Reinforcement Particle Size Research Articles

Influence of particle size and spatial distribution of B4C reinforcement on the microstructure and mechanical behavior of precipitation strengthened Al alloy matrix composites

We report on an investigation of the influence of reinforcement particle size on the microstructure and mechanical behavior of Al metal matrix composites. In our work, Al 7075/B4C composites containing three types of B4C particle sizes (56.9µm, 4.2µm and 2.0µm) were synthesized and studied. For a constant value of volume fraction of B4C, the composite with coarse reinforcement particles exhibited a relatively homogeneous and discrete distribution of the B4C particles while the composites with fine reinforcement exhibited agglomeration of the B4C particles. The composite with the smallest B4C particles possessed the highest yield strength and fracture strength. Quantitative analysis of the strengthening mechanisms revealed that smaller B4C particles lead to larger values in strain gradient strengthening as well as CTE mismatch strengthening, which are significantly correlated to the geometrically necessary dislocations caused by the presence of B4C. In addition, the different spatial distributions of the B4C particles contributed to different fracture mechanisms in the composites.

Effect of Reinforcement Particle Size and Weight Fraction on the Mechanical Properties of SiC Particle Reinforced Al Metal Matrix Composites

The production of engineering materials that possess low density and distinguished mechanical properties has been one of the most stimulating issues in both academic and industry in the last three decades, which caused a shift in research from monolithic to composite materials. For this reason aluminium matrix composites were widely manufactured and used in many aerospace and automobile industries. In this work, the effect of different processing parameters such as particle size and percentage of reinforcement on the tensile properties of Al-10Sb/SiC composite was investigated. Stir casting technique was used to fabricate the composites. The results showed a significant improvement in the yield and ultimate tensile strengths of the composite with increasing the SiC content and/or decreasing the particle size of the reinforcement. The yield and ultimate tensile strengths of the Al composites produced with the finest particle size of 115 µm and at 9% wt. Sic were the highest among all composites. On the other hand the composite exhibited impaired ductility compared with the unreinforced Al alloy.

Effect of modifier elements on machinability of Al-20%Mg2Si metal matrix composite during dry turning

ABSTRACTThe principle aim of this study was to observe the effect of machining parameters as well as the separate additions of 0.4 wt% bismuth, 0.01 wt% strontium, and 0.8 wt% antimony on the machinability of Al-20%Mg2Si in situ metal matrix composite. Microstructure alteration, surface roughness, main cutting force, and chip morphology were taken into account as indices to examine the effect of modifiers and machinability during dry turning. It was found that the additives modify the Mg2SiP particles by changing the particle shape from coarse primary to polygonal shape and decrease the particle size and aspect ratio as well as increase the particle density. Results show that the modified work-pieces present adequate machinability with respect to cutting force and surface roughness. The smaller reinforcements enable lower surface roughness values to be obtained even if they are pulled out, fractured, or elongated. In addition, the modified work-pieces encourage lower surface roughness values in comparison with unmodified work-piece due to less built-up-edge formation. A scenario for surface roughness of Al-Mg2Si composite with respect to the size and aspect ratio of reinforcement particles is proposed in this study.

Effect of variable particle size reinforcement on mechanical and wear properties of 6061Al–SiCp composite

The influence of reinforcement particle size variation plays a major role on the properties of Al–SiCp composite. Therefore, this study aim to investigate the mechanical and wear performance of single particle size (SPS) and multiple particle size (MPS) Al–SiCp composite prepared by stir casting process. The SPS comprises three categories; fine (15 μm), intermediate (40 μm) and coarse (80 μm) particle sizes and combination of the three sizes accounts for the MPS in the ratio 1:1:2, respectively. Oxidation of the SiCp and addition of 1 wt% Mg during composite processing resulted to interface reaction products such as MgO (magnesium oxide) and MgAl2O4 (magnesium aluminate) which suppresses the potential formation of undesired Al3C4 (aluminium carbide). The study reveals that MPS composite improved the hardness and impact properties with enhanced wear performance compared to SPS composite. Characterization of the composite morphology and phases was performed using scanning electron microscope and X-ray diffraction analysis. This study provides an effective method of optimizing the properties of Al–SiCp composite by integrating MPS with low volume fraction of reinforcement phase.

