Tomography of 3D-Printed Lattice Structured Aluminum-Silicon Alloy and Its Deformation.

Additive manufactured light components are desirable for airspace and automobile applications where failure resistance under contact is important. To date, understanding the nature of subsurface damage in contact is still lacking. In this research, we investigated 3D-printed aluminum-silicon (Al-Si) alloys in the lattice structure under a rolling contact condition. Using the microtomography technique, we were able to construct a 3D image of the lattice structure being plastically deformed. Finite element analysis was conducted about the strain and stress on struts of different dimensions. Results showed that morphology dominated the deformation. The significant factors affecting the deformation were the strut aspect ratio, and their relative diameter. When the aspect ratio of a strut is smaller than 0.5, the plastic deformation is distributed in the subsurface region and when it is larger than 0.5, the deformation concentrates on the top layer of struts. This research indicates that the dimensional parameters of lattice structures can be designed for optimization to achieve higher resistance to deformation.

Investigating the effects of vacancies on self-diffusion in silicon clusters using classical molecular dynamics.

Due to recent advances in the field of microelectronics, the growth in microelectronics applications, and the exponentially increasing demand for microelectronic devices in the power sector, it is important to study the behavior of silicon at the nanoscale, given that nanoclusters of silicon could be used to design a new kind of lithium-ion batteries with strongly enhanced performance. Here, molecular dynamics was employed to calculate the self-diffusion coefficients of silicon clusters at room temperature and at a temperature approaching the melting point of silicon, complementing experimental efforts in this field. Silicon clusters of the same spherical geometry and size but with different vacancy fractions were studied using molecular dynamics using the Tersoff potential in order to estimate phase changes and self-diffusion coefficients. At 300 K, the self-diffusion coefficient was found to vary non-monotonically: the self-diffusion coefficient at a vacancy fraction of 7.5% is half than the vacancy at a fraction of 0%, while the self-diffusion coefficient at a vacancy fraction of 20% is two orders of magnitude larger than that at a vacancy fraction of 0%. However, there is only a marginal monotonic increase in the self-diffusion coefficient values with vacancy fraction at 2000 K. The results of this investigation of vacancy-mediated self-diffusion could aid attempts to improve diffusion control, which is crucial to nanocluster applications in various devices, and the results also provide insight into how the temperature, energy, pressure, and phase changes of the silicon clusters depend on vacancy fraction. This may ultimately allow the design and selection of materials for thermoelectric and optoelectronic devices and thermal transducers to be optimized. Our results also indicated that the findings we obtained for the clusters are independent of the particular random vacancy distribution considered and the heating rate applied to the clusters. Graphical Abstract Silicon nanoparticles (SNP) are among the best options to choose from for the design of devices for renewable energies; SNP based material performance can be effectively tailored by controling the vacancy, temperature and other properties of the SNP.