Standardised Characterisation of Graphene Oxide to Aid Safety Assessment for Rapid Commercialisation

The rapid commercialisation of nanomaterials (NMs) with unique properties, that enable their utilisation in various fields of nanotechnology from energy to medicine, has prompted the European Union to recognise the indispensable need to develop standardised approaches for the characterisation of NMs to establish safe and sustainable utilisation. One example of such NMs is graphene oxide (GO). With its exceptionally thin morphology, enormous specific surface area, tuneable surface chemistry, and high dispersibility in aqueous media, GO has been pivotal in the rise and growth of several energy and medicinal nanotechnologies. Standardised approaches for the physico-chemical characterisation of commercially available GO with various properties are being developed within the framework of project POTENTIAL (Platform Optimisation To Enable NanomaTerIAL safety assessment for rapid commercialisation) [1]. Characterisation protocols of GO obtained from commercial partners are being produced to aid in the classification and 'grouping' of different types of GO based on their flake size, flake morphology, periodic crystallinity, defect density, defect nature, and surface functional groups. Thorough 'grouping' by POTENTIAL will help achieve the objective of drawing proof conclusions on the interactions of GO-derived NMs with animals, plants, water, soil, and air. To achieve that, various essential physico-chemical characterisations of different types of GO have been conducted, namely: SEM, XPS, (HR-)TEM, AFM, and Raman spectroscopy. Each characterization helps generate several descriptors. For instance, SEM analysis can help generate cumulative distribution parameters (D10, D50, and D90) to describe size and aspect ratio distributions; XPS analysis informs about atomic content and associated chemical states; (HR-)TEM analysis to probe fine structure and periodic crystallinity; AFM analysis helps generate cumulative distribution parameters for particle thickness; and Raman spectroscopy analysis can help estimate the defect density and defect nature of GO materials. The generated descriptors will be used to develop algorithms for similarity assessment that will ultimately enable grouping of NMs and read-across information for risk and Safe-and-Sustainable-by-Design assessment.