbon nanotube
(SWNT), multi-walled carbon nanotube (MWNT) and graphene.
Keywords: Nano-QSPR, Physiochemical properties, Fullerenes, SWNTs, MWNTs, Graphene.
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