干摩擦条件下WC增强Cu—Mn—Ni复合涂层的磨损性能研究

通过钎焊工艺在 45 # 钢表面沉积WC颗粒增强Cu -Mn -Ni复合涂层 ,考察了WC颗粒尺寸及含量对WC/Cu-Mn -Ni复合涂层耐磨性能的影响 .实验结果表明 :在给定的试验条件下 ,当WC颗粒质量分数为 30 %而平均粒径为 15 0 μm时 ,复合涂层的耐磨性最佳 ;WC颗粒对复合涂层磨损过程及磨损机制具有显著的影响 ,磨损机理表现为表面微突体间相互滑动产生塑性变形、粘着、脆性剥落及犁削     

氮化物陶瓷颗粒增强铜基复合材料的干摩擦磨损性能研究

采用粉末冶金工艺制备了纯铜以及AlNp／Cu和TiNp／Cu系列铜基复合材料，研究了2种复合材料在不同颗粒含量、不同载荷及滑动速度等条件下与45^#钢对摩时的干摩擦磨损性能，用扫描电子显微镜观察其磨损表面形貌，用能谱仪分析了磨损表面的元素组成．结果表明：与纯铜相比，AlNpCu及TiNp／Cu复合材料的耐磨性能显著提高，随着氮化物颗粒含量增加，2种复合材料的磨损率先下降而后趋于稳定；载荷与滑动速度提高引起的热效应使得纯铜及其复合材料的磨损率增高；由于TiNp的硬度高于AlNp以及本身具有一定的自润滑性能，使得TiNp／Cu复合材料的耐磨减摩性能优于AlNp／Cu复合材料．     

铝合金等离子体淹没氮离子注入层的摩擦学性能研究

用等离子体淹没离子注入技术对ＬＹ１２和ＬＤ１０铝合金表面进行氮离子注入。用俄歇电子能谱分析离子注入层中氮的浓度分布，在此基础上进行了摩擦磨损试验。用扫描电观察和分析磨损表面特征。研究表明：氮离子注入铝合金形成细小，弥散的硬质ＡｌＮ析出相，铝合金表层的显微硬度增加，摩擦系数降低；耐磨性随着注入剂量和电压的增加而提高。磨损机制主要为粘着磨损，随离子注入剂量的增加，粘着磨损趋行减轻。     

聚氨酯在磨粒侵蚀条件下的表面化学效应

在工程实际中，由于高分材料的抗磨粒侵蚀性能都比较而得到了广泛的应用，然而载至目前，所见这类材料在磨粒侵蚀磨损机理方面的研究报道相当之少，而且仅局限于物理过程的考察。因此，对聚氨酯在磨粒侵蚀条件下的表面化学效应进行了试验研究。利用扫描电子显微镜、Ｘ射线光电子能谱仪和傅立叶表面红外分析仪，对这种高分子材料在磨粒侵蚀磨损前后表面的微观形貌、元素组成、结合能和官能闭进行了分析。     

高温磨损中合金组成体的作用及其相互依赖

作者用其自制的高温磨损试验机考察了不同含碳量的Fe-Cr及Fe-Cr-Mn合金的高温耐磨性。通过数据分析及磨损面和亚表层之结构和组织的观察,论述了共晶碳化物及金属基体在高温磨损条件下对材料耐磨性的贡献和相互依赖性。作者指出,高硬度共晶碳化物在高温磨损过程中能够发挥一定的抵抗磨料的作用而使合金的耐磨性提高;基体组织在高温时的塑性变形是影响合金高温耐磨性的一个重要因素,它直接影响共晶碳化物发挥抵抗磨料作用的程度;Fe-Cr-Mn合金中由于Mn的加入改善了基体组织的性能,使其硬度和高温耐磨性均比Fe-Cr合金的高。     

快速镍刷镀层在含磨粒的油润滑条件下的摩擦磨损性能研究

作者在含磨粒的油润滑条件下对快速镍刷镀层的摩擦磨损性能与45~#钢(淬火+低温回火)的进行了对比试验研究。结果表明,镍刷镀层不仅磨损量和摩擦系数始终都比45~#钢的小,而且它的稳定磨损阶段也长而未出现45~#钢那样明显加剧的磨损。作者指出,这主要是由于镍刷渡层组织所含微孔既可吸附和储存润滑油而起辅助润滑作用,又能使磨粒镶嵌于其中而减少磨粒磨损的缘故,而且随着摩擦温升其塑性也得到改善,因而快速镍刷镀层的摩擦磨损性能都比质地致密且硬度更高的45~#钢的好。     

