Integrated manufacturing of REciclable multi-material COmposites for the TRANSport sector
Ultrasonic Deposition of Carbon Nanotubes on Polycrystalline Cubic Boron Nitride Composites
Polycrystalline cubic boron nitride (PcBN) are super-hard materials with high hardness and excellent abrasive resistance, widely used in cutting tools for precision machining of automotive and aerospace parts; however, their brittle properties make them prone to premature failure. Coatings are often applied to PcBN to extend their range of applicability and durability. Conventional coating methods are limited to the thickness range of a few hundred nanometres, poor adhesion to the substrate, and limited stability under ambient conditions. To further the properties of PcBN composites, in this paper, we explore the use of ultrasonic bonding to apply thick coatings (30–80 μm) on PcBN cutting tools. For the first time, a multi-walled carbon nanotube (MWCNT) powder is preplaced on a PcBN substrate to allow an unconventional coating technique to take place. The effects of ultrasonic bonding parameters on the change of mechanical properties of the coated tools are investigated through scanning electron microscopy (SEM), energy dispersive X-Ray spectroscopy (EDX), micro-hardness analyses, and white light interferometry. The structure of the carbon nanotubes is investigated through transmission electron microscopy (pre coating) and cross-section of the bonded MWCNTs is studied via focused ion beam milling and SEM to evaluate the bonding between the multi-walled nanotubes. Optimum processing windows (i.e., bonding speed, energy, and pressure) are discovered for coating MWCNTs on PcBN. Focus ion beam milling analyses revealed a relationship between consolidation parameters and porosity of MW(pCNT) bonds. The proposed method paves the way for the novel design of functional coatings with attunable properties (i.e., thickness and hardness) and therefore improved productivity in the machining of aerospace and automotive parts.
» Author: Manuela Pacella
» Reference: doi: 10.3390/ma14030516
» Publication Date: 21/01/2021
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº 768737
