Investigation into the Performance of NiTi Shape Memory Alloy Wire Reinforced Sn-Bi Self-Healing Metal Matrix Composite.

Self-healing materials have the potential to create a paradigm shift in the life cycle design of engineered structures, by changing the relation between material damage and structural failure, affecting structures' lifetime, safety, and reliability. However, the knowledge of self-healing capabilities in metallic materials is still in its infancy compared to other material systems because of challenges in the synthesis of organized and complex structures. This paper presents a study of a metal matrix composite system that was synthesized with an off-eutectic Tin (Sn)-Bismuth (Bi) alloy matrix, reinforced with Nickel-Titanium (NiTi) shape memory alloy (SMA) wires. The ability to close cracks, recover bulk geometry, and regenerate strength upon the application of heat was investigated. NiTi wires were etched and coated in flux before being incorporated into the matrix to prevent disbonding with the matrix. Samples were subjected to large deformations in a three-point bending setup. Subsequent thermo-mechanical testing of the composites confirmed the materials' ability to restore their geometry and recover strength, without using any consumable components. Self-healing was accomplished through a combination of activation of the shape memory effect in the NiTi to recover the samples' original macroscopic geometry, closing cracks, and melting of the eutectic material in the matrix alloy, which resealed the cracks. Subsequent testing indicated a 92% strength recovery.

Tribological Performance of Graphite Nanoplatelets Reinforced Al and Al/Al2O3 Self-Lubricating Composites.

In the present work, the effect of graphite nanoplatelets (GNPs) on tribological properties of the aluminum (Al), and Al/alumina (Al2O3) composite are studied. GNPs are multilayer graphene sheets which were used as a solid lubricant material. Two sets of composites, Al/GNPs and Al/GNPs/Al2O3 with varying amounts of reinforcements, were synthesized by powder metallurgy that involves cold compaction followed by hot compaction. The hardness of the composites increased with the addition of GNPs and Al2O3. The Al/GNPs composite with 1 wt.% of GNPs (Al/1GNPs) showed a 20% increase in hardness whereas Al/GNPs/ Al2O3 composite with 1 wt.% GNPs and 2 wt.% Al2O3 (Al/1GNPs/2Al2O3) showed 27% increases in hardness compared to the pure Al. The coefficient of friction measured at 20 N was observed to be 22% and 53% lesser for Al/1GNPs and Al/1GNPs/2Al2O3, respectively, compared to corresponding alloys without graphene Al. The X-ray diffraction and scanning electron microscopy analysis revealed the presence of GNPs at the worn surface after the tribology tests. The wear rate was also reduced significantly. In comparison with pure Al, the Al/1GNPs and Al/1GNPs/2Al2O3 composites resulted in 5- and 20-times lesser wear rate, respectively. The addition of Al2O3 caused reduction in wear rate due to higher hardness and load carrying ability, whereas composites with more than 1 wt.% GNPs showed higher wear rate due to lower hardness and higher porosity. The Al/1GNPs/2Al2O3 composite exhibited the least coefficient of friction (0.2-0.25) and wear rate (1 × 10-6-4 × 10-6 mm3/N.m) compared to other GNPs and Al2O3 reinforced Al composites. The worn surfaces were further analyzed to understand the wear mechanism by Raman spectroscopy, transmission electron microscopy, and x-ray diffraction to detect the Al4C3 phase formation, chemical bonding, and defect formation in graphene.

Ball Milled Graphene Nano Additives for Enhancing Sliding Contact in Vegetable Oil.

Graphite nanoplatelets (GNPs) as an oil nano additive has gained importance to enhance the lubrication properties of renewable lubricants, such as vegetable oils. Using appropriately processed GNPs is necessary to gain the required tribological advantage. The present study investigated ball-milled GNPs, to understand the effect of GNPs concentration, and applied load on tribological behavior. Pin-on-disk tests were employed, to investigate the tribological performance of the nano-additive oil-based lubricant in the boundary lubrication regime. In order gain an understanding of the lubrication mechanism, Scanning Electron Microscope (SEM), Energy-Dispersive X-ray Spectroscopy (EDX), and Raman Spectroscopy were performed for characterization. The study found that there is a critical concentration of GNPs, below and above which a reduced wear rate is not sustained. It is found that the tribological enhancements at the optimum concentration of GNP in boundary lubrication condition are a result of reduced direct metal-metal contact area at the interface. This phenomenon, along with the reduced shear strength of the ball-milled GNPs, is indicated to reduce the formation of asperity junctions at the interface and enhance tribological properties of the nano-additive oil-based lubricant.

