The ability to generate 3D angiogenesis models is central for tissue engineering and drug screening applications. However, existing bio-fabrication technologies have yet to attain precise guidance of capillary networks in 3D. Here, we present our latest results in fabricating capillary networks using a novel laser-assisted bioprinting technique named Laser Induced Side Transfer (LIST). We found that LIST-printed human umbilical vein endothelial cells (HUVECs) present negligible loss of viability and maintain their abilities to migrate, proliferate and form intercellular junctions. Furthermore, we showed that LIST enabled the formation of capillary-like networks in 3D with high spatial precision (50 μm) over a large volume (1 cm3). Those networks were validated as angiogenesis assays for pro- and anti-angiogenic compounds. LIST could be widely adapted for applications requiring multiscale bioprinting capabilities, like the development of 3D drug screening models and artificial tissues.
The effect of the laser and the optomechanical parameters in the micromachining process of the complex geometry is the challenging part in the manufacturing industry due to wide range of materials. There are limited ways to find the best process parameters for machining and texturing with specific depth, thickness and roughness. The COMSOL software was used to model all the laser parameters like laser power, sampling rate, and optomechanical parameters like pulse overlap. Presented simulation demonstrates the roughness, depth and thickness of machined path. In addition, from the simulation point of view, the laser and optomechanical parameters can be optimized for the specific depth and thickness. To validate the numerical model, experiments are conducted for different process parameters by changing the laser power, varying the sampling rate of the laser and data acquisition card, changing the pulse overlap and the results are tabulated. Also the same input parameters are given to numerical simulation and the results are in good agreement with experimental outcomes. In conclusion, the simulated model can be used to estimate the effect of the process parameters before the machining. So that the presented model has the control over the machined surface quality and the process can be optimized by giving different material properties in the simulation.
Laser micro machining is one of the micro manufacturing processes. Since it has wide range of applications in Microelectronics, medical device, aerospace etc., the accuracy of the process is the most significant factor. In this study, the challenges and corresponding possible solutions that are encountered in machining complex geometries are addressed. Furthermore, the effect of process parameters on the overall quality of the manufacturing are discussed. The paper proposes mathematical function based and image processing based algorithms to find the machining coordinates. The former calculates the first and second derivatives of the functions to find the essential coordinates and the latter converts pixels of the image into coordinates. Achieving required overlap is one of the difficulty in the curved shapes, which can be solved by using both the algorithms. However, the function-based approach is more efficient as the image processing approach depends on the image resolution. Lower resolution results in reduction in smoothness of the extracted coordinates and higher resolution leads to increased computational cost. By changing the different laser parameters such as laser power and mechanical parameters like sampling rate of data acquisition card; different roughness, depth and overlaps can be attained. The study demonstrates precision micromachining and it establishes optimal relation between the process parameters and quality of the machined surface.
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