Friction-stir processing of an AA8026-TiB2-Al2O3 hybrid nanocomposite: Microstructural developments and mechanical properties

In this study, micro- and nano-sized TiB2 and Al2O3 particles were incorporated separately and simultaneously through the AA8026 aluminum base alloy during multi-pass friction stir processing (FSP) with 100% overlapping to fabricate metal matrix mono and hybrid nanocomposites. Various FSP conditions including different rotational speeds (w), traverse velocities (v), and processing pass numbers were assessed to attain a homogenous distribution of reinforcing particles through the Al-metal matrix. Moreover, the impacts of size (micro or nano) and type of reinforcement particles (TiB2 and Al2O3) on the process-ability of single and hybrid nanocomposite systems were examined. Microstructures of different zones and distributions of reinforcing ceramic particles through the Al-matrix under various processing conditions were studied and characterized by using optical (OM), scanning (SEM), and transmission electron microscopy (TEM) techniques, respectively. The main mechanical characteristics of the prepared nanocomposites, such as, indentation Vickers hardness, tensile properties, and wear resistance were measured and compared for all of the various processing conditions. By optimization of the FSP parameters, as a rotational speed of 1600rpm and a traverse velocity of 40mm/min after 4 passes, a uniform AA8026-TiB2-Al2O3 hybrid nanocomposite was attained with significant improvements (~70–100%) in the different mechanical properties. As a result, the tensile yield strength of ~270MPa, elongation of ~4.5%, and indentation Vickers hardness of ~141HV were obtained. Also, the average wear rate was reduced from the 21×10−3mg/m value for the AA8026 base alloy down to 2.6×10−3mg/m for the best processed nanocomposite. A direct relationship between the wear rate and the indentation hardness resistance was demonstrated. Finally, effects of FSP processing conditions and reinforcement particles (type and size) on the microstructure and mechanical properties of the FSPed Al-matrix nanocomposites were addressed and discussed.

Experimental Study of Surface Integrity of Al/SiC Particulate Metal–matrix Composites in Hot Machining

Al/SiCp Metal Matrix Composites (MMCs) are the new class of materials and are rapidly replacing conventional materials in various applications industrial and aerospace applications. These materials are generally regarded as extremely difficult to machine, because of the abrasive characteristics of the reinforced particulates. It has poor machinability such as excessive tool wear and fracturing of the reinforcement particles on machined surface. It leaves behind adhered particle fragments, pits and cavities despite superior excellent engineering properties. These characteristics in machining of Al/SiCp MMCs tend to adversely affect the machined surface quality/integrity. Hence, an attempt is made to improve the machinability of Al/SiCp MMCs and surface quality by hot machining. This paper presents the results of an experimental research on hot machining of Al/SiCp MMCs produced by stir casting. PVD coated carbide inserts were used under dry cutting conditions. Experiments were carried out on CNC lathe. Experiments on Al/SiCp 10% composites of two different particle size of Silicon carbide reinforcement i.e. coarse and fine (220 and 600 mesh size respectively) are performed using L16 orthogonal array as per the Taguchi method. The study of Al/SiCp MMCs on the basis of surface integrity was tried out in order to know the machinability. The experimental study showed that feed, depth of cut and preheating temperature have a significant influence on cutting force, feed force, thrust force, surface roughness and micro-hardness variation beneath the machined surface. The micro-hardness is found to be higher near the machined surface layer and decreases with the depth of machined subsurface for all experimental conditions. Qualitative analysis of surface and subsurface damage is analysed using SEM photographs. A SEM photograph reflects the SiC particulates debonding, fracture, feed marks and smeared layer on machined surface. Better values of surface roughness are obtained at 60°C temperature during machining of both Al/SiC/10p/220 (0.776μm) and Al/SiC/10p/600 (0.640μm) MMCs.

