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Jae-Hyun Yang

Korea Advanced Institute of Science and Technology · 材料科学

研究室紹介

Professor Jae-Hyun Yang's research lab specializes in condensed matter physics and materials science, with a primary focus on iron-based superconductors and defect engineering in functional materials. The lab investigates the electronic and magnetic properties of Fe-based superconductors, particularly the impact of nonstoichiometry, such as excess iron at interstitial sites, on superconducting behavior and electronic localization. Additionally, the lab explores innovative non-destructive evaluation techniques for industrial applications, including magnetic inspection methods for underground pipelines. Recent work also extends into computational social science, leveraging large language models to simulate and enhance survey-based innovation research.

iron-based superconductorsdefect engineeringnon-destructive evaluationmagnetic inspectioninnovation surveys

Research Overview

Papers
4
Total Citations
257
Papers (5y)
4
Primary Field
材料科学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
4total
2001
2008
2009
2026
Citations per year (5y)
257total
2001200820092026

Selected Papers

4
1
Article|251 citations·2009
Charge-carrier localization induced by excess Fe in the superconductorFe1+yTe1−xSex
T. J. Liu, Xianglin Ke, Bin Qian, Jin Hu, David Fobes, E. K. Vehstedt, Huy Pham, J. H. Yang, Minghu Fang, Leonard Spînu, P. Schiffer, Y. Liu
SJR Q1Physical Review BOA

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

Electronic, Optical and Magnetic MaterialsMaterials Science
2
Article|5 citations·2001
Detection of Metal Defects on Gas Distribution Pipeline by Remote Field Eddy Current (Rfec) Using Finite-Element Analysis
J. H. Yang, Yong Soo Yoon
Oil & Gas Science and Technology – Revue d’IFP Energies nouvellesOA

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

Mechanical EngineeringEngineering
3
Preprint|1 citations·2008
Superconductivity and Antiferromagnetism In Fe(Te1-xSx)y System
Minghu Fang, Bin Qian, Huy Pham, J. H. Yang, T. J. Liu, E. K. Vehstedt, Leonard Spînu, Zhiqiang Mao
ArXiv.orgOA

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

Electronic, Optical and Magnetic MaterialsMaterials Science
4
Article|0 citations·2026
LLMs as complementary tools for innovation surveys research: pattern replication and contextual relevance
Jae Hyung Park, J. H. Yang
SJR Q1ScientometricsOA

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

Sociology and Political ScienceSocial Sciences

Research Areas

Electronic, Optical and Magnetic MaterialsMechanical EngineeringSociology and Political Science

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