Predictive Analysis of Wettability of Al-Si Based Multiphase Alloys and Aluminum Matrix Composites by Machine Learning and Physical Modeling.

Wetting of multiphase alloys and their composites depends on multiple parameters, and these relationships are difficult to predict from first principles only. We study correlations between the composition, surface finish, and microstructure of Al-Si alloys (Si content 7-50%) and Al metal matrix composites (MMCs) with graphite (Gr), NiAl3, and SiC and the water contact angle (CA) experimentally, theoretically, and with machine learning (ML) techniques. Their surface properties were modified by mechanical abrasion, etching, and addition of alloying elements. An ML approach was developed to investigate correlations between the predictor variables (properties of the materials) and the CA. Theoretical models of wetting of rough surfaces (Wenzel, Cassie-Baxter, and their modifications) do not fully capture the CA, while ML models follow the experimental values. A full factorial design is utilized with combinations of all levels of the predictor factors (grit size, silicon percentage, droplet size, elapsed time, etching, reinforcing particles). To map the predictor variables to the response variables, 409 experimental data points were applied to train and test various supervised ML models, namely, regression, artificial neural network (ANN), chi-square automatic interaction detection (CHAID), extreme gradient boosting (XGBoost), and random forest. The correlations between the most significant factors and CA are explored through visualization techniques. The most accurately trained model shows a strong positive linear correlation (r > 0.9) between predicted and observed CA values in the test set, indicating the robustness of the model. The experimental measurements and artificial intelligence results demonstrate that CA increases following mechanically abrading the surface, etching, and adding Gr to the surface. The ML methods are promising to predict wetting properties and to provide a deeper understanding of the physical phenomena associated with the wettability of metallic alloys and their metal matrix composites.

Effect of Microstructure on Contact Angle and Corrosion of Ductile Iron: Iron-Graphite Composite.

Ductile iron samples with similar compositions and varying microstructures were uniformly abraded, and the effects of phase fractions (ferrite, pearlite, and graphite) on the apparent contact angle (with water) and corrosion characteristics of ductile iron were investigated. We also investigated the effect of droplet volume on the apparent contact angle of ductile iron. Irrespective of the droplet size, the ductile iron system followed the Wenzel model of wetting, and the contact angle increased with increasing droplet volume. The Wenzel and Cassie-Baxter contact angles were calculated, and the calculated results agreed well with the experimental results. It was experimentally proven that pearlite is more susceptible to corrosion than ferrite and graphite, and a higher portion of pearlite in the microstructure can be detrimental to the corrosion resistance of the material. Understanding the relationship between the microstructure, contact angle, and corrosion can be used to develop materials with higher contact angle and corrosion-resistant microstructures. Using metal pipes that have high contact angles is desirable because artificial coatings on metal pipes can degrade over time leading to high cost of replacement and contamination to water systems.

Role of Water Solidification Concepts in Designing Nano-Textured Anti-Icing Surfaces.

Creating anti-icing surfaces has proven to be a challenging task. With such a wide range of impacting parameters it is important to quantify ones with a large effect. Water solidification mechanisms play a fundamental role in designing anti-icing surfaces. In this Review Article, we will consider the effects of surface roughening on the mechanisms of nucleation and ice growth to show how surface roughening can be an alternative to overcome the limitations of icing of superhydrophobic coatings and surfaces. The results from various studies of anti-icing properties of superhydrophobic surfaces are reviewed and expanded to incorporate water solidification mechanisms to provide a more comprehensive approach to the design of anti-icing surfaces. The literature within this review shows that by applying the necessary roughness to either hydrophilic or hydrophobic surfaces and adjusting the surface topography, we can significantly suppress ice nucleation on various surfaces.

Mechanical, physical and tribological characterization of nano-cellulose fibers reinforced bio-epoxy composites: An attempt to fabricate and scale the 'Green' composite.

The development of bio-based composites is essential in order to protect the environment while enhancing energy efficiencies. In the present investigation, the plant-derived cellulose nano-fibers (CNFs)/bio-based epoxy composites were manufactured using the Liquid Composite Molding (LCM) process. More specifically, the CNFs with and without chemical modification were utilized in the composites. The curing kinetics of the prepared composites was studied using both the isothermal and dynamic Differential Scanning Calorimetry (DSC) methods. The microstructure as well as the mechanical and tribological properties were investigated on the cured composites in order to understand the structure-property correlations of the composites. The results indicated that the manufactured composites showed improved mechanical and tribological properties when compared to the pure epoxy samples. Furthermore, the chemically modified CNFs reinforced composites outperformed the untreated composites. The surface modification of the fibers improved the curing of the resin by reducing the activation energy, and led to an improvement in the mechanical properties. The CNFs/bio-based epoxy composites form uniform tribo-layer during sliding which minimizes the direct contact between surfaces, thus reducing both the friction and wear of the composites.

