Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551014
Pertenecen a esta colección Tesis y Trabajos de grado de los Doctorados correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Microstructural and mechanical characterization of laser surface textured Ti6Al4V coated by PVD for biomedical applications(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-10-01) Quintanar Abarca, Bryan Ivan; García López, Erika; mtyahinojosa, emipsanchez; Melo Máximo, Lizbeth; Uribe Lam, Esmeralda; Cedeño Viveros, Luis Daniel; Escuela de Ingeniería y Ciencias; Campus Estado de México; Melo Máximo, Dulce ViridianaThis document presents the PhD dissertation proposal for the nanotechnology program focused on the surface modification of Ti alloy using a Laser Surface Texturing (LST) method, followed by a thin film deposition by Physical Vapor Deposition technique in order to improve mechanical, tribological, and antibacterial properties for biomedical applications. The main challenge for this research is to develop a material with different additive manufacturing processes and create a thin film on a high roughness surface; during thin film coating is well known that polished and flat materials (with low roughness) are used to have better adhesion and obtain a correct deposition. Then using Laser Surface Texturing will create a surface with high roughness, which will be a complication for thin film deposition. A broad range of parameter modifications and depositions will be needed to obtain the best coating design possible. The main idea is to use Ti6Al4V as the substrate on which laser surface texturing will be done, after this process, a thin film coating of ZnO was deposited on the substrate using PVD, looking for an improvement of antibacterial properties, biocompatibility and enhance mechanical properties for biomedical applications. This proposal contemplates the use of different surface modification technologies, and the use of thin film deposition based on nanoparticles growth, which are some available resources that exist in “Tecnológico de Monterrey – Campus Estado de México” and “Campus Monterrey”. As future steps, there was considered an extra step, creating a microfluidic device capable of creating microencapsulation for drug delivery systems for adding at the top of the material created in this research. The microencapsulation device works with a technique called Electrospray and was fabricated during an international research stay at the Massachusetts Institute of Technology with the support of the Monterrey Tec – MIT program.
- A methodology for modeling multiscale multiphysics nature that bridges basic science with sustainable manufacturing technologies using human and Artificial intelligence(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-05-22) Estrada Diaz, Jorge Alfredo; Elías Zúñiga, Alex; emimmayorquin; Martínez Romero, Oscar; Palacios Pineda, Luis Manuel; Ruiz Huerta, Leopoldo; Escuela de Ingeniería y Ciencias; Campus Monterrey; Olvera Trejo, DanielThis dissertation deals with the modeling of multiscale multiphysics phenomena. These complex processes involve the interaction between physical occurrences of different nature, at different time and space scales, turning its description, prediction and control into a daunting task. Being pivotal technologies for the manufacturing of advanced materials, this work revolves around the complex technologies of Selective Laser Melting (SLM), electrospray, Ultrasonic Micro-Injection Molding (UMIM) and smart materials, i.e. Magneto-Rheological Elastomers (MRE). Modeling efforts are taken into action through classical yet powerful methodologies such as dimensional analysis and cutting-edge approaches such as fractal analysis and artificial intelligence, i.e., Artificial Neural Networks (ANNs) and Multiobjective Evolutionary Algorithms (MOEAs), with promising results that reflect on their ability to capture the intricate interplay of process parameters and material properties in these convoluted phenomena. Offering complementary benefits (attaining of meaningful physical insights and efficient handling computational processing operation and pattern identification in data, respectively) both approaches should be jointly exploited for handling multiscale multiphysics phenomena.