양재현 교수

We have investigated the effect of Fe nonstoichiometry on properties of the ${\text{Fe}}_{1+y}(\text{Te},\text{Se})$ superconductor system by means of resistivity, Hall coefficient, magnetic susceptibility, and specific-heat measurements. We find that the excess Fe at interstitial sites of the (Te, Se) layers not only suppresses superconductivity but also results in a weakly localized electronic state. We argue that these effects originate from the magnetic coupling between the excess Fe and the

It is necessary to find out whether there are metal defects on underground gas distribution pipelines without excavation in order to establish safety strategies for replacement or maintenance. The metal defects are classified into general corrosion, stress corrosion cracking, lamination, pits, and metal loss, which cause leak or partial damages to a gas pipeline. Therefore, it is required to develop an effective method in the form of an in-line inspection concept that could be implemented intern

We have synthesized polycrystalline samples and single crystals of Fe(Te1-xSx)y, and characterized their properties. Our results show that the solid solution of S in this system is limited, < 30%. We observed superconductivity at ~ 9 K in both polycrystalline samples Fe(Te1-xSx)y with 0< x <= 0.3 and 0.86 <= y <= 1.0, and single crystals with the composition Fe(Te0.9S0.1)0.91, consistent with the recent report of Tc ~ 10 K superconductivity in the FeTe1-xSx polycrystalline samples

Abstract Surveys are a cornerstone of research metrics and innovation studies, providing key indicators for research evaluation, policy design, and comparative analysis. Yet they increasingly face declining response rates, survey fatigue, and limited explanatory depth. Traditional surveys capture what firms do but provide restricted insight into why specific strategies are chosen. This study explores whether large language models (LLMs) can generate synthetic innovation survey responses that bot