Use of PVD sputtering thin-film technology for miniaturization of sensors, for direct application in mechanical components subjected to high external loadings, and evaluate the materials parameters exactly where they must be measured. Optimization of the process to improve the mechanical and electrical integrity of these devices, allowing their reliable and reproducible production and utilization.
The proposed solution is a software that can help to deposit the multilayer stacking with the appropriate conditions for achieving a reliable and reproducible product. The aim is the development of a software solution that can help deposit multilayer systems for a reliable and reproducible product by indicating the correct deposition conditions. This simple program, with the information about the required characteristics of the stacking layers (e.g. residual stress level, defects density, electrical characteristics, hardness, Young´s modulus), supplies the deposition conditions for the stacks fabrication.
1. Development and optimization of new materials in thin layers that can be integrated into a multilayer system with sensitive properties. Understand the contamination level between the interfaces and its effect on the interfacial delamination of the complete stack.
2. Development of a model to predict the thermomechanical reliability of the stack considering the materials' properties and target application. Correlation between the model output and the residual stress levels. Adapt deposition conditions to comply with the model output.
3. Experimental analysis on the thermoresistive properties of the functional layer and how they are affected by the multilayer approach integration.
4. Selection of a target application for service testing the multilayer system.
1. Multilayer system deposited on service substrates with mechanical integrity to support the external load, with electrical characteristics suitable for temperature assessment.
2. Methodology for surfaces and interfaces preparation and complete structural and chemical knowledge of the interfaces between the layers in the stacks.
3. Computation of normal and shear stresses in multilayer stacking and single layers, and machine learning model to predict Young's modulus and the yield strength.
4. Temperature measuring in real-time and data transmission during machining operations.