Mechanical Properties of 7075 Aluminium Matrix Composites Reinforced by Nanometric Silicon Carbide Particulates

Aluminum Matrix composites (AMCs) are known as light weight and high-strength materials with their potential application in areas such as aerospace, automobile, defence, engineering and other industries. AMCs have the advantage to significantly reduce the overall weight of the vehicles and aircraft while maintaining their structural strength. Reinforcement of micron or nano-sized range particles with aluminium matrix yields improved mechanical and physical properties in composite materials. The strength of Al matrix composites will be improved about 20% with decreasing reinforcement particle size from micrometric scale to nanometric scale. In this study, Al7075 alloy and nano SiC composites have been fabricated by Electromagnetic stir casting process combined with mechanical stirring. Different weight % of nano SiC particles (0.5, 1, 1.5, and 2 wt%) were used for synthesis of composites. Certain test methods scanning electron microscopy (SEM) and X-Ray diffraction (XRD) are used to examine the microstructure along with the measurement of impact strength of the nano composite. SEM microstructure shows SiC particles are fairly infused into the matrix alloy with agglomeration and porosity at some places. X-Ray Diffraction (XRD) analysis acknowledged that no unknown crystalline elements are present in the composites while mixing reinforcement with Al alloy matrix. The results impact strength shows that impact strength decreases with respect to the base metal because of brittle nature of reinforcement.

Wire EDM Mechanism of MMCs with the Variation of Reinforced Particle Size

The size of reinforced particles notably affects the electro-discharge machining (EDM) of metal matrix composites (MMCs). This paper explores the mechanism of wire EDM of MMCs with different sizes of reinforced particles as well as the corresponding unreinforced matrix material. The mechanisms of material removal, surface generation, and taper kerf formation were investigated. This study shows that the particles’ ability to protect matrix materials from the intense heat of electric arc controls the material removal rate, surface generation, and taper of kerf. The low melting point matrix material is removed very easily, but the heat resistance reinforced particles delay the removal of material and facilitate the transfer of the workpiece material to wire electrode and vice versa. Thus, the material stays longer in touch with intense heat and affects the surface generation, wire electrode wear, and width of the kerf.

Energy damping in magnesium alloy composites reinforced with TiC or Ti2AlC particles

In part I of this study, we reported on the synthesis and mechanical properties of Mg alloy composites reinforced with TiC or Ti2AlC particles. In this, part II, we explore their damping as a function of the nature and volume fraction of the reinforcing particles and the matrix alloy composition. Using Mg alloys instead of pure Mg and reducing the reinforcement particle size reduced the damping capabilities of these composites. In all cases, a tradeoff was found between a composite's stiffness and its damping capability – as measured by the area enclosed in its fully and spontaneously reversible cyclic compressive stress–strain curves. Low stiffness materials, such as pure Mg and its alloys, dissipated significant amounts of energy, but only at lower stresses. The TiC reinforced composites dissipated the least energy. However, by combining two solids, Mg or its alloys with Ti2AlC, that are both inherently damping, it is possible to dissipate roughly 25% of total applied mechanical energy, while simultaneously maintaining ultimate compressive stresses and stiffness values that were almost as good as those of the TiC reinforced composites. However, since below 200MPa, Ti2AlC does not dissipate much energy, the difference between the two was only manifested at stresses >200MPa. When the interfaces were strong, cyclic hardening and no fatigue were observed; when the interfaces were weak, cyclic softening and fatigue were recorded. Most importantly, we show that the energy needed to extend or bow out the dislocations – that are presumably strongly pinned and postulated to be the mechanism for energy dissipation – is a linear function of the applied stresses for the end members – Mg and Ti2AlC – and is even more pronounced for the composites.

