Real-time monitoring of plasma synthesis of functional materials by high power impulse magnetron sputtering and other PVD processes: towards a physics-constrained digital twin

Abstract

Plasma synthesis of thin films by physical vapour deposition (PVD) enables the creation of materials that drive significant innovations in modern life. High value manufacturing demand for tighter quality control and better resource utilisation can be met by a digital twin capable of modelling the deposition process in real time. Optical emission spectroscopy (OES) was combined with process parameters to monitor all stages of both high power impulse magnetron sputtering and conventional magnetron sputtering processes to provide a robust method of determining process repeatability and a reliable means of process control for quality assurance purposes. Strategies and physics-based models for the in-situ real-time monitoring of coating thickness, composition, crystallographic and morphological development for a CrAlYN/CrN nanoscale multilayer film were developed. Equivalents to the ion-to-neutral ratio and metal-to-nitrogen ratios at the substrates were derived from readily available parameters including the optical emission intensities of Cr I, N2 (C–B) and Ar I lines in combination with the plasma diffusivity coefficient obtained from the ratio of substrate and cathode current densities. These optically-derived equivalent parameters identified the deposition flux conditions which trigger the switch of dominant crystallographic texture from (111) to (220) observed in XRD pole figures and the development of coating morphology from faceted to dense for a range of magnetron magnetic field configurations. OES-based strategies were developed to monitor the progress of chamber evacuation, substrate cleaning and preventative chamber wall cleaning to support process optimisation and equipment utilisation. The work paves the way to implementation of machine learning protocols for monitoring and control of these and other processing activities, including coatings development and the use of alternative deposition techniques. The work provides essential elements for the creation of a digital twin of the PVD process to both monitor and predict process outcomes such as film thickness, texture and morphology in real time.