The physicochemical characterisation data from a library of 69 engineered nanomaterials (ENMs) has been exploited in silico following enrichment with a set of molecular descriptors that can be easily acquired or calculated using atomic periodicity and other fundamental atomic parameters. Based on the extended set of twenty descriptors, a robust and validated nanoinformatics model has been proposed to predict the ENM ζ-potential. The five critical parameters selected as the most significant for the model development included the ENM size and coating as well as three molecular descriptors, metal ionic radius (rion), the sum of metal electronegativity divided by the number of oxygen atoms present in a particular metal oxide (Σχ/nO) and the absolute electronegativity (χabs), each of which is thoroughly discussed to interpret their influence on ζ-potential values. The model was developed using the Isalos Analytics Platform and is available to the community as a web service through the Horizon 2020 (H2020) NanoCommons Transnational Access services and the H2020 NanoSoveIT Integrated Approach to Testing and Assessment (IATA).
Bibliographical noteFunding Information:
This work was funded by the POST-DOC/0718/0070 project, co-funded by the European Regional Development Fund and the Republic of Cyprus through the Research and Innovation Foundation , the EU H2020 project NanoSolveIT (Grant Agreement No. 814572 ) and the EU H2020 research infrastructure project NanoCommons (grant agreement no. 731032 ).
© 2021 The Author(s)
- Engineered nanomaterials
- Isalos Analytics Platform
- Molecular descriptors
- Read across
- Zeta potential
ASJC Scopus subject areas
- Materials Science (miscellaneous)
- Safety, Risk, Reliability and Quality
- Safety Research
- Public Health, Environmental and Occupational Health