Nanowear of Hafnium Diboride Thin Films

Chemical Vapor Deposition-grown HfB₂ films were subjected to nanowear testing at normal loads of 50–500 μN. The material response was investigated by measuring residual wear depths and wear scar roughness and by calculating wear rates and specific energies. Films annealed for 1 h at 800°C showed significant reduction in wear rate and required a higher critical energy for wear, compared to as-deposited HfB₂ films. Analysis of roughness of the worn scars revealed that plowing effect dominates at higher loads (200–500 μN), whereas at lower loads, asperity flattening dominates. The excellent response of annealed HfB₂ films to nanotribological testing demonstrates the potential of these films for applications requiring high wear resistance at the nanoscale.     

Tribological performance of PTFE- and PEEK-based coatings under oil-less compressor conditions

Due to favorable tribological performance, PTFE- and PEEK-based polymeric coatings have received interest in air-conditioning and refrigeration compressor applications, as a potential solution to supplement and potentially replace conventional oil lubricants. The literature in this area is somewhat scarce, especially on the tribological performance of PTFE- and PEEK-based polymeric coatings under aggressive conditions simulating compressor operation. In this work, several PTFE-, PEEK-, resin- and fluorocarbon-based polymeric coatings, coated on gray cast iron were tribologically evaluated using a specialized tribometer under compressor specific conditions, that included oscillatory motion (simulating piston-type compressors) and unidirectional motion (simulating swash plate compressor operation). The coatings showed good to excellent tribological performance, and in general PTFE-based coatings exhibited better friction and wear behavior than the rest of the coatings, including PEEK-based coatings. Long-term durability experiments also showed the superiority and suitability of PTFE/Pyrrolidone coating for potential use in oil-less compressors (where oil-less conditions refer to operation in the absence of any liquid lubricant).     

Fault Accommodation for a Class of Nonlinear Uncertain Systems With Event-Triggered Input

The event-triggered fault accommodation problem for a class of nonlinear uncertain systems is considered in this paper.The control signal transmission from the controller to the system is determined by an event-triggering scheme with relative and constant triggering thresholds.Considering the event-induced control input error and system fault threat,a novel eventtriggered active fault accommodation scheme is designed,which consists of an event-triggered nominal controller for the time period before detecting the occurrence of faults and an adaptive approximation based event-triggered fault accommodation scheme for handling the unknown faults after detecting the occurrence of faults.The closed-loop stability and inter-event time of the proposed fault accommodation scheme are rigorously analyzed.Special cases for the fault accommodation design under constant triggering threshold are also derived.An example is employed to illustrate the effectiveness of the proposed fault accommodation scheme.     

Structure and mechanical properties of low temperature magnetron sputtered nanocrystalline (nc-)Ti(N,C)/amorphous diamond like carbon (a-C:H) coatings

This paper reports on the structure and mechanical properties of ~ 2 μm thick nanocomposite (nc-) Ti(N,C)/amorphous diamond like carbon (a-C:H) coatings deposited on 100Cr6 steel substrates, using low temperature (~ 200 °C) DC reactive magnetron sputtering. The carbon content was varied with acetylene partial pressure in order to obtain single layer coatings with different a-C:H carbon phase fractions. The nanocrystalline Ti(N,C) phase is approximately stoichiometric for all coatings and the a-C:H phase fraction increases from 31 to 47 at.% as the coatings stoichiometry changed from TiC_1.34 N_0.51 to TiC_2.48 N_0.48, respectively. TiC_1.34 N_0.51 coatings showed the highest nanoindentation hardness (H) of ~ 14 GPa and a modulus (E_r) of ~ 144 GPa; H reduced to < 6 GPa and E_r to < 70 GPa for TiC_2.48 N_0.48 coatings. nc-Ti(N,C)/a-C:H coatings are promising candidates for applications where better matching of the modulus between a relatively low modulus substrate, hard loading support layer and low modulus-high H/E ratio top layer is required.     

