Department of Bioinformatics—BiGCaT, School of Nutrition and Translational Research in Metabolism, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
Blair D. Johnston
Department Chemicals and Product Safety, Federal Institute for Risk Assessment, Max-Dohrn-Str. 8-10, 10589 Berlin, Germany
Mary Gulumian
National Health Laboratory Services, 1 Modderfontein Rd, Sandringham, Johannesburg 2192, South Africa
Marianne Matzke
UK Centre for Ecology and Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford OX10 8BB, UK
Amaia Green Etxabe
UK Centre for Ecology and Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford OX10 8BB, UK
Nathan Bossa
LEITAT Technological Center, Circular Economy Business Unit, C/de La Innovació 2, 08225 Terrassa, Barcelona, Spain
Angela Serra
Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland
Irene Liampa
School of Chemical Engineering, National Technical University of Athens, 157 80 Athens, Greece
Stacey Harper
School of Chemical, Biological, and Environmental Engineering, Oregon State University, 116 Johnson Hall 105 SW 26th St., Corvallis, OR 97331, USA
Kaido Tämm
Institute of Chemistry, University of Tartu, Ülikooli 18, 50090 Tartu, Estonia
Alexander CØ Jensen
The National Research Center for the Work Environment, Lersø Parkallé 105, 2100 Copenhagen, Denmark
Pekka Kohonen
Misvik Biology OY, Karjakatu 35 B, 20520 Turku, Finland
Luke Slater
Institute of Cancer and Genomics, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
Chemoinformatics has developed efficient ways of representing chemical structures for small molecules as simple text strings, simplified molecular-input line-entry system (SMILES) and the IUPAC International Chemical Identifier (InChI), which are machine-readable. In particular, InChIs have been extended to encode formalized representations of mixtures and reactions, and work is ongoing to represent polymers and other macromolecules in this way. The next frontier is encoding the multi-component structures of nanomaterials (NMs) in a machine-readable format to enable linking of datasets for nanoinformatics and regulatory applications. A workshop organized by the H2020 research infrastructure NanoCommons and the nanoinformatics project NanoSolveIT analyzed issues involved in developing an InChI for NMs (NInChI). The layers needed to capture NM structures include but are not limited to: core composition (possibly multi-layered); surface topography; surface coatings or functionalization; doping with other chemicals; and representation of impurities. NM distributions (size, shape, composition, surface properties, etc.), types of chemical linkages connecting surface functionalization and coating molecules to the core, and various crystallographic forms exhibited by NMs also need to be considered. Six case studies were conducted to elucidate requirements for unambiguous description of NMs. The suggested NInChI layers are intended to stimulate further analysis that will lead to the first version of a “nano” extension to the InChI standard.