Strain and composition distributions within wurtzite InGaN/GaN layers are investigated by high-resolution reciprocal space mapping (RSM). We illustrate the potential of RSM to detect composition and strain gradients independently. This information is extracted from the elongation of broadened reciprocal lattice points (RLP) in asymmetric x-ray reflections. Three InxGa12xN/GaN (nominal x50.25) samples with layer thickness of 60, 120, and 240 nm, were grown in a commercial metal-organic chemical vapor deposition reactor. The RSMs around the (105) reflection show that the strain profile is nonuniform over depth in InGaN. The directions of ''pure'' strain relaxation in the reciprocal space, for a given In content (isocomposition lines), are calculated based on elastic theory. Comparison between these directions and measured distributions of the RLP shows that the relaxation process does not follow a specific isocomposition line. The In mole fraction (x) increases as the films relax. At the start of growth all the films have x;0.2 and are coherent to GaN. As they relax, x progressively increases towards the nominal value (0.25). Compositional gradients along the growth direction extracted from the RSM analysis are confirmed by complementary Rutherford backscattering measurements

Monte Carlo simulations of anomalous ion channeling in near-lattice-matched AlInN/GaN bilayers allow an accurate determination of the strain state of AlInN by Rutherford backscattering or channeling. Although these strain estimates agree well with x-ray diffraction (XRD) results, XRD composition estimates are shown to have limited accuracy, due to a possible deviation from Vegard's law, which we quantify for this alloy. As the InN fraction increases from 13% to 19%, the strain in AlInN films changes from tensile to compressive with lattice matching predicted to occur at [InN] = 17.1%.

A depth-resolved study of the optical and structural properties of wurtzite InGaN/GaN bilayers grown by metallorganic chemical vapor deposition on sapphire substrates is reported. Depth-resolved cathodoluminescence ͑CL͒ and Rutherford backscattering spectrometry ͑RBS͒ were used to gain an insight into the compositional profile of a 75-nm thick InGaN epilayer in the direction of growth. CL acquired at increasing electron energies reveals a peak shift of about 25 meV to the blue when the electron beam energy is increased from 0.5 to ϳ7 keV, and shows a small shift to lower energies between ϳ7 and 9 keV. For higher accelerating voltages the emission energy peak remains constant. This behavior can be well accounted for by a linear variation of In content over depth. Such an interpretation conforms to the In/Ga profile derived from RBS, where a linear decrease of the In mole fraction from the near surface ͑ϳ0.20͒ down to the near GaN/InGaN interface ͑ϳ0.14͒ region fits the random spectra very well. Furthermore, by measuring the tetragonal distortion at different depths, using RBS/channeling, it is shown that regions of higher In content also appear to be more relaxed. This result suggests that strain hinders the incorporation of In atoms in the InGaN lattice, and is the driving force for the compositional pulling effect in InGaN films.

We present an ultrafast neural network (NN) model, QLKNN, which predicts core tokamak transport heat and particle fluxes. QLKNN is a surrogate model based on a database of 300 million flux calculations of the quasilinear gyrokinetic transport model QuaLiKiz. The database covers a wide range of realistic tokamak core parameters. Physical features such as the existence of a critical gradient for the onset of turbulent transport were integrated into the neural network training methodology. We have coupled QLKNN to the tokamak modelling framework JINTRAC and rapid control-oriented tokamak transport solver RAPTOR. The coupled frameworks are demonstrated and validated through application to three JET shots covering a representative spread of H-mode operating space, predicting turbulent transport of energy and particles in the plasma core. JINTRAC-QLKNN and RAPTOR-QLKNN are able to accurately reproduce JINTRAC-QuaLiKiz T i,e and n e profiles, but 3 to 5 orders of magnitude faster. Simulations which take hours are reduced down to only a few tens of seconds. The discrepancy in the final source-driven predicted profiles between QLKNN and QuaLiKiz is on the order 1%-15%. Also the dynamic behaviour was well captured by QLKNN, with differences of only 4%-10% compared to JINTRAC-QuaLiKiz observed at mid-radius, for a study of density buildup following the L-H transition. Deployment of neural network surrogate models in multi-physics integrated tokamak modelling is a promising route towards enabling accurate and fast tokamak scenario optimization, Uncertainty Quantification, and control applications.

The authors present a detailed study of Al1−xInxN layers covering the whole composition range of 0.09<x<1. All layers were grown on GaN on Si(111) templates using metal-organic vapor phase epitaxy. For 0.13<x<0.32 samples grow fully strained and without phase separation. At higher In concentrations, the crystalline quality starts to deteriorate and a transition to three-dimensional growth is observed. A comparison of their experimental data with theoretically predicted phase diagrams reveals that biaxial strain increases the stability of the alloy.

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The main objective of this work is the preparation of decorative zirconium oxynitride, ZrOxNy, thin films by dc reactive magnetron sputtering. Film properties were analyzed as a function of the reactive gas flow and were correlated with the observed structural changes. Measurements showed a systematic decrease in the deposition rate with the increase of the reactive gas flow and revealed three distinct modes: (i) a metallic mode, (ii) a transition mode (subdivided into three zones), and (iii) an oxide mode. The measurements of target potential were also consistent with these changes, revealing a systematic increase from 314to337V. Structural characterization uncovered different behaviors within each of the different zones, with a strong dependence of film texture on the oxygen content. These structural changes were also confirmed by resistivity measurements, whose values ranged from 250to400μΩcm for low gas flows and up to 106μΩcm for the highest flow rates. Color measurements in the films revealed a change from bright yellow at low reactive gas flows to red brownish at intermediate flows and dark blue for the films prepared at the highest flows. Hardness measurements gave higher values for the region where larger grain sizes were found, showing that the grain growth hardening effect is one of the main parameters that can help explain the observed behavior. Also the peak intensity ratio and the residual stress states were found to be important factors for explaining this behavior.