The field of nanotechnology, biotechnology and microelectronics are mostly characterized by coupled physical and chemical phenomena that evolve at different length and time scales thus requiring the need of a multiscale modelling approach.
Thin film deposition is a key process in the semiconductor manufacturing sector that is widely used to deposit films mounted on portable electronic devices. For the device to work properly, key properties such as the surface roughness and thickness of the film must meet certain criteria. In the industrial practice, the production of thin films is currently operated empirically, without a deep knowledge of the underlying dynamics. Therefore, the development of efficient control strategies for thin film deposition is needed to satisfy the increasingly stringent requirements in the semiconductor manufacturing sector.
However, a few obstacles hinder the progress in this field:
- development of fundamental mathematical models describing the system for optimization and control purposes
- lack of practical in-situ sensors that provide real-time measurements for online control
- uncertainties in the deposition process that are not captured by the prevalent, nominal multiscale models
Our research in this area aims to develop efficient techniques that improve the controllability of multiscale process systems under limited availability of on-line measurements and uncertainty in the physical parameters.
Another research avenue that has been investigated by group in multiscale systems is first-principles calculations for relevant catalytic systems. In this research, we have made use of Density Functional Theory (DFT) analysis to provide insight (from the modelling point of view) on the expected behaviour of certain reactions in the production of carbon nanotube and carbon filaments. Also, we study the effects of different metals and their supports in the production of these carbonaceous materials.