硅相锌基复合材料减摩抗磨性能的研究

为了改善锌铝合金在干摩擦条件下的耐磨性能，拓宽它的工程应用范围，在其中添加质量分数为１０％的Ｓｉ，同时以质量分数０．１％～０．３％的Ｐ－Ｃｕ对硅相进行变质处理，研制出硅相增强锌基复合材料，并且对这种材料的减摩抗磨性能进行了试验研究．结果表明：硅相锌基复合材料分别在干摩擦和２０＃机械油滴油润滑条件下的减摩抗磨性能良好．扫描电子显微镜观察发现，硅相锌基复合材料中的硅相经变质处理得以细化和分布均匀化，这对改善锌铝合金的综合性能具有重要作用；由于硅相的硬度远比基体的高，在滑动摩擦过程中可以起支撑作用，减少偶件与基体的直接接触而降低摩擦磨损     

Prediction and simulation of wear response of Linz–Donawitz (LD) slag filled glass–epoxy composites using neural computation

This article reports on the implementation of a soft computing technique based on artificial neural networks (ANNs) in analyzing the wear performance of a new class of hybrid composites filled with Linz–Donawitz slag (LDS). LDS is a major solid waste generated in huge quantities during steel making. It comes from slag formers such as burned lime/dolomite and from oxidizing of silica, iron etc. while refining the iron into steel in the LD furnace. In this work, hybrid composites consisting of short glass fiber (SGF) reinforced epoxy filled with different LDS content (0, 7.5, 15 and 22.5 wt%) are prepared by simple hand lay‐up technique. Solid particle erosion trials, as per ASTM G 76 test standards, are conducted on the composite samples following a well‐planned experimental schedule based on Taguchi design of experiments. Significant process parameters predominantly influencing the rate of erosion are identified. The study reveals that the LDS content is the most significant among various factors influencing the wear rate of these composites. Further, a model based on ANN for the prediction of erosion performance of these composites is implemented. The ANN prediction profiles for the characteristic wear properties exhibit very good agreement with the measured results demonstrating that a well‐trained network has been created. The simulated results explaining the effect of significant process variables on the wear rate indicate that the trained neural network possesses enough generalization capability of predicting wear rate even beyond the experimental range. Copyright © 2014 John Wiley & Sons, Ltd.     

Effect of Y2O3 on microstructural characteristics and wear resistance of cobalt‐based composite coatings produced on TA15 titanium alloy surface by laser cladding

The effects of Y₂O₃ on the microstructure, phase composition of the coatings, microhardness and wear resistance of cobalt‐based composite coatings prepared by laser cladding were investigated. The TA15 titanium alloy was selected as substrate which the cobalt‐based composite powder with different content of Y₂O₃ was cladded on. The microstructure of the coatings was observed by scanning electron microscope (SEM) and metallurgical microscope. The phase structure of the coatings was determined by X‐ray diffraction (XRD), and the microhardness and wear resistance of the coatings were measured by hardness tester and wear testing machine. The results show that the rare earth oxide Y₂O₃ can refine and purify the microstructure of the coatings, reduce the porosities and cracks and improve compactness of the coatings. Moreover the addition of Y₂O₃ improves the microhardness of the coatings and reduces the friction coefficient, thus improving the wear property of the coatings. And the wear resistance of the coating with Y₂O₃ has improved about 50 times; the highest value of microhardness in the coating is HV1181.1. And 0.8 wt% content of Y₂O₃ in the coating is the best choice for improving the microhardness and wear resistance of the coating. It is feasible to improve the microstructure and tribological properties of laser cladding coatings by adding of Y₂O₃. Copyright © 2014 John Wiley & Sons, Ltd.     

Enhancement of water barrier properties and tribological performance of hybrid glass fiber/epoxy composites with inclusions of carbon and silica nanoparticles

Water barrier properties and tribological performance (hardness and wear behavior) of new hybrid nanocomposites under dry and wet conditions were investigated. The new fabricated hybrid nanocomposite laminates consist of epoxy reinforced with woven and nonwoven tissue glass fibers and two different types of nanoparticles, silica (SiO₂) and carbon black nanoparticles (C). These nanoparticles were incorporated into epoxy resin as a single nanoparticle (either SiO₂ or C) or combining SiO₂ and C nanoparticles simultaneously with different weight fractions. The results showed that addition of carbon nanoparticles with 0.5 and 1 wt% resulted in maximum reduction in water uptake by 28.55% and 21.66%, respectively, as compared with neat glass fiber reinforced epoxy composites. Addition of all studied types and contents of nanoparticles improves hardness in dry and wet conditions over unfilled fiber composites. Under dry conditions, maximum reduction of 47.26% in weight loss was obtained with specimens containing 1 wt% carbon nanoparticles; however, in wet conditions, weight loss was reduced by 17.525% for specimens containing 0.5 wt% carbon nanoparticles as compared with unfilled fiber composites. Diffusion coefficients for different types of the hybrid nanocomposites were computed using Fickian and Langmuir models of diffusion. Copyright © 2017 John Wiley & Sons, Ltd.