TEM observations of wear mechanisms of TiAlCrN and TiAlN/CrN coatings grown by combined steered-arc/unbalanced magnetron deposition

The dry sliding wear of monolayer TiAlCrN and TiAlCrYN and multilayer TiAlN/CrN coatings has been investigated against a BM2 tool steel counterface using a ring on block configuration at 91 N, 0.42 m/s. The coatings were deposited on a BM2 tool steel substrate by combined steered-arc/unbalanced-magnetron deposition. The wear rate of the multilayer was superior to the monolayer, although both provide a substantial improvement compared with the wear behaviour of the base BM2 tool steel (e.g., wear rate = 6.1 × 10-4 mm3/m for the BM2 tool steel; 3.98 × 10-5 mm3/m for the TiAlCrN monolayer and 2.58 × 10-5 mm3/m for the TiAlN/CrN multilayer). Wear of the coatings occurred by several mechanisms, fine scale (< 200 nm) detachment in the early stages and micron scale detachment associated with cracking in the coating in the later stages. Detailed transmission electron microscopy of cross-sections of the worn surface indicated that two dominant types of cracking were present within the coating: (1) cracking perpendicular to the coating surface, often along columnar grain boundaries, typically running through the entire coating; (2) cracking approximately parallel to the worn surface, extending across several columnar grains. For the multilayers, there was no evidence that the spalling was induced by decohesion along the interface of the multilayers. Limited surface deformation was detected at the worn surface of the TiAlCrYN and TiAlCrN, but not at the worn surface of the TiAlN/CrN, tested under identical conditions. In contrast, the uncoated BM2 tool steel worn surface exhibited extensive plastic deformation. The relationship between wear mechanism and coating structure is discussed. © 1999 Published by Elsevier Science S.A. All rights reserved

Lubricated sliding wear behaviour of aluminium alloy composites

Interest in aluminium alloy (Al-alloy) composites as wear resistant materials continues to grow. However, the use of the popular Al-alloy-SiC composite can be limited by the abrasive nature of the SiC, leading to increased counterface wear rates. This study reports new Al-alloy composites that offer high wear resistance, to a level similar to Al-alloy-SiC. Aluminium alloy (2124, 5056) matrix composites reinforced by nominally 15 vol.% of Cr3Si, MoSi2, Ni3Al and SiC particles were prepared by a powder metallurgy route. The aluminium alloy matrix was produced by gas atomisation, and the Cr3Si, MoSi2 and Ni3Al were prepared by self-propagating high temperature synthesis (SHS), while the SiC was from a standard commercial supply. Following blending, the particulates were consolidated by extrusion, producing a homogenous distribution of the reinforcement in the matrix. Wear testing was undertaken using a pin-on-ring configuration against an M2 steel counterface, with a commercial synthetic oil lubricant, at 0.94 m/s and a normal load of 630 N, corresponding to initial Hertzian contact pressures of 750–890 MPa (the exact value depending on the material properties). Specific wear rates at sliding distances exceeding 400 km were in the range 4.5–12.7 × 10?10 mm3/Nm. The monolithic alloys gave the highest specific wear rates, while the MoSi2 and Cr3Si reinforced alloys exhibited the lowest. The worn surface has been analysed in detail using focused ion beam (FIB) microscopy to determine the sub-surface structural evolution and by tomographic reconstruction of tilted scanning electron microscopy (SEM) images, to determine the local worn surface topography. Consequently, the wear mechanisms as a function of alloy composition and reinforcement type are discussed.<br/

On Nesting Monte Carlo Estimators

Many problems in machine learning and statistics involve nested expectations and thus do not permit conventional Monte Carlo (MC) estimation. For such problems, one must nest estimators, such that terms in an outer estimator themselves involve calculation of a separate, nested, estimation. We investigate the statistical implications of nesting MC estimators, including cases of multiple levels of nesting, and establish the conditions under which they converge. We derive corresponding rates of convergence and provide empirical evidence that these rates are observed in practice. We further establish a number of pitfalls that can arise from naive nesting of MC estimators, provide guidelines about how these can be avoided, and lay out novel methods for reformulating certain classes of nested expectation problems into single expectations, leading to improved convergence rates. We demonstrate the applicability of our work by using our results to develop a new estimator for discrete Bayesian experimental design problems and derive error bounds for a class of variational objectives.Comment: To appear at International Conference on Machine Learning 201

