Here, we report on adding an important dimension to the fundamental understanding of the evolution of the thin film micro structure evolution. Thin films have gained broad attention in their applications for electro-optical devices, solar-cell technology, as well storage devices. Deep insights into fundamental functionalities can be realized via studying crystallization microstructure and formation processes of polycrystalline or epitaxial thin films. Besides the fundamental aspects, it is industrially important to minimize cost which intrinsically requires lower energy consumption at increasing performance which requires new approaches to thin film growth in general. Here, we present a state of the art sputtering technique that allows for time-resolved in situ studies of such thin film growth with a special focus on the crystallization via small angle scattering and X-ray diffraction. Focusing on the crystallization of the example material of BaTiO3, we demonstrate how a prototypical thin film forms and how detailed all phases of the structural evolution can be identified. The technique is shaped to enable a versatile approach for understanding and ultimately controlling a broad variety of growth processes, and more over it demonstrate how to in situ investigate the influence of single high temperature sputtering parameters on the film quality. It is shown that the whole evolution from nucleation, diffusion adsorption and grain growth to the crystallization can be observed during all stages of thin film growth as well as quantitatively as qualitatively. This can be used to optimize thin-film quality, efficiency and performance.

Thin-film  growth is a platform technique that allows the preparation of various undeveloped materials and enables the development of novel energy generation devices. Preferred phase formation, control of crystalline orientation and quality, defect concentration, and stoichiometry in thin films are important for obtaining thin films exhibiting desired physical and chemical properties. In particular, the control of crystalline phase formation by utilizing thin-film technology favors the preparation of undeveloped materials. In this study, thin-film growth of transition metal nitride and rare-earth metal boride was performed using remote plasma–assisted molecular beam epitaxy and hybrid physical–chemical vapor deposition techniques, and was successfully achieved by tuning the competition between thermodynamics and kinetics during vapor-phase thin-film growth. Growth conditions of high crystalline quality titanium nitride thin films and high phase purity ytterbium boride thin films were not thermodynamically favorable. Appropriate control of the contribution degree of thermodynamics and kinetics during vapor-phase thin-film growth is crucial for fabricating high phase purity and high crystalline quality thin films.

For the purpose of a deeper understanding of thin film growth, in the last two decades several groups developed models for simulation on the atomistic scale. Models using molecular dynamics as their simulation method already give results comparable to experiments, however statistical analysis of the simulations themselves are lacking so far, reasoned by the limits imposed by the computational power and parallelization that can only be used in lateral dimensions. With advancements of software and hardware, an increase in simulation speed by a factor of up to 10 can be reached. This allows either larger structures and/or more throughput of the simulations. The paper analyses the significance of increasing the structure size in lateral dimensions and also the repetition of simulations to gain more insights into the statistical fluctuation contained in the simulations and how well the coincidence with the experiment is. For that, glancing angle incidence deposition (GLAD) coatings are taken as an example. The results give important insights regarding the used interaction potential, the structure size and resulting important differences for the density, surface morphology, roughness and anisotropy. While larger structures naturally can reproduce the real world in more detail, the results show which structure sizes are needed for these aspects without wasting computational resources.