Wear Mechanism of Artificial Joint Failure Using Wear Debris Analysis.

Aseptic loosening is one of the main failure modes in artificial joints. Significant information about the aseptic loosening is carried by the wear debris of the joints. In this paper, the wear debris acquired from the ultrahigh molecular weight polyethylene (UHMWPE) artificial joints is prepared and a systematic research is carried out to investigate the wear mechanism of aseptic loosening using the wear debris analysis. The hip joint simulator was used to conduct the wear tests of the CoCrMo-UHMWPE artificial joint friction pairs. The scanning electron microscope (SEM) was employed to analyze the wear debris profiles. The analysis results demonstrated that the UHMWPE joints mainly produced the roundness, tuberous, lacerated, sheet, pole-liked and strip wear debris, and the wear mechanism of the joint aseptic loosening had a close relationship with the morphology of the debris types. The adhesive wear, fatigue wear and laceration under alternating stress were the main causes of the joint failure. Based on the wear debris analysis results, a new diagnosis method using the radar map fractal representation was proposed to diagnose the failure of the artificial joints.

Wear Resistance Properties Reinforcement Using Nano-Al/Cu Composite Coating in Sliding Bearing Maintenance.

Sliding bearing maintenance is crucial for reducing the cost and extending the service life. An efficient and practical solution is to coat a restorative agent onto the worn/damaged bearings. Traditional pure-copper (Cu) coating results in a soft surface and poor abrasion resistance. To address this issue, this paper presents a nano-composite repairing coating method. A series of nano-Al/Cu coatings were prepared on the surface of 45 steel by composite electro-brush plating (EBP). Their micro-hardness was examined by a MHV-2000 Vickers hardness tester, and tribological properties by a UMT-2M Micro-friction tester, 3D profiler and SEM. Then, the influence of processing parameters such as nano-particle concentration and coating thickness on the micro-hardness of nano-Al/Cu coating was analyzed. The experimental analysis results demonstrate that, when the nano-Al particle concentration in electrolyte was 10 g/L, the micro-hardness of the composite coating was 1.1 times as much as that of pure-Cu coating. When the Al nano-particle concentration in electrolyte was 20 g/L, the micro-hardness of the composite coating reached its maximum value (i.e., 231.6 HV). Compared with the pure-Cu coating, the hardness and wear resistance of the nano-composite coating were increased, and the friction coefficient and wear volume were decreased, because of the grain strengthening and dispersion strengthening. The development in this work may provide a feasible and effective nano-composite EBP method for sliding bearing repair.

Prediction of Sliding Friction Coefficient Based on a Novel Hybrid Molecular-Mechanical Model.

Sliding friction is a complex phenomenon which arises from the mechanical and molecular interactions of asperities when examined in a microscale. To reveal and further understand the effects of micro scaled mechanical and molecular components of friction coefficient on overall frictional behavior, a hybrid molecular-mechanical model is developed to investigate the effects of main factors, including different loads and surface roughness values, on the sliding friction coefficient in a boundary lubrication condition. Numerical modelling was conducted using a deterministic contact model and based on the molecular-mechanical theory of friction. In the contact model, with given external loads and surface topographies, the pressure distribution, real contact area, and elastic/plastic deformation of each single asperity contact were calculated. Then asperity friction coefficient was predicted by the sum of mechanical and molecular components of friction coefficient. The mechanical component was mainly determined by the contact width and elastic/plastic deformation, and the molecular component was estimated as a function of the contact area and interfacial shear stress. Numerical results were compared with experimental results and a good agreement was obtained. The model was then used to predict friction coefficients in different operating and surface conditions. Numerical results explain why applied load has a minimum effect on the friction coefficients. They also provide insight into the effect of surface roughness on the mechanical and molecular components of friction coefficients. It is revealed that the mechanical component dominates the friction coefficient when the surface roughness is large (Rq > 0.2 µm), while the friction coefficient is mainly determined by the molecular component when the surface is relatively smooth (Rq < 0.2 µm). Furthermore, optimal roughness values for minimizing the friction coefficient are recommended.

Progress on Fault Mechanisms for Gear Transmissions in Coal Cutting Machines: From Macro to Nano Models.

Numerical modeling has been recognized as the dispensable tools for mechanical fault mechanism analysis. Techniques, ranging from macro to nano levels, include the finite element modeling boundary element modeling, modular dynamic modeling, nano dynamic modeling and so forth. This work firstly reviewed the progress on the fault mechanism analysis for gear transmissions from the tribological and dynamic aspects. Literature review indicates that the tribological and dynamic properties were separately investigated to explore the fault mechanism in gear transmissions. However, very limited work has been done to address the links between the tribological and dynamic properties and scarce researches have been done for coal cutting machines. For this reason, the tribo-dynamic coupled model was introduced to bridge the gap between the tribological and dynamic models in fault mechanism analysis for gear transmissions in coal cutting machines. The modular dynamic modeling and nano dynamic modeling techniques are expected to establish the links between the tribological and dynamic models. Possible future research directions using the tribo dynamic coupled model were summarized to provide potential references for researchers in the field.

Nanosensors for food safety.

This review summarizes recent research and development of nanosensors applied to the food safety. Since the food safety is directly related to the people's health and life, the food detection has received considerable attentions. However, this food security has emerged in China as a severe problem in recent years. Food safety problems frequently compromised due to formaldehyde, poison vegetables, excessive pesticide residues, etc. These kinds of food contaminations could not be detected efficiently by traditional methods. Applying nanotechnology and nanominerals, various food contaminations can be identified accurately. Therefore nanosensors have been widely used in the food detection. We introduce current research on nanosensors followed by the industrial application of nanosensors. Finally, the challenges for the future food safety using nanosensors are discussed.