Modeling, simulation, dynamic optimization and control of a plasma assisted reactive evaporation process for preparation of Zinc Oxide (ZnO) thin films

• Autores: Asdrubal Antonio Ramirez Botero
• Directores de la Tesis: Razak Latifi (dir. tes.), Gerardo Gordillo (codir. tes.), Iván Darío Gil (dir. tes.)
• Lectura: En la Université de Lorraine ( Colombia ) en 2019
• Idioma: español
• Títulos paralelos:
  • Modélisation, simulation, optimisation et commande d’un procédé d’évaporation réactive assistée par plasma pour la production de couches minces d’oxyde de zinc
• Enlaces
  • Tesis en acceso abierto en: repositorio.unal.edu.co
• Resumen

  • In this work the modeling, simulation, dynamic optimization and control of a Plasma Assisted Reactive Evaporation process (PARE) for the deposition of Zinc Oxide (ZnO) thin films are proposed. Initially, a dimensional unsteady-state model was developed for the process, this model apply dynamic material balances to the process and accounting for diffusive and convective mass transfer, and bulk and surface reactions in order to establish the space-time evolution of the concentration of the species (O_2(g) , O_((g))^., O_((g))^-, 〖Zn〗_((g)), 〖Zn〗_((g))^+ and 〖ZnO〗_((g))) present throughout the reactor and compute the final film thickness. The case of study corresponds to a pilot reactor operated by the Semiconductor Materials and Solar Energy Research Group (SM and SE) of the Universidad Nacional de Colombia where the ZnO thin films are used for the fabrication of different kind of solar cells (inverted inorganic solar cells, organic solar cells and perovskite based solar cells). The equations are spatially discretized using finite difference methods and then implemented and solved in time using Matlab®. The simulation results are validated by means of COMSOL MULTIPHYSICS® which computes the same results; However, to complete the others objectives of the project it will keep using the finite difference method under Matlab® because it offers more flexibility in the perspective of dynamic optimization and control of PARE process. To corroborate the model, experimental measurements of ZnO film thickness were carried out using a thickness monitor on a pilot reactor designed and implemented by the Semiconductor Materials and Solar-Energy (SM and SE) Research Group at Universidad Nacional de Colombia. After 90 min of deposition time the simulated results and the experimental measurements exhibit a very good agreement, just around 20 nm discrepancy in the final thin film thickness hence showing the high accuracy of the developed model. The dynamic optimization problem is transformed into a non-linear programming (NLP) problem using the CVP method, i.e. the control variables are approximated by means of piecewise constant functions. It is then implemented within Matlab and solved using fmincon optimizer. Two different optimization problems are proposed., in the first problem Zn flow rate (V_(w,Zn)) is considered as control or manipulated variables u(t) and in the second problem both Zn flow rate (V_(w,Zn)) and Oxygen flow rate 〖(V〗_(w,O_2 )) are considered as manipulated variables. Quality constraints are established according to experimental studies that were performed in order to determinate the final product properties such as Transmittance, Resistivity, Film thickness and reactor parameters. Two optimization problems are solved taking as control variable the Zn flow rate and Oxygen flow rate in order to minimize batch time while some thin film desired properties (transmittance, resistivity and thickness) satisfy the defined constraints. The batch time was reduced in a 15% with respect to the current operating conditions used by the Semiconductor Materials and Solar Energy research Group. Finally, the optimal profiles of the Zn flow rate and Oxygen flow rate that were obtained in the optimization part were used to develop and simulated a regulatory control algorithm using the Simulink toolbox of Matlab®. The results obtained in the simulation of the control algorithm show that the designed controller has an appropriate performance by following the optimal flow trajectories and the ideal ratio of Oxygen and Zinc.