Effect of particle size on the thermal and mechanical properties of aluminum composites reinforced with SiC and diamond

The effect of particle size on thermal conductivity (TC) and bending strength was investigated in the SiC/Al and diamond/Al (Dia/Al) composites for thermal management applications. The results showed that with the particle size of SiC increasing from 7 to 250μm, the TC of the 40vol.% SiC/Al composite was improved by 50%, from 182 to 272W/mK, while the bending strength decreased by 100% from 352 to 175MPa. Comparatively, with diamond particles increasing from 30 to 200μm, the TC of the 40vol.% Dia/Al composite increased by around 52% from 313 to 475W/mK, and the bending strength declined by 32% from 327 to 223MPa. Characterization of fracture surface indicated that large SiC particles featured by an irregular shape tended to fracture prior to the Al matrix during loading, while large diamond particles with a regular shape did not have such a tendency. Moreover, diamond particles with a high intrinsic TC contributed to global TC much more than SiC ones with a relatively low TC. Thus, in order to balance thermal and mechanical properties of particulate reinforced aluminum composites, particle size of reinforcements should be well compromised according to their intrinsic properties.

Effect of high ratio of reinforcement particle size to matrix powder size and volume fraction on microstructure, densification and tribological properties of SiCp reinforced metal matrix composites manufactured via hot pressing method

The effects of reinforcement particle to matrix powder size ratio (Rs/Ms) and volume fraction of reinforcement particle on the microstructure, densification and tribological properties of SiCp reinforced aluminium (Al–SiCp) metal matrix composites manufactured via hot-pressing method were investigated for high ratios of Rs/Ms (1≤Rs/Ms≤4). Central composite design (CCD) method was used for experimental design. Based on the results obtained in this study, density of 99% could be reached and a uniformly distribution of reinforcement particles in microstructure could be observed for the composite with the volume fraction of 15% and Rs/Ms ratio of 3.5. Also, the relative density increased as Rs/Ms ratio increased up to the reinforcement volume fraction of 17.5%. However, an increase in Rs/Ms ratio had an unfavourable effect on the density at the high volume fractions (≥17.5). Results also showed that there was no direct correlation between hardness and wear resistance as a function of volume fraction and Rs/Ms ratio. The wear tests were performed under adhesive wear condition using pin-on-ring test machine. The results showed that Rs/Ms ratio had a strong influence on the microstructure and wear behaviour of Al–SiCp composites. Up to the volume fraction of 15%, as the reinforcement particle size or reinforcement particle to matrix powder size ratio increased, the wear loss decreased; however, at the volume fractions higher than 17.5%, wear loss increased with increasing the reinforcement particle to matrix powder size ratio. Both adhesive and abrasive wear mechanisms were the dominant failure mechanisms at the low volume fractions (≤15%) while delamination wear was the most dominant failure mechanism for the composites with higher volume fractions (≥20%).

Influence of Fiber Reinforcement and Abrasive Particle Size on Three-Body Abrasive Wear of Hybrid Friction Composites

In the present study, enhancement of abrasion resistance of phenol formaldehyde (PF) resin based hybrid friction composites with different ingredients viz. binder, micron sized fibers and fillers have been synergistically investigated. Hybrid friction composites based on basalt and recycled aramid fibers were prepared using compression moulding. Three-body abrasive wear tests were conducted according to ASTM G-65 standard by dry sand/rubber wheel abrasion tester using two different size of angular silica sand abrasives (212 and 425 μm) at a constant load of 40 N. The results indicated that the wear volume loss increases with increasing abrading distance and abrasive particle size. However, the specific wear rate decreased with increasing abrading distance and increases with increase in abrasive particle size. Addition of fiber content has a significant influence on the abrasive wear performance of these composites. Further, the worn surfaces were examined by scanning electron microscopy to identify the involved wear mechanisms.