Metal ceramic wear mechanisms

Sliding wear of metal-on-ceramic, ceramic-on-metal, and ceramic-on-ceramic have been investigated using a tri-pin-on-disc machine. A technique has been developed for thin foil preparation for transmission electron microscopic examination perpendicular to the wear surface. The role of transformation toughening in the wear behaviour of zirconia ceramics has been investigated. In addition, the role of high strain deformation in a steel surface has been evaluated. The wear factor of 316L stainless steel pins worn against a zirconia disc was found to decrease as the load was increased, believed to be associated with metal oxide formation. TEM of the stainless steel revealed a worn surface which consisted of a mechanical mixture of metal oxide and heavily deformed metal. Deformation of the metal had occurred by shear banding with a microstructure similar to that observed in rolled specimens, although the texture formed was a wire texture rather than a rolling texture. The crystallite size was found to decrease towards the surface, demonstrating that the shear stress was a maximum at the surface. The shear bands at the surface had always been formed by the passage of the last asperity indicating that contact was plastic over the load range 6-60N/pin. The majority of wear occurred by transfer resulting from plastic overload, although a contribution to the material loss was made by metal extruded off the end of the pin as a result of the high strains. The depth of deformation correlated closely with the wear volume. The wear of the zirconia discs was found to be dominated by metal transfer. With Mg-PSZ, transformation occurred cooperatively in crystallographically determined bands. Microcrack coalescence led to preferential wear in these bands. However, with a Y-TZPdisc transformation appeared to have been responsible for widespread surface fracture. The wear of zirconia pins against a bearing steel disc gave limited metal transfer. Very little transformation of tetragonal to monoclinic was observed. However, milder forms of the transformation related wear mechanism did occur. Zirconia had formed a solid solution with the iron oxide, leading to the conclusion that the wear mechanism was tribochemically based. TZP worn against a ZTA disc showed evidence of very high temperature rises at the interface. The surface layer was amorphous and contained a mixture of alumina and zirconia suggesting that melting had occurred at the interface during sliding. At a depth of O.5pm. the surface consisted of heavily elongated tetragonal grains, with a low dislocation density, indicating a strain of at least 1.7. At a depth of 2-4pm a layer of monoclinic was found. There was evidence that the stresses imposed by friction extended to at least 8-10pm from the surface. TZP containing 20vol% SiC whiskers gave exceptionally low wear rates when worn against a ZTA disc. The greater wear resistance is believed to be a result of the improved load bearing capacity and of the higher thermal conductivity. It is clear that the poor thermal conductivity of zirconia dominates its tribological behaviour. Temperature generation was high enough to substantially reduce the driving force for transformation of the tetragonal to monoclinic, with a high enough temperature for plastic' deformation where a low thermal conductivity counterface was used. Where transformation occurred, its effect was to increase the wear rate

Auto-Encoding Sequential Monte Carlo

We build on auto-encoding sequential Monte Carlo (AESMC): a method for model and proposal learning based on maximizing the lower bound to the log marginal likelihood in a broad family of structured probabilistic models. Our approach relies on the efficiency of sequential Monte Carlo (SMC) for performing inference in structured probabilistic models and the flexibility of deep neural networks to model complex conditional probability distributions. We develop additional theoretical insights and introduce a new training procedure which improves both model and proposal learning. We demonstrate that our approach provides a fast, easy-to-implement and scalable means for simultaneous model learning and proposal adaptation in deep generative models

Investigating worn surfaces of nanoscale TiAlN/VN multilayer coating using FIB and TEM

TiAlN/VN multilayer coatings exhibit excellent dry sliding wear resistance and low friction coefficient, believed to be associated with the formation of tribo-films comprising Magnéli phases such as V2O5. In order to investigate this hypothesis, dry sliding wear of TiAlN/VN coatings was undertaken against Al2O3. Focused ion beam was used to generate site-specific TEM specimens. A thin (2-20nm) tribo-film was observed at the worn surface, with occasional 'roll-like' wear debris (φ 5-40nm). Both were amorphous and contained the same Ti, Al and V ratio as the coating, but with the nitrogen largely replaced by oxygen. No evidence of Magnéli phases was found. © 2006 IOP Publishing Ltd