Seungwu Han

Seoul National University of Science and Technology — South Korea

Engineering · Physical Sciences

63h-index16.4kcitations305works9.32yr avg
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Research Topics

Semiconductor materials and devices(46), Electronic and Structural Properties of Oxides(44), Machine Learning in Materials Science(40), Graphene research and applications(38), Carbon Nanotubes in Composites(35)

Publications305 total

Atomistic Insights into Cu/Amorphous-Ta <sub> <i>x</i> </sub> N Interfacial Adhesion via Machine Learning Interatomic Potentials: Effects of Stoichiometry and Interface Construction
ACS Applied Electronic Materials·2025
Author response for "Atomistic insights into hydrogen migration in IGZO from machine-learning interatomic potential: linking atomic diffusion to device performance"
2025
A Computational Study for Screening High-Selectivity Inhibitors in Area-Selective Atomic Layer Deposition on Amorphous Surfaces
arXiv (Cornell University)·2025Open Access
Neural network-driven molecular insights into alkaline wet etching of GaN: toward atomistic precision in nanostructure fabrication
npj Computational Materials·2025Open Access
Optimizing Cross-Domain Transfer for Universal Machine Learning Interatomic Potentials
ArXiv.org·2025· 1 citedOpen Access
Author response for "Atomistic insights into hydrogen migration in IGZO from machine-learning interatomic potential: linking atomic diffusion to device performance"
2025
Are diffusion models ready for materials discovery in unexplored chemical space?
arXiv (Cornell University)·2025Open Access
Unveiling Defect Motifs in Amorphous GeSe Using Machine Learning Interatomic Potentials
ACS Applied Materials & Interfaces·2025· 1 cited
Discovery of oxide Li-conducting electrolytes in uncharted chemical space via topology-constrained crystal structure prediction
arXiv (Cornell University)·2025Open Access
Atomistic Insights into Cu/amorphous-Ta$_x$N Interfacial Adhesion via Machine Learning Interatomic Potentials: Effects of Stoichiometry and Interface Construction
arXiv (Cornell University)·2025Open Access
Etching-to-deposition transition in SiO2/Si <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si206.svg" display="inline" id="d1e1145"> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>3</mml:mn> </mml:mrow> </mml:msub> </mml:math> N <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si207.svg" display="inline" id="d1e1153"> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:math> using CH <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si110.svg" display="inline" id="d1e1161"> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>x</mml:mi> </mml:mrow> </mml:msub> </mml:math> F <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si111.svg" display="inline" id="d1e1170"> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>y</mml:mi> </mml:mrow> </mml:msub> </mml:math> ion-based plasma etching: An atomistic study with neural network potentials
Applied Surface Science·2025
Etching-to-deposition transition in SiO$_2$/Si$_3$N$_4$ using CH$_x$F$_y$ ion-based plasma etching: An atomistic study with neural network potentials
arXiv (Cornell University)·2025Open Access
Electronic structures of crystalline and amorphous GeSe and GeSbTe compounds using machine learning empirical pseudopotentials
APL Machine Learning·2025· 1 citedOpen Access
An efficient forgetting-aware fine-tuning framework for pretrained universal machine-learning interatomic potentials
arXiv (Cornell University)·2025Open Access
Atomistic simulation of HF diffusion on ammonium fluorosilicate surface using neural network potential
Modelling and Simulation in Materials Science and Engineering·2025· 1 cited
Author response for "Application of pretrained universal machine-learning interatomic potential for physicochemical simulation of liquid electrolytes in Li-ion battery"
2025
Electronic structures of crystalline and amorphous GeSe and GeSbTe compounds using machine learning empirical pseudopotentials
arXiv (Cornell University)·2025Open Access
Nonmelting Disordering Facilitated by Electron Delocalization
ACS Nano·2025
Application of pretrained universal machine-learning interatomic potential for physicochemical simulation of liquid electrolytes in Li-ion battery
arXiv (Cornell University)·2025· 1 citedOpen Access
Etching-to-Deposition Transition in Sio2/Si3n4 Using Chxfy Ion-Based Plasma Etching: An Atomistic Study with Neural Network Potentials
SSRN Electronic Journal·2025Open Access
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Frequent Co-authors

Cheol Seong Hwang(9), Joohee Lee(7), David J. Srolovitz(6), Graeme J. Ackland(6), Bora Lee(5), Sang Ho Jeon(5), Ho Won Jang(5), Youngho Kang(5), Mikhail I. Mendelev(4), Ki Tae Nam(4), Hyo‐Shin Ahn(4), Kye Yeop Kim(4), Bae Ho Park(3), Soo Young Kim(3), Seong Keun Kim(3), Sang‐Young Lee(3), Jaichan Lee(3), Choong‐Ki Lee(3), Eunae Cho(3), Kanghoon Yim(3)