Synthesis and Quasi-Static Compressive Properties of Mg-AZ91D-Al2O3 Syntactic Foams.

Magnesium alloys have considerably lower density than the aluminum alloy matrices that are typically used in syntactic foams, allowing for greater specific energy absorption. Despite the potential advantages, few studies have reported the properties of magnesium alloy matrix syntactic foams. In this work, Al2O3 hollow particles of three different size ranges, 0.106-0.212 mm, 0.212-0.425 mm, and 0.425-0.500 mm were encapsulated in Mg-AZ91D by a sub-atmospheric pressure infiltration technique. It is shown that the peak strength, plateau strength and toughness of the foam increases with increasing hollow sphere wall thickness to diameter (t/D) ratio. Since t/D was found to increase with decreasing hollow sphere diameter, the foams produced with smaller spheres showed improved performance-specifically, higher energy absorption per unit weight. These foams show better performance than other metallic foams on a specific property basis.

Beyond Wenzel and Cassie-Baxter: second-order effects on the wetting of rough surfaces.

The Wenzel and Cassie-Baxter models are almost exclusively used to explain the contact angle dependence of the structure of rough and patterned solid surfaces. However, these two classical models do not always accurately predict the wetting properties of surfaces since they fail to capture the effect of many interactions occurring during wetting, including, for example, the effect of the disjoining pressure and of crystal microstructure, grains, and defects. We call such effects the second-order effects and present here a model showing how the disjoining pressure isotherm can affect wettability due to the formation of thin liquid films. We measure water contact angles on pairs of metallic surfaces with nominally the same Wenzel roughness obtained by abrasion and by chemical etching. These two methods of surface roughening result in different rough surface structure, thus leading to different values of the contact angle, which cannot be captured by the Wenzel- and Cassie-type models. The chemical and physical changes that occur on the stainless steel and aluminum alloy surfaces as a result of intergranular corrosion, along with selective intermetallic dissolution, lead to a surface roughness generated on the nano- and microscales.

Wetting transitions in underwater oleophobic surface of brass.

An oil droplet in water can be in the Cassie state (with water and/or air trapped between the solid and oil) with a high contact angle (top left) or in the Wenzel state (top right). Depending on the roughness of the brass substrate, both states with high (bottom left) and low (bottom right) contact angle are observed.

Metal matrix composites for sustainable lotus-effect surfaces.

The lotus effect involving roughness-induced superhydrophobicity is a way to design nonwetting, self-cleaning, omniphobic, icephobic, and antifouling surfaces. However, such surfaces require micropatterning, which is extremely vulnerable to even small wear rates. This limits the applicability of the lotus effects to situations when wear is practically absent. To design sustainable superhydrophobic surfaces, we suggest using metal matrix composites (MMCs) with hydrophobic reinforcement in the bulk of the material, rather than only at its surface. Such surfaces, if properly designed, provide roughness and heterogeneity needed for superhydrophobicity. In addition, they are sustainable, since when the surface layer is deteriorated and removed due to wear, hydrophobic reinforcement and roughness remains. We present a model and experimental data on wetting of MMCs. We also conducted selected experiments with graphite-reinforced MMCs and showed that the contact angle can be determined from the model. In order to decouple the effects of reinforcement and roughness, the experiments were conducted for initially smooth and etched matrix and composite materials.

Physical chemistry of self-organization and self-healing in metals.

Wear occurs at most solid surfaces that come in contact with other solid surfaces. While biological surfaces and tissues usually have the ability to repair minor wear damage, engineered self-healing materials only started to emerge recently. An example of a smart self-healing material is the material with imbedded microcapsules or microtubes, which rupture during crack propagation and release a healing agent that repairs the crack. Self-healing mechanisms are hierarchical in the sense that they involve interactions with different characteristic scale lengths. While traditional models of self-healing require equations with many degrees of freedom, taking into account the hierarchical organization allows us to reduce the number of equations to a few degrees of freedom. We discuss the conditions under which the self-healing occurs and provide a general theoretical framework and criteria for self-healing using the concept of multiscale organization of entropy and non-equilibrium thermodynamics. The example of a self-healed Al alloy reinforced with microtubes filled with Sn60Pb40 solder is discussed as a case study.