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The functional properties of devices based on perovskite oxides depend strongly on the growth modes that dramatically affect surface morphology and microstructure of the hetero-structured thin films. To achieve atomically flat surface morphology, which is usually a necessity for the high quality devices, understanding of the growth mechanism of heteroepitaxial thin film is indispensable. In this study, we explore heteroepitaxial growth kinetics of the SrRuO3 using intermittent growth scheme of pulsed laser epitaxy and ex-situ atomic force microscopy. Two significant variations in surface roughness during deposition of the first unit cell layer were observed from atomic force microscopy indicating the possible formation of the half unit cell of the SrRuO3 before the complete formation of the first unit cell. In addition, layer-by-layer growth mode dominated during the first two unit cell layer deposition of the SrRuO3 thin film. Our observation provides underlying growth mechanism of the heteroepitaxial SrRuO3 thin film on the SrTiO3 substrate during the initial growth of the thin film.
To visualize the topography of thin oxide films during growth, thereby enabling to study its growth behavior quasi real-time, we have designed and integrated an atomic force microscope (AFM) in a pulsed laser deposition (PLD) vacuum setup. The AFM sc
Transition metal oxide thin films show versatile electrical, magnetic, and thermal properties which can be tailored by deliberately introducing macroscopic grain boundaries via polycrystalline solids. In this study, we focus on the modification of th
We present results on growth of large area epitaxial ReS2 thin film both on c plane sapphire substrate and MoS2 template by pulsed laser deposition (PLD). Films tend to grow with (0001) ReS2 perpendicular to (0001) Al2O3 and (0001) ReS2 perpendicular
Materials informatics exploiting machine learning techniques, e.g., Bayesian optimization (BO), has the potential to offer high-throughput optimization of thin-film growth conditions through incremental updates of machine learning models in accordanc
Elemental defects in transition metal oxides is an important and intriguing subject that result in modifications in variety of physical properties including atomic and electronic structure, optical and magnetic properties. Understanding the formation