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Uniform distribution of carbon nanotubes (CNTs) in metal matrix during additive manufacturing of nanocomposites is always a challenge since the CNTs tend to aggregate in the molten pool. In this study, Multiwall carbon nanotubes (MWNTs) were separated and distributed uniformly into iron matrix by laser sintering process. MWNTs and iron powders were mixed together by magnetic stir, coated on steel 4140 surface, followed by laser sintering. Due to the fast heating and cooling rate, the CNTs are evenly distributed in the metal matrix. The temperature field was calculated by multiphysics simulation considering size effects, including size dependent melting temperature, thermal conductivity, and heat capacity. The SEM, TEM, and XRD were used to understand the laser sintering of CNT integrated nanocomposites. The results proved the feasibility of this technique to synthesize MWNTS integrated metal matrix nanocomposites. V

A finite element model is developed to predict the chip formation and phase transformation in orthogonal machining of hardened AISI 52100 steel (62HRC) using Polycristalline Cubic Boron Nitride (PCBN) tools. The model mainly includes a chip separation criterion based on critical equivalent plastic strain; a Coulomb's law for the friction at the tool/chip interface; a material constitutive relation of velocity-modified temperature; a thermal analysis incorporating the heat dissipated from inelastic deformation energy and friction; and an annealing effect model, in which the work hardening effect may be lost or re-accumulate depending on material temperature. This fully coupled thermalmechanical finite element analysis accurately simulates the formation of segmental chips and predicts the phase transformation on the chips, as verified by experiment. It is found that high temperatures around the secondary shear zone causes fast re-austenitization and martensite transformation, while other parts of the chips retain the original tempered martensitic structure.

Laser-induced photo-chemical synthesis of SnO2 nanotubes has been demonstrated by employing a nanoporous polycarbonate membrane as a template. The SnO2 nanotube diameter can be controlled by the nanoporous template while the nanotube length can be tuned by laser parameters and reaction duration. The microstructure characterization of the nanotubes indicates that they consist of mesoporous structures with sub 5 nm size nanocrystals connected by the twinning structure. The application of SnO2 nanotubes as an anode material in lithium ion batteries has also been explored, and they exhibited high capacity and excellent cyclic stability. The laser based emerging technique for scalable production of crystalline metal oxide nanotubes in a matter of seconds is remarkable. The compliance of the laser based technique with the existing technologies would lead to mass production of novel nanomaterials that would be suitable for several emerging applications.

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It is well known that there is a large variance associated with fatigue life. However, in literature little is found on the relationship between manufacturing processes and fatigue variance of the manufactured components. In this research, the influence of machining processes on the fatigue variance of the machined Ti 6Al-4V samples is studied experimentally. The impact is evaluated by comparing the safety ratios of face-turned samples with those of ground samples. The safety ratio is defined as the average fatigue life over the fatigue life with a reliability of 95%. In the computation, it is assumed that fatigue life follows Weibull distribution. Two sets of faced samples and two sets of ground samples are tested for bending fatigue. The test is under constant amplitude in high cycle fatigue regime under room temperature. The results show that the safety ratios of face-turned samples are significantly smaller than are those of ground samples. Consequently, it is suggested that fatigue life variance be considered as a new process capability. This capability serves as a basis in choosing manufacturing processes for making fatigue critical products such as aircraft. Another finding is the positive correlation between the residual stress variation and fatigue life variation. This correlation suggests that a better understanding and prediction of residual stress lead to a better prediction of fatigue life.