Abstract
Workers exposure to graphene was measured in a pilot production plant. Reduced graphene oxide was produced through graphite oxidation and posterior thermal reduction. The monitoring was performed using two handheld on-line devices covering the particle size range from 10 nm to 10 μm (CPC3007 and OPS3330). Simultaneously, personal and area filter samples were collected for off line analysis, including gravimetric, elemental carbon analysis and SEM/EDX. Significant releases of particles were identified in two tasks, during the graphene oxide washing, and during its milling. However, the analysis of the particles size distribution and of their morphology suggested that the released particles were not the target nanomaterial but engine generated nanoparticles. The mass of elemental carbon in the collected filters was below the quantification limit and the calculated graphene mass concentrations were quite below the selected reference exposure limit. Overall, this work showed that worker exposure to graphene was low in this pilot plant, contributing to guarantee a safe process, prior to its industrialization.
| Original language | English |
|---|---|
| Article number | 012005 |
| Pages (from-to) | 12005 |
| Number of pages | 1 |
| Journal | Journal of Physics: Conference Series |
| Volume | 1323 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 17 Oct 2019 |
| Event | 6th Nanosafe International Conference on Health and Safety Issues Related to Nanomaterials for a Socially Responsible Approach, NANOSAFE 2018 - Grenoble, France Duration: 5 Nov 2018 → 9 Nov 2018 |
Keywords
- Graphene
- Nanostructured materials
- Particle size
- Pilot plants
- Particle size analysis
Project and Funding Information
- Project ID
- info:eu-repo/grantAgreement/EC/H2020/685825/EU/Functionally graded Additive Manufacturing scaffolds by hybrid manufacturing/FAST
- Funding Info
- This research was carried out as part of the project FAST- Functionally Graded Additive Manufacturing Scaffolds by Hybrid Manufacturing. The project FAST has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 685825.