Optimisation of Mechanical Properties of Gradient Zr-C Coatings

One of the key components of the designing procedure of a structure of hard anti-wear coatings deposited via Physical Vapour Deposition (PVD) is the analysis of the stress and strain distributions in the substrate/coating systems, initiated during the deposition process and by external mechanical loads. Knowledge of residual stress development is crucial due to their significant influence on the mechanical and tribological properties of such layer systems. The main goal of the work is to find the optimal functionally graded material (FGM) coating's structure, composed of three functional layers: (1) adhesive layer, providing high adhesion of the coating to the substrate, (2) gradient load support and crack deflection layer, improving hardness and enhancing fracture toughness, (3) wear-resistant top layer, reducing wear. In the optimisation procedure of the coating's structure, seven decision criteria basing on the state of residual stresses and strains in the substrate/coating system were proposed. Using finite element simulations and postulated criteria, the thickness and composition gradients of the transition layer in FGM coating were determined. In order to verify the proposed optimisation procedure, Zr-C coatings with different spatial distribution of carbon concentration were produced by the Reactive Magnetron Sputtering PVD (RMS PVD) method and their anti-wear properties were assessed by scratch test and ball-on-disc tribological test.

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:14

Enthalten in:

Materials (Basel, Switzerland) - 14(2021), 2 vom: 08. Jan.

Sprache:

Englisch

Beteiligte Personen:

Szparaga, Łukasz [VerfasserIn]
Bartosik, Przemysław [VerfasserIn]
Gilewicz, Adam [VerfasserIn]
Mydłowska, Katarzyna [VerfasserIn]
Ratajski, Jerzy [VerfasserIn]

Links:

Volltext

Themen:

Anti-wear coatings
FEM modeling
Functionally graded materials
Gradient coatings
Journal Article
Optimisation

Anmerkungen:

Date Revised 25.01.2021

published: Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.3390/ma14020296

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM319935027