Homogenization of Carbides in Ni60/WC Composite Coatings Made by Fiber Laser Remelting

In the current study, the effect of laser remelting on homogenization of carbides in WC-reinforced Ni60 composite coatings was investigated. Ni60 + 50 wt% WC composite coatings were fabricated on the surface of Q550 steel by LDF4000-100 fiber laser device. First cladding layer was made by rectangle laser spot and then circular laser spot was utilized to remelt the coatings. Microstructure characteristics were investigated by optical microscope and scanning electron microscopy. Elemental distribution and phase constitution were analyzed by energy disperse spectroscopy and X-ray diffraction. The results showed that accumulation of residual WC particles was sufficiently eliminated under the effect of laser remelting. The irregularly shaped carbides in first cladding layer were transformed into well-distributed polygonal carbides by laser remelting. Statistical analysis indicated median size of reinforcement particles decreased from 35.40 to 5.62 µm. Microhardness of remelted region had a smooth profile and decreased by −50 HV0.1 than that of first cladding region. Homogenization of carbides in nickel composite coating was well realized by laser remelting.

Microstructural evolution and sliding wear studies of copper-alumina micro- and nano-composites fabricated by spark plasma sintering

AbstractCopper-alumina nanocomposites of 0.5, 1, 3, 5, 7 vol.% alumina (average size <50 nm) reinforced in copper matrix were fabricated using spark plasma sintering (SPS) technique. Another set of microcomposites containing 1, 5, 20 vol.% of alumina (average size ∼10 μm) had been fabricated to compare the physical as well as mechanical attributes of composites with variation of reinforcement particle size. These micro- and nano-composites have been characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), transmission electron microscopy (TEM) followed by microhardness, nanoindentation hardness, and wear measurements. It has been found that hardness values are higher for nanocomposites as compared to microcomposites. It is also found that wear resistance increases with increasing alumina content. The microcomposites show better wear resistance than nanocomposites for the same composition. The interaction of copper and alumina results in the formation of CuAlO2 which manifests differential interfacial phenomenon. We have obtained 95.82% densification and 93.17 HV hardness for spark plasma sintered Cu-20 vol.% Al2O3 microcomposite. The wear rate is appreciably low, that is, 0.86×10-4 mm3N-1m-1 for 20 vol.% alumina reinforced copper microcomposite.

Effect of Single, Double and Triple Particle Size SiC and Al2O3 Reinforcement on Wear Properties of AMC Prepared by Stir Casting in Vacuum Mould

The aim of present research work is to study the effect of single particle size (SPS), dual particle size (DPS) and triple particle size (TPS) of SiC and Al2O3 reinforcement as hybrid solute on wear properties of aluminium matrix composite (AMC) prepared by stir casting in vacuum mould. The ABS plastic based master pattern (prepared with fused deposition modelling setup) for vacuum mould has been used in the present study. The friction and wear tests were carried out using a pin-on-disc type tribo-test machine under dry sliding condition. The results of study suggest that SPS based AMC exhibited better wear resistant properties as compared to DPS and TPS. The study also highlights the effect of other controllable process parameters of vacuum moulding process (namely: vacuum pressure, sand grain size and proportion of solutes) on wear behavior of AMC.

Modeling machining of particle-reinforced aluminum-based metal matrix composites using cohesive zone elements

Finite element modeling for the machining of heterogeneous materials like particle-reinforced metal matrix composites has not been much successful as compared to homogeneous metals due to several issues. The most challenging issue is to deal with severe mesh distortion due to nonuniform deformation inside the workpiece. Other problems are related to the modeling of the interface between reinforcement particles and matrix and tool-reinforcement particle interaction. In this study, different strategies are adopted for finite element models (FEM) to cope with the above issues and comparative analyses have been performed. These 2D FE models are based on plane strain formulations and utilize a coupled temperature displacement method. The workpiece is modeled using reinforcement particle size and volume fraction inside the base matrix. The interface between the reinforcement particles and the matrix is modeled by using two approaches, with and without cohesive zone elements, and the chip separation is modeled with and without using a parting line. This allows models to simulate the local effects such as tool-reinforcement particle interaction and reinforcement particle debonding. In addition, the models can predict cutting forces, chip morphology, stresses, and temperature distributions. The effects of different methodologies on the model development, simulation runs, and predicted results have been discussed. The results are compared with experimental data, and it has been found that the utilization of cohesive zone elements (CZE) with the parting line approach seems to be the best one for the modeling of metal matrix composite (MMC) machining.

