Ali Emre Taşlı

Mr. Ali Emre Taşlı


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 November 2023 in Microplastics
Verified
Journal Article
Open access
PDF file
KGKalouda Grigoriadi
Kalouda Grigoriadi
MNMerel G. A. Nooijens
Merel G. A. Nooijens
ATAli Emre Taşlı
Ali Emre Taşlı
MVMax Marc Claire Vanhouttem
Max Marc Claire Vanhouttem
SHSieger Henke
Sieger Henke
ABArjen Boersma
Arjen Boersma
The Microplastic Index (MPI) was presented in a previous paper as a method to assess the formation of microplastics during the application of impact and wear stresses, based on selected mechanical and physical properties of polymers. In this paper, the experimental validation of the MPI model is presented. A series of ten polymers was characterized to obtain the relevant parameters for the calculation of the MPI, i.e., the minimum particle size and volume of microplastics formed. The milling (addressing impact stress) and sanding experiments (addressing wear stress) resulted in particle sizes between 3 and 200 μm and 0.3 and 25 μm, respectively. These values were very well predicted by the MPI model, showing smaller particles for brittle polymers and larger ones for ductile polymers. In addition, the experimental-specific wear rates of impact and wear correlated well with the predicted ones, being 0.01–30 mm3/Nm for impact and 0.0002–0.012 mm3/Nm for wear. These results indicate that the MPI can be very well used to predict the tendency of a material to form microplastics. In the search for understanding and mitigating microplastic formation, the MPI can be used by both producers and end users to choose plastic grades that form fewer microplastics.