Neural-network-based robust fault diagnosis in robotic systems

Fault diagnosis plays an important role in the operation of modern robotic systems. A number of researchers have proposed fault diagnosis architectures for robotic manipulators using the model-based analytical redundancy approach. One of the key issues in the design of such fault diagnosis schemes is the effect of modeling uncertainties on their performance. This paper investigates the problem of fault diagnosis in rigid-link robotic manipulators with modeling uncertainties. A learning architecture with sigmoidal neural networks is used to monitor the robotic system for any off-nominal behavior due to faults. The robustness and stability properties of the fault diagnosis scheme are rigorously established. Simulation examples are presented to illustrate the ability of the neural-network-based robust fault diagnosis scheme to detect and accommodate faults in a two-link robotic manipulator.     

Effect of Molecularly Thin Lubricant on Roughness and Adhesion of Magnetic Disks Intended for Extremely High-Density Recording

For extremely high-density recording using conventional technologies, the fly-height needs to decrease to less than ten nanometers. To allow such operation, disk and slider surfaces must become extremely smooth, down to root-mean-square (RMS) roughness values of a few angstroms. For super-smooth disks, molecularly thin lubricants are applied to improve tribological performance of head/disk interfaces. The focus of this study is to quantify the effect of lubricant thickness in terms of detailed roughness parameters and to evaluate the effect of roughness and molecularly thin lubricant on adhesion of magnetic disks intended for extremely high-density recording. Three identical ultra-low-flying disks have been fabricated from the same batch for this particular experiment. To investigate the effect of molecularly thin lubricants on disk roughness, super-smooth magnetic disks with increasing lubricant thickness have been measured and studied, using a primary roughness parameter set. It describes amplitude, spatial, hybrid, and functional aspects of surface roughness and is used to quantify the extremely smooth disk roughness as a function of lubricant thickness. It is found that in addition to simple amplitude parameters, hybrid and functional parameters also capture small features on the disk roughness and show distinct trends with increasing lubricant thickness. Subsequently, a continuum-based adhesion model that uses three parameters from the primary roughness parameter set, is used to predict how the varying thickness of molecularly thin lubricant and the resulting disk roughness affect intermolecular forces at ultra-low-flying head-disk interfaces. It is found that a thicker lubricant layer of 2nm causes higher adhesion forces for ultra-low-flying-heights in the range of 1–3 nm     

Tip-radius effect in finite element modeling of sub-50 nm shallow nanoindentation

An accurate representation of the indenter geometry is essential for correct finite element simulations of shallow indentations of less than 50 nm using a 90° cube-corner indenter. A nonlinear regression method for estimating the tip radius of an indenter is presented, which takes into account that initially the contact is only with the spherical surface of the tip and subsequently also includes contact with the equivalent conical surface. The tip radius of a Berkovich indenter is estimated by a finite element modeling (FEM) best-fitting method. Using the estimates of tip radii, the yield strength of gold in the film of a gold/silicon system was estimated from the best fit between FEM simulations and nanoindentation experiments using the 90° cube corner indenter, which compared favorably with an FEM simulation and nanoindentation data using a Berkovich indenter.     

Boosting the Hardware-Efficiency of Cascade Support Vector Machines for Embedded Classification Applications

Support Vector Machines (SVMs) are considered as a state-of-the-art classification algorithm capable of high accuracy rates for a different range of applications. When arranged in a cascade structure, SVMs can efficiently handle problems where the majority of data belongs to one of the two classes, such as image object classification, and hence can provide speedups over monolithic (single) SVM classifiers. However, the SVM classification process is still computationally demanding due to the number of support vectors. Consequently, in this paper we propose a hardware architecture optimized for cascaded SVM processing to boost performance and hardware efficiency, along with a hardware reduction method in order to reduce the overheads from the implementation of additional stages in the cascade, leading to significant resource and power savings. The architecture was evaluated for the application of object detection on \(800\times 600\) resolution images on a Spartan 6 Industrial Video Processing FPGA platform achieving over 30 frames-per-second. Moreover, by utilizing the proposed hardware reduction method we were able to reduce the utilization of FPGA custom-logic resources by \(\sim \)30%, and simultaneously observed \(\sim \)20% peak power reduction compared to a baseline implementation.