Investigation of the wear resistance and microstructure of Al/SiC metal matrix composites as a function of reinforcement volume fraction and reinforcement to matrix particle size ratio applying artificial neural network

Abstract In this study, the influences of reinforcement volume fraction and the ratio of the reinforcement particle size to the matrix particle size on the wear behaviour of Al/SiC metal matrix composites were investigated by use of a model function obtained from an artificial neural network. Hardness and ball-on-disc wear tests were applied to Al/SiC composites manufactured via a powder metallurgy method. The results indicate that as the reinforcement volume fraction and the ratio of the reinforcement particle size to the matrix particle size increase, the wear loss decreases except in two cases; in the first case (vol.% ≤ 7.5), as the ratio of the reinforcement particle size to the matrix particle size rises, the wear loss increases and then decreases. In the second case, the decreasing trend of wear loss at high values of volume fraction (≥ 15%) declines and then increases where the value of the reinforcement to the matrix particle size ratio is about 1.

Application of a Neural Network Model for Prediction of Wear Properties of Ultrahigh Molecular Weight Polyethylene Composites

In the current study, the effect of applied load, sliding speed, and type and weight percentages of reinforcements on the wear properties of ultrahigh molecular weight polyethylene (UHMWPE) was theoretically studied. The extensive experimental results were taken from literature and modeled with artificial neural network (ANN). The feed forward (FF) back-propagation (BP) neural network (NN) was used to predict the dry sliding wear behavior of UHMWPE composites. Eleven input vectors were used in the construction of the proposed NN. The carbon nanotube (CNT), carbon fiber (CF), graphene oxide (GO), and wollastonite additives are the main input parameters and the volume loss is the output parameter for the developed NN. It was observed that the sliding speed and applied load have a stronger effect on the volume loss of UHMWPE composites in comparison to other input parameters. The proper condition for achieving the desired wear behaviors of UHMWPE by tailoring the weight percentage and reinforcement particle size and composition was presented. The proposed NN model and the derived explicit form of mathematical formulation show good agreement with test results and can be used to predict the volume loss of UHMWPE composites.

Determining the Effects of Machining Parameters and Modifier on Surface Roughness in Dry Turning of Al-20%Mg2Si-PMMC using Design of Experiments (DOE)

The machinability of particulate metal matrix composites (PMMC) is influenced by the matrix mechanical properties as well as size, distribution and volume fracture of reinforcement particles. In order to machine different PMMCs, especial machining conditions based on the type of operation must be considered. The main principle aim of this observation is to assess the effect of machining parameters involving cutting speed, feed rate and Strontium addition on surface roughness of Al-20%Mg2Si in-situ composite. In this study design of experiment (DOE) methodology was applied to design experimental trials and the results were analyzed using Analysis of Variance (ANOVA). The dry turning was done on ALPHA 1350S CNC lath machine with a new insert for each test to ensure accurate reporting. The results showed that the Mg2Si particles morphology such as size, shape and distributions have altered by Sr addition. The statistical analysis revealed that all main effects influenced the surface roughness. The predicted results are found to be so closer to actual results. Due to low proximity difference between predicted results and actual results with each other, based on confirmation tests, the predictive model is sufficient accurate at reliability of 95%.

Prediction of tribological behaviour of rice husk ash reinforced aluminum alloy matrix composites using artificial neural network

Artificial Neural Network (ANN) model was developed to predict the wear rate and coefficient of friction for the Rice Husk Ash (RHA) reinforced aluminum alloy composite. The composite was fabricated using the stir cast route and their tribological behavior was tested using Pin-on-Disc wear tester. The experiments were conducted based on Orthogonal array (L27) generated through the Taguchi Technique and their results were used to train the ANN model. The input parameters assigned to develop an ANN model are applied load, sliding speed, RHA particle size and weight percentage of RHA reinforcement. A four layer perception network having 4-7-8-2 architecture was found to be the optimum network. Finally, confirmation test was done to verify the predictive model with the experimental results and also the wear surface morphology of the wear pin was analyzed using the scanning electron microscope.