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Direct Metal Laser Sintering (DMLS) is one of the leading additive manufacturing processes, which produces complex metallic parts directly from the powder. One of the major problems of this rapid manufacturing process is an inhomogeneous temperature distribution, which leads to residual stress in the build part. Thus, temperature analyses must be performed, to better understand the temperature distribution and sintering behavior of the powder bed with a different laser recipe. In this study, a comprehensive three-dimensional numerical model was developed to understand the temperature distribution during direct metal laser sintering of AlSi10Mg alloy powder. The computer simulation was carried out in ANSYS 17.0 platform. Further, the effect of process parameters such as laser power and scan speed on the temperature distribution and sintering behavior were studied. From the simulation results, it was found that, when the laser power increased from 70 W to 190 W, the maximum temperature of the molten pool increased from 731 • C to 2672 • C, and the molten pool length changed from 0.286 mm to 2.167 mm. A reverse phenomenon was observed with an increase in scan speed. The sintering depth of the powder layer increases significantly from 0.061 mm to 0.872 mm with increasing the applied laser power, but decreased from 0.973 mm to 0.209 mm as a higher scan speed was applied. The developed model helps to optimize the powder layer thickness and minimize the wastage of excess powders during the sintering process.

In the present era, the laser additive manufacturing process is widely adopted in the manufacturing sector to produce near net shape components with minimum wastage of raw materials. Direct metal laser sintering (DMLS) is one of the laser additive manufacturing techniques which has received the most attention, as it builds the parts directly from metal or alloy powders. However, the quality of the components produced by DMLS has hindered its use on a larger scale. The process parameters in the DMLS process directly influence the quality of the building part. So, a better understanding of the influence of process parameters on build parts can provide insight to get high-quality products. In the present study, a three-dimensional transient heat transfer model was developed to simulate the temperature field and molten pool profile using the ansys 17.0 platform. The temperature distribution, melt pool dimension, solidification rate, cooling rate, and structural morphology are investigated with the variation of input laser energy. From the investigation, it was observed that the temperature of the powder bed and melt pool dimensions such as length, width, and depth increases with an increase in input laser energy. The cooling rate also increases with a decrease in laser energy input. Further, the developed model is validated to verify the accuracy and the simulated results are quite agreed with the analytical as well as experimental results.

Molecular dynamics simulations with second nearest neighbor modified embedded atom method have been performed on free-standing copper and nickel nanoclusters composed of 2048 atoms. Thermo-dynamical, dynamical and structural properties of the nanoclusters have been investigated during melting and crystallization process. Variation of potential energy, specific heat and self-diffusion coefficient of atoms during the phase transition have been used to determine the melting and crystallization points. Radial distribution function is used to characterize the structural changes of the nanoclusters. The melting and solidification profiles of both the nanoclusters showed hysteresis behavior, which is attributed to the undercooling effect during the solidification process. The melting temperature is about few hundreds of Kelvins higher than the crystallization temperature. The result shows that the melting and crystallization temperature of copper nanocluster are 1360[Formula: see text]K[Formula: see text][Formula: see text][Formula: see text]5[Formula: see text]K and 1090[Formula: see text]K[Formula: see text][Formula: see text][Formula: see text]5[Formula: see text]K, respectively, and those of the nickel nanoclusters are 1710[Formula: see text]K[Formula: see text][Formula: see text][Formula: see text]5[Formula: see text]K and 1390[Formula: see text]K[Formula: see text][Formula: see text][Formula: see text]5[Formula: see text]K, respectively.