‪Seung-Hyun Victor Oh‬ - ‪Google Acadêmico‬

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	Todos	Desde 2019
Citações	16	16
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Coautores

Woohyun HwangPostdoctoral Research Fellow, Yonsei UniversityE-mail confirmado em yonsei.ac.kr
Kwangrae KimUniversity of Texas at AustinE-mail confirmado em utexas.edu
Ji-Hwan LeeYonsei UniversityE-mail confirmado em yonsei.ac.kr
Giyeok LeeDepartment of Materials Science and Engineering, Yonsei UniversityE-mail confirmado em yonsei.ac.kr

Seung-Hyun Victor Oh

Seung-Hyun Victor Oh

YONSEI University , Seoul, Korea

E-mail confirmado em yonsei.ac.kr

Machine Learning


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Using Feature‐Assisted Machine Learning Algorithms to Boost Polarity in Lead‐Free Multicomponent Niobate Alloys for High‐Performance Ferroelectrics SHV Oh, W Hwang, K Kim, JH Lee, A Soon Advanced Science 9 (13), 2104569, 2022	13	2022
Exploring anharmonic lattice dynamics and dielectric relations in niobate perovskites from first-principles self-consistent phonon calculations K Kim, W Hwang, SHV Oh, A Soon npj Computational Materials 9 (1), 154, 2023	3	2023
Recalibrating the Experimentally Derived Structure of the Metastable Surface Oxide on Copper via Machine Learning-Accelerated In Silico Global Optimization HJ Kim, G Lee, SHV Oh, C Stampfl, A Soon ACS nano, 2024		2024
Insights into Enhanced Antiferroelectricity in Doped-Niobate Perovskites for High Energy-Storage Density Applications Through Data-Informed In-Silico Experiments W Hwang, K Kim, SH Oh, A Soon Available at SSRN 4712614, 0

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