Crystalline materials are produced in complex high-temperature processes involving a large variety of physical phenomena from heat transfer to fluid dynamics. We are working on a new generation of multiphysical models for these processes within the NEMOCRYS project funded by a Starting Grant from the European Research Council (ERC). The expected paradigm change in the way how we observe, describe and develop crystal growth processes will minimize the necessary experimental cycles and open new horizons for scientific analysis as well as for smart process control using artificial intelligence and other modern technologies.

We are developing a series of unique crystal growth setups for model materials to enable low working temperatures, relaxed vacuum-sealing requirements and hence an easy experimental access for various measurement techniques. The obtained in-situ measurement data are used to develop and validate multiphysical models, which are then applied for various crystal growth processes both on research and industrial scales. Furthermore, model experiments are employed to optimize the techniques for in-situ observation as well as to build a new basis for model benchmarking and for big data concepts in crystal growth.

Artificial intelligence (AI) based on artificial neural networks (ANN) can significantly reduce costs and shorten time for development of novel crystalline materials and crystal growth processes. The main reason for using ANNs is to quickly extract patterns and relationships in crystal growth data sets that are too complex to be noticed by other numerical techniques. The fast forecasting is crucial for the process control where in situ measurements of process parameters are not feasible.

The IKZ used static ANNs for parameter optimization in the magnetic driven growth of VGF-GaAs and DS-Si. A recent research topic was the application of dynamic neural networks for real-time prediction in the transient VGF-GaAs crystal growth process. For example, temperature distributions in the furnace as well as the position of the crystallization front during the growth can be quickly predicted. The AI application to other crystal growth topics is currently in progress. 

Crystal Growth is a kinetic process where atoms are integrated in a crystal lattice. This takes place for growth of bulk crystals and for deposition of crystalline layers. Understanding the kinetic processes is of great importance for the structure and the properties of the material as well as for the process engineering. Numerical calculations provide a deeper knowledge in concjunction with specific characterization methods such as e.g.  transmission electron microscopy (TEM) or atomic force microscopy (AFM). 

Homoepitaxy of Ga₂O₃  is investigated with a spefically developed kinetic Monte Carlo (KMC) method: What is the impact of process parameters on growth rate and surface morphology,  what are the dominating kinetic prcoesses?
Furthermore, phase field models are topic of our research, both for the melt/crystal phase transition and for epitaxial growth. We are developing a specific phase field model for the homoepitaxy of Ga₂O₃ based on the results of the computation with the KMC model.

Subject of the work are furnaces and processes for crystal growth and also for investigations of the finished crystals. Above all, as numerical tools commercially available software is used, both especially on a crystal growing process
tailored, as well as programs with a very wide diversified physical-technical applicability. The numerical models are two- or three-dimensional and simulate the growth in most cases of bulk crystals. The focus is on field distributions of temperature, flow velocity and thermal stresses.

The Czochralski growth of NdScO₃ single crystals along the [110] direction is analyzed numerically with regard to the influence of optical absorption on the shape of the phase boundary between crystal and melt and the formation of thermoelastic stresses. After the axi-symmetric calculation of temperature and flow field in the growth furnace the three-dimensional analysis of the stresses is performed at which the orthorhombic anisotropy of thermal expansion and elasticity is taken into account.