Cast tungsten carbide is widely used to reinforce iron or steel substrate surface composites to meet the demands of harsh wear environments due to its extremely high hardness and excellent wettability with molten steel. Cast tungsten carbide particle/steel matrix surface composites have demonstrated great potential development in applications under the abrasive working condition. The thermal shock test was used to investigate the fatigue behavior of the composites fabricated by vacuum evaporative pattern casting technique at different temperatures. At elevated temperatures, the fatigue behavior of the composites was influenced by the oxidation of tungsten carbide, producing WO3. Thermodynamic calculations showed that the W2C in the tungsten carbide particle was oxidized at an initial temperature of approximately 570 °C. The relationship between oxidation and thermal fatigue crack growth was investigated, and the results suggested that oxidation would become more significant with increasing thermal shock temperature. These findings provide a valuable guide for understanding and designing particle/steel substrate surface composites.

Intrinsic size effects in nanoglass plasticity have been connected to the structural length scales imposed by the interfacial network, and control over this behavior is critical to designing amorphous alloys with improved mechanical response. In this paper, atomistic simulations are employed to probe strain delocalization in nanoglasses with explicit correlation to the interfacial characteristics and length scales of the amorphous grain structure. We show that strength is independent of grain size under certain conditions, but scales with the excess free volume and degree of short-range ordering in the interfaces. Structural homogenization upon annealing of the nanoglasses increases their strength toward the value of the bulk metallic glass; however, continued partitioning of strain to the interfacial regions inhibits the formation of a primary shear band. Intrinsic size effects in nanoglass plasticity thus originate from biased plastic strain accumulation within the interfacial regions, which will ultimately govern strain delocalization and homogenous flow in nanoglasses.

In this study, a niobium-reinforced hydroxyapatite (HA-Nb) coating was developed on cobalt–chromium (CoCr) alloy by plasma spraying with three varied levels, i.e., 10, 20, and 30% of weight percent (wt%) of Nb content. The corrosion behavior and biocompatibility of the samples were analyzed through electrochemical corrosion testing and cytotoxicity studies, respectively. The results of corrosion testing revealed that the HA coating increased the corrosion resistance of the CoCr alloy, and with the incremental increase of Nb reinforcement in HA, corrosion resistance was further enhanced. The HA-30Nb coating demonstrated the finest corrosion resistance with the highest Ecorr and lowest Icorr values, which were about one order of magnitude lower in comparison to the bare CoCr alloy. The surface hardness increased and the surface roughness decreased with the increase of Nb content in the coating. Wettability analysis revealed that HA and HA-Nb coatings had a hydrophilic nature. HA-Nb coatings demonstrated a significantly better cell proliferation than the CoCr alloy.

Protein-based materials are a powerful instrument for a new generation of biological materials, with many chemical and mechanical capabilities. Through the manipulation of DNA, researchers can design proteins at the molecular level, engineering a vast array of structural building blocks. However, our capability to rationally design and predict the properties of such materials is limited by the vastness of possible sequence space. Directed evolution has emerged as a powerful tool to improve biological systems through mutation and selection, presenting another avenue to produce novel protein materials. In this prospective review, we discuss the application of directed evolution for protein materials, reviewing current examples and developments that could facilitate the evolution of protein for material applications.

Several experiments and molecular dynamics calculations have reported anomalous mechanical behaviors of nanoporous materials that may be attributed to capillary effects. For example, nanoporous gold exhibits a tension–compression asymmetry in yield strength with the material being stronger in compression than tension. In addition, some molecular dynamics calculations have reported a spontaneous collapse of pores in nanoporous gold with nanometer-sized ligaments. Despite these perplexing observations, there are few theoretical models capable of shedding light on such capillary phenomena, particularly under general stress states. Here, we utilize a physics-based model to explore the implications of high surface energies on the mechanical response of dislocation-starved nanoporous materials subject to general stress states. For low stress triaxialities, we report an anomalous size effect and an anomalous temperature-dependence of dislocation-starved nanoporous materials with sufficiently large surface energies. Additionally, we provide an analytic criterion for spontaneous pore collapse in nanoporous materials with nanometer-sized ligaments.

Improvement of the performance of renewable electronic devices is a crucial point for the consolidation of this emerging technology. Herein, we develop a supercapacitor based on cellulose, carbon nanotubes, and ionic liquids. A conductive paper prepared by simple acid hydrolysis of cellulose and carboxylated carbon nanotubes was used as an electrode. A cellulose sponge impregnated with 1-n-butyl-3-methylimidazolium bis(trifluoromethane sulfonyl)imide was used as a separator/electrolyte. Electrochemical tests were performed in a two-electrode cell that presented a specific capacitance of 34.37 F/g when considered the active mass and 97.9% of capacitance retention after 5000 charge/discharge cycles.

Alloy design is critical to achieving the target performance of industrial components and products. In designing new alloys, there are multiple property requirements, including mechanical, environmental, and physical properties, as well as manufacturability and processability. Computational models and tools to predict properties from alloy compositions and to optimize compositions for multiple objectives are essential in enabling efficient, robust alloy design. Data-driven property models by machine learning (ML) are particularly useful in predicting physical properties with relatively simple dependence on composition, and in predicting complex properties that are too difficult for a physics-based model to achieve with desirable accuracy. In this article, we describe examples of ML applications to model coefficient of thermal expansion, creep and fatigue resistance in designing Ni-based superalloys, and optimization methodologies. We also discuss physics-based microstructure models that have been developed for optimizing heat-treatment conditions to achieve desired microstructures.

Robots and artificial machines have been captivating the public for centuries, depicted first as threats to humanity, then as subordinates and helpers. In the last decade, the booming exposure of humans to robots has fostered an increasing interest in soft robotics. By empowering robots with new physical properties, autonomous actuation, and sensing mechanisms, soft robots are making increasing impacts on areas such as health and medicine. At the same time, the public sympathy to robots is increasing. However, there is still a great need for innovation to push robotics toward more diverse applications. To overcome the major limitation of soft robots, which lies in their softness, strategies are being explored to combine the capabilities of soft robots with the performance of hard metallic ones by using composite materials in their structures. After reviewing the major specificities of hard and soft robots, paths to improve actuation speed, stress generation, self-sensing, and actuation will be proposed. Innovations in controlling systems, modeling, and simulation that will be required to use composite materials in robotics will be discussed. Finally, based on recently developed examples, the elements needed to progress toward a new form of artificial life will be described.