Nanoparticles are increasingly used and a vast number of nanotechnological products including consumer products, are entering the market. To determine whether a product contains a nanomaterial, particle size and number concentration need to be measured. The EU project ACEnano innovates and optimises analytical techniques to detect and characterise nanoparticles. Proficiency testing is an integral part of the ACEnano project and the development of a proficiency testing scheme for nanomaterial analysis to assure comparable performance of laboratories is foreseen.
The ACEnano Knowledge Warehouse (KW) supports the activities related to data collection and mehod optimisation in ACEnano and aims to furhter disseminate this knowledge to the nanosafety community in a re-usable format. The KW includes multiple instances (protocols, data and dissemination) to optimally accommodate the requirements of the different data types (e.g. raw, processed data and protocols).
The H2020 project ACEnano aims to introduce confidence, adaptability and clarity into nanomaterial risk assessment, by developing a widely implementable and robust tiered approach to nanomaterials physicochemical characterisation that will simplify and facilitate contextual (hazard or exposure) description and its transcription into a reliable nanomaterials grouping framework.
ACEnano will introduce its plan for external training events during the NanoSAFE 2018 conference in Grenoble, France, from 9 am on 6th November (Chrome1 meeting room).
Following on from the first two biennial meetings, which took place in Sicily and Sweden, the 3rd NanoSafety Forum for Young Scientists took place in Valletta, Malta, on 10th-11th September 2018, under the aegis of the EU NanoSafety Cluster and ACEnano project.
The e-infrastructure project OpenRiskNet developing a platform providing data and modelling tools for predictive toxicology and risk assessment and coordinated by DouglasConnect, is entering its second stage, in which the platform is made accessible to everyone. In the first phase, advanced concepts have been developed and implemented into the first version of the platform including building and deploying of virtual research environments (VREs), a reference environment accessible by everyone for testing, harmonized and partly semantically annotated data and modelling services, corresponding training material as well as seven risk assessment case studies, which are used to evaluate and optimize the infrastructure.
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