Scratch-induced damage of doped DLC and MoS ₂ coatings—Deep symbolic analysis

Understanding contact-induced damage is of paramount importance in the analysis of the lifespan and performance of surface coatings. In this work, we investigate the effects of dopants and interlayers on the structural durability of diamond-like carbon coatings (DLCs) and molybdenum disulfide (MoS₂) coatings on stainless steel via micro-scratch tests. The analysis of XPS survey spectra and Raman spectra of DLCs shows that the ratio of sp²/sp³ (i.e., the intensity ratio of sp² over sp³ obtained by XPS) is proportional to <em>I</em>_D/<em>I</em>_G, where <em>I</em>_D and <em>I</em>_G are the intensities of D and G bands of the Raman spectra. The analysis of the scratch tests reveals that there are three critical loads for the scratch-induced damage of the DLCs and MoS₂ coatings, corresponding, respectively, to the initiation of periodic V-cracking, the minimum load for periodic semicircle cracking or peel-off, and the minimum load for partial and periodic delamination. Dopants can reduce the friction coefficient of the DLCs and have negligible effect on the Ti/MoS₂ coatings. The Cr interlayer can better enhance the bonding strength between the DLCs and the steel substrate than the Si interlayer. Doping Cr and H can reduce the<em> </em>hardness of DLCs; doping Si can increase the hardness of the<em> </em>DLCs; and doping Ti, Pb, and PbTi can reduce the hardness of the MoS₂ coatings. Deep Symbolic Optimization (DSO) algorithm is used to establish nominal-mathematical formulations between the critical variables for the scratch test and the materials parameters of the surface coating. The DSO analysis demonstrates the feasibility of using “deep-learning” to establish “quantitative” relationships between the critical variables for mechanical deformation and materials parameters.