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Understanding the nature of grain boundaries is a prerequisite for fabricating high-performance superconducting bulks and wires. For iron-based superconductors [e.g. Ba(Fe,Co)[Formula: see text]As[Formula: see text], Fe(Se,Te), and NdFeAs(O,F)], the dependence of the critical current density [Formula: see text] on misorientation angle ([Formula: see text]) has been explored on [001]-tilt grain boundaries, but no data for other types of orientations have been reported. Here, we report on the structural and transport properties of Fe(Se,Te) grown on CeO[Formula: see text]-buffered symmetric [010]-tilt roof-type SrTiO[Formula: see text] bicrystal substrates by pulsed laser deposition. X-ray diffraction and transmission electron microscopy revealed that [Formula: see text] of Fe(Se,Te) was smaller whereas [Formula: see text] of CeO[Formula: see text] was larger than that of the substrate. The difference in [Formula: see text] between the CeO[Formula: see text] buffer layer and the substrate is getting larger with increasing [Formula: see text]. For [Formula: see text] of the substrates, [Formula: see text] of Fe(Se,Te) was zero, whereas [Formula: see text] of CeO[Formula: see text] was continuously increasing. The inclined growth of CeO[Formula: see text] can be explained by the geometrical coherency model. The [Formula: see text]-axis growth of Fe(Se,Te) for [Formula: see text] of the substrates is due to the domain matching epitaxy on (221) planes of CeO[Formula: see text]. Electrical transport measurements confirmed no reduction of inter-grain [Formula: see text] for [Formula: see text], indicative of strong coupling between the grains.

Definitive Screening Design (DSD) is a powerful design of experiment technique employed to find significant factors (parameters) and optimize the factor levels in many experiments of different fields. However, making its design and analyzing the obtained results usually requires expensive software or advance programming knowledge. Therefore, the authors of this work developed a web application, called “DSDApp”, with which users can make designs and analyze the results of DSD without statistical and programming efforts. DSDApp can generate DSD tables, make second-order models, and optimize factor levels to obtain max/min/target output values. Corresponding authors: Ryoichiro Hayasaka, long.hayasaka.6832@gmail.com Pablo Cayado, pablo.cayado@unige.ch