A study on the plasma-enhanced atomic layer deposition of amorphous inorganic oxides SiO and AlO on polypropylene (PP) was carried out with respect to growth taking place at the interface of the polymer substrate and the thin film employing in situ quartz-crystal microbalance (QCM) experiments. A model layer of spin-coated PP (scPP) was deposited on QCM crystals prior to depositions to allow a transfer of findings from QCM studies to industrially applied PP foil. The influence of precursor choice (trimethylaluminum (TMA) vs [3-(dimethylamino)propyl]-dimethyl aluminum (DMAD)) and of plasma pretreatment on the monitored QCM response was investigated. Furthermore, dyads of SiO/AlO, using different Al precursors for the AlO thin-film deposition, were investigated regarding their barrier performance. Although the growth of SiO and AlO from TMA on scPP is significantly hindered if no oxygen plasma pretreatment is applied to the scPP prior to depositions, the DMAD process was found to yield comparable AlO growth directly on scPP similar to that found on a bare QCM crystal. From this, the interface formed between the AlO and the PP substrate is suggested to be different for the two precursors TMA and DMAD due to different growth modes. Furthermore, the residual stress of the thin films influences the barrier properties of SiO/AlO dyads. Dyads composed of 5 nm AlO (DMAD) + 5 nm SiO exhibit an oxygen transmission rate (OTR) of 57.4 cm m day, which correlates with a barrier improvement factor of 24 against 5 when AlO from TMA is applied.

Thin films are ubiquitous in modern technology and highly useful in materials discovery and design. For achieving optimal extrinsic properties, their microstructure needs to be controlled in a multi-parameter space, which usually requires too high a number of experiments to map. Here, we propose to master thin film processing microstructure complexity, and to reduce the cost of microstructure design by joining combinatorial experimentation with generative deep learning models to extract synthesis-composition-microstructure relations. A generative machine learning approach using a conditional generative adversarial network predicts structure zone diagrams. We demonstrate that generative models provide a so far unseen level of quality of generated structure zone diagrams that can be applied for the optimization of chemical composition and processing parameters to achieve a desired microstructure.

Controlling the amorphous or crystalline state of multinary Cr-Mn-Fe-Co-Ni alloy nanoparticles with sizes in the range between ~1.7 nm and ~4.8 nm is achieved using three processing routes. Direct current sputtering from an alloy target in the ionic liquid 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide leads to amorphous nanoparticles as observed by high-resolution transmission electron microscopy. Crystalline nanoparticles can be achieved in situ in a transmission electron microscope by exposure to an electron beam, ex situ by heating in vacuum, or directly during synthesis by using a high-power impulse magnetron sputtering process. Growth of the nanoparticles with respect to the amorphous particles was observed. Furthermore, the crystal structure can be manipulated by the processing conditions. For example, a body-centered cubic structure is formed during in situ electron beam crystallization while longer ex situ annealing induces a face-centered cubic structure.

The properties of plasma-enhanced chemical vapour deposition (PECVD) coatings on polymer materials depend to some extent on the surface and material properties of the substrate. Here, isotactic polypropylene (PP) substrates are coated with silicon oxide (SiOx) films. Plasmas for the deposition of SiOx are energetic and oxidative due to the high amount of oxygen in the gas mixture. Residual stress measurements using single Si cantilever stress sensors showed that these coatings contain high compressive stress. To investigate the influence of the plasma and the coatings, residual stress, silicon organic (SiOCH) coatings with different thicknesses between the PP and the SiOx coating are used as a means to protect the substrate from the oxidative SiOx coating process. Pull-off tests are performed to analyse differences in the adhesion of these coating systems. It could be shown that the adhesion of the PECVD coatings on PP depends on the coatings’ residual stress. In a PP/SiOCH/SiOx-multilayer system the residual stress can be significantly reduced by increasing the thickness of the SiOCH coating, resulting in enhanced adhesion.

