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Open AccessArticle

NanoDefiner e-Tool: An Implemented Decision Support Framework for Nanomaterial Identification

Department of Computer Science, University of Applied Sciences and Arts Dortmund (FH Dortmund), 44227 Dortmund, Germany
Material Physics Research, BASF SE, 67056 Ludwigshafen, Germany
Institute of Process Engineering and Environmental Technology, Technische Universität Dresden (TU Dresden), 01062 Dresden, Germany
R&I Centre Brussels, Solvay S.A., 1120 Brussels, Belgium
DG JRC, European Commission, 21027 Ispra, Italy
Division 6.1 Surface Analysis and Interfacial Chemistry, Bundesanstalt für Materialforschung und -prüfung (BAM), 12205 Berlin, Germany
Institute of Food Safety, RIKILT Wageningen UR, 6708 WB Wageningen, The Netherlands
Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital Essen, 45122 Essen, Germany
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Current address: Université de Lyon, Université Claude Bernard Lyon 1, MATEIS CNRS UMR 5510, Faculté de Pharmacie—ISPB, 69373 Lyon, France.
Current address: Federal Institute for Risk Assessment, International Affairs, 10589 Berlin, Germany.
Materials 2019, 12(19), 3247;
Received: 3 September 2019 / Revised: 25 September 2019 / Accepted: 26 September 2019 / Published: 4 October 2019
(This article belongs to the Special Issue Nanomaterial Characterization Methods: Leaping Towards Validation)
The European Commission’s recommendation on the definition of nanomaterial (2011/696/EU) established an applicable standard for material categorization. However, manufacturers face regulatory challenges during registration of their products. Reliable categorization is difficult and requires considerable expertise in existing measurement techniques (MTs). Additionally, organizational complexity is increased as different authorities’ registration processes require distinct reporting. The NanoDefine project tackled these obstacles by providing the NanoDefiner e-tool: A decision support expert system for nanomaterial identification in a regulatory context. It provides MT recommendations for categorization of specific materials using a tiered approach (screening/confirmatory), and was constructed with experts from academia and industry to be extensible, interoperable, and adaptable for forthcoming revisions of the nanomaterial definition. An implemented MT-driven material categorization scheme allows detailed description. Its guided workflow is suitable for a variety of user groups. Direct feedback and explanation enable transparent decisions. Expert knowledge is held in a knowledge base for representation of MT performance criteria and physicochemical particle type properties. Continuous revision ensured data quality and validity. Recommendations were validated by independent case studies on industry-relevant particulate materials. Besides supporting material identification and registration, the free and open-source e-tool may serve as template for other expert systems within the nanoscience domain. View Full-Text
Keywords: nanotechnology; nanomaterial; particulate material; particle measurement; decision support; expert system; EC nanomaterial definition nanotechnology; nanomaterial; particulate material; particle measurement; decision support; expert system; EC nanomaterial definition
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MDPI and ACS Style

Brüngel, R.; Rückert, J.; Wohlleben, W.; Babick, F.; Ghanem, A.; Gaillard, C.; Mech, A.; Rauscher, H.; Hodoroaba, V.-D.; Weigel, S.; Friedrich, C.M. NanoDefiner e-Tool: An Implemented Decision Support Framework for Nanomaterial Identification. Materials 2019, 12, 3247.

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