In this paper, we report anatase and rutile titanium oxide (TiO2) nanoparticulate thin films fabricated on silica and Indium Tin Oxide (ITO) substrates using femtosecond pulsed laser deposition (fs-PLD). Depositions were carried-out at substrate temperatures of 25 °C, 400 °C and 600 °C from anatase and rutile phase target materials. Effect of substrate temperature on the surface morphology, microstructural, optical, and electrical properties of these films were systematically investigated by using various range of measurements such as scanning electron microscopy, (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman spectroscopy, Ultraviolet–visible-near infrared (UV–Vis–NIR) spectroscopy, and Hall Effect measurements. It is observed that the TiO2 thin films surface are predominated with nanoparticulates of diameter less 35 nm, which constitute about ~ 70%; while the optical bandgaps and electrical resistivity decrease with increasing substrate temperature. A mixed-phase (anatase/rutile) TiO2 thin film was produced at a substrate temperature of 400 °C when samples are fabricated with anatase and rutile target materials. The results of this study indicate that the structural and crystallinity, optical, and electrical properties can be controlled by varying fs-PLD process parameters to prepare TiO2 thin films, which are suitable for applications in photovoltaics, solar cells, and photo-catalysis.
The photometric properties of an radio frequency (RF)-based sputtering plasma source were monitored through optical spectroscopy. The colour of the plasma source was deduced based on conventional chromaticity index analysis and it was compared to the direct spectral data plots of the emission peaks to investigate the possibility of characterising the plasma based on its specific colour and exploring the potential of defining a new method by which the plasma sputtering process can be addressed based on the plasma colour parameters. The intention of this investigation is to evaluate the possibility of simplifying the monitoring and assessment of the sputtering process for applied scientists operating plasma sputter deposition systems. We demonstrate a viable potential for this technique in terms of providing information regarding the stability of the plasma, chamber pressure, and plasma power; however, further work is underway to verify and assess a relationship between the quality of the thin film coating and the colour characteristics of the deposition plasma. Here, we only focus on the feasibility of such an approach and demonstrate interesting observations. We observed a linear relationship between the colour functions and the plasma power, while the stability of the sputtering plasma can be assessed based on the plasma colour functions. The colour functions also follow a unique pattern when the working gas pressure is increased.
The spectral properties and colour functions of a radio frequency (RF)-based sputtering plasma source was monitored during consecutive sputter deposition of zinc doped indium oxide (IZO) thin films under argon and argon/hydrogen mix. The effect of target exposure to the hydrogen gas on charge density/mobility and spectral transmittance of the deposited films was investigated. We demonstrate that consecutive exposure to the hydrogen gas during the deposition process progressively affects the properties of thin films with a certain degree of continuous improvement in electrical conductivity while demonstrating that reverting to only argon from argon/ hydrogen mix follows a complex pathway, which has not been reported previously in such detail to our knowledge. We then demonstrate that this effect can be used to prepare highly conductive zinc oxide thin films without indium presence and as such eliminating the need for the expensive indium addition. We shall demonstrate that complexity observed in emission spectra can be simply identified by monitoring the colour of the plasma through its colour functions, making this technique a simple real-time monitoring method for the deposition process.
We investigate the complexity of the reactive sputtering of highly conductive zinc oxide thin films in the presence of hydrogen at room temperature. We report on the importance of precise geometric positioning of the substrate with respect to the magnetron to achieve maximum conductivity. We examine the electrical properties of the deposited thins films based on their position on the substrate holder relative to the magnetron. By considering early reports by other researchers on the angular dependency of plasma parameters and the effect of hydrogen doping on electric and magnetic properties of hydrogen-doped zinc oxide, we propose a hypothesis on the possibility of such properties resulting in the observations presented in this report pending further tests to verify this hypothesis. Overall, in this report we present the guide by which highly conductive zinc oxide thin film coatings can be prepared via RF sputtering with hydrogen presence along with argon as the sputtering gas.
The spectral emission data from the plasma glow of various sputtering targets containing indium oxide, zinc oxide, and tin oxide were obtained. The plasma was generated at various power and chamber pressures. These spectral data were then converted into two-dimensional arrays by implementing a basic array-reshaping technique and a more complex procedure utilizing an unsupervised deep-learning technique, known as the self-organizing-maps method. The two-dimensional images obtained from each single-emission spectrum of the plasma mimic an image that can then be used to train a convolutional neural network model capable of predicting certain plasma features, such as impurity levels in the sputtering target, working gas composition, plasma power, and chamber pressure during the machine operation. We show that our single-array-to-2D-array conversion technique, coupled with deep-learning techniques and computer vision, can achieve high predictive accuracy and can, therefore, be fundamental to the construction of a sputtering system’s digital twin.
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