In thin film deposition processes, the deposition temperature is one of the crucial process parameters for obtaining films with desired properties. Usually the optimum deposition temperature is found by conducting several depositions sequentially in a time consuming process. This paper demonstrates a facile and rapid route of the simultaneous thin film deposition at six different deposition temperatures ranging from 100 to 1000 8C. Cuprite (Cu 2 O) was chosen for the study as this material is of interest for energy applications. The thin films are assessed for their crystallographic, microstructural, Raman scattering, and photoelectrochemical properties. The results show that the utilization of a step heater leads to the rapid optimization of thin film microstructures of an absorber material used in photoelectrochemistry. This results in a structure zone diagram for Cu 2 O. For a substrate temperature of 600 8C, an optimum between crystallinity and morphology occurs. 1 Introduction Thin film semiconductors in photoelectrochemical applications need to fulfil numerous properties. Whereas the search for new absorber and catalytic materials by combinatorial and high-throughput methods is currently addressed, the high-throughput optimization of deposition parameters, e.g., deposition temperature, however, is less developed. Finding optimal deposition conditions for even relatively simple metal oxide semiconductors for photoelectrochemical applications [1], usually requires careful evaluation of the different properties of a thin film like morphology, crystal structure, and interface formation [2][3][4][5]. In reactive magnetron sputtering, these properties can be tuned by deposition parameters like applied power, gas flow, substrate rotation, deposition geometry, total or partial gas pressure, and substrate temperature. These parameters are, however, interdependent. Attaining the desired metal oxide phase (e.g., competing phase formation between CuO and Cu 2 O) adds to the overall complexity of the problem of finding optimal deposition parameters [6]. Evaluating all possible optimization

No abstract

In this work, a fundamental investigation of an industrial (Cr,Al)N reactive high power pulsed magnetron sputtering (HPPMS) process is presented. The results will be used to improve the coating development for the addressed application, which is the tool coating for plastics processing industry. Substrate-oriented plasma diagnostics and deposition of the (Cr,Al)N coatings were performed for a variation of the HPPMS pulse frequency with values from f = 300 Hz to f = 2000 Hz at constant average power P = 2.5 kW and pulse length ton = 40 μs. The plasma was investigated using an oscilloscope, an intensified charge coupled device camera, phase-resolved optical emission spectroscopy, and an energy-dispersive mass spectrometer. The coating properties were determined by means of scanning electron microscopy, glow discharge optical emission spectroscopy, cantilever stress sensors, nanoindentation, and synchrotron X-ray diffraction. Regarding the plasma properties, it was found that the average energy within the plasma is nearly constant for the frequency variation. In contrast, the metal to gas ion flux ratio is changed from JM/JG = 0.51 to JM/JG = 0.10 for increasing frequency. Regarding the coating properties, a structure refinement as well as lower residual stresses, higher universal hardness, and a changing crystal orientation from (111) to (200) were observed at higher frequencies. By correlating the plasma and coating properties, it can be concluded that the change in the gas ion to metal ion flux ratio results in a competitive crystal growth of the film, which results in changing coating properties.

Correlatively employing density functional theory and experiments congregated around high power pulsed magnetron sputtering, a plasma-surface model for metastable Cr0.8Al0.2N (space group Fm3¯m) is developed. This plasma-surface model relates plasma energetics with film composition, crystal structure, mass density, stress state, and elastic properties. It is predicted that N Frenkel pairs form during Cr0.8Al0.2N growth due to high-energy ion irradiation, yielding a mass density of 5.69 g cm−3 at room temperature and Young's modulus of 358–130 GPa in the temperature range of 50–700 K for the stress-free state and about 150 GPa larger values for the compressive stress of 4 GPa. Our measurements are consistent with the quantum mechanical predictions within 5% for the mass density and 3% for Young's modulus. The hypothesis of a stress-induced Young's modulus change may at least in part explain the spread in the reported elasticity data ranging from 250 to 420 GPa.