In this contribution, first synthesis of semiconducting ZnSiN 2 and ZnGeN 2 from solution is reported with supercritical ammonia as solvent and KNH 2 as ammonobasic mineralizer.T he reactions were conducted in custom-built highpressure autoclaves made of nickel-based superalloy.T he nitrides were characterized by powder X-ray diffractiona nd their crystal structures were refinedb yt he Rietveld method. ZnSiN 2 (a = 5.24637(4), b = 6.28025(5), c = 5.02228(4) , Z = 4, R wp = 0.0556) and isotypic ZnGeN 2 (a = 5.46677(10), b = 6.44640(12), c = 5.19080(10) , Z = 4, R wp = 0.0494) crystallize in the orthorhombic space group Pna2 1 (no. 33). The morphology and elemental composition of the nitrides were examined by electron microscopy and energy-dispersive X-ray spectroscopy (EDX). Well-definedsingle crystalswith adiameter up to 7 mmw ere grownb ya mmonothermal synthesis at temperatures between 870 and 1070 Ka nd pressures up to 230 MPa. Optical properties have been analyzed with diffuse reflectance measurements. The band gaps of ZnSiN 2 and ZnGeN 2 were determined to be 3.7 and 3.2 eV at room temperature, respectively.I ns itu X-ray measurements were performed to exemplarily investigate the crystallization mechanism of ZnGeN 2 .D issolution in ammonobasic supercritical ammonia between 570 and6 70 Kw as observed which is quite promising for the crystal growth of ternary nitrides under ammonothermalconditions.

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Thermal boundary conditions for numerical simulations of ammonothermal GaN crystal growth are investigated. A global heat transfer model that includes the furnace and its surroundings is presented, in which fluid flow and thermal field are treated as conjugate in order to fully account for convective heat transfer. The effects of laminar and turbulent flow are analyzed, as well as those of typically simultaneously present solids inside the autoclave (nutrient, baffle, and multiple seeds). This model uses heater powers as a boundary condition. Machine learning is applied to efficiently determine the power boundary conditions needed to obtain set temperatures at specified locations. Typical thermal losses are analyzed regarding their effects on the temperature distribution inside the autoclave and within the autoclave walls. This is of relevance because autoclave wall temperatures are a convenient choice for setting boundary conditions for simulations of reduced domain size. Based on the determined outer wall temperature distribution, a simplified model containing only the autoclave is also presented. The results are compared to those observed using heater-long fixed temperatures as boundary condition. Significant deviations are found especially in the upper zone of the autoclave due to the important role of heat losses through the autoclave head.

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