Changho Hong

activity

20202025

most citedTraining machine-learning potentials for crystal structure prediction using disordered structures

41 citations · 80 across the 5 of their papers we have counts for

collaborators

Showing cond-mat.mtrl-sciShow all

3 papers · 1 filter

cond-mat.mtrl-sci2025

A Computational Study for Screening High-Selectivity Inhibitors in Area-Selective Atomic Layer Deposition on Amorphous Surfaces

Gijin Kim, Purun-hanul Kim, Suk Gyu Hahm +4

Area-selective atomic layer deposition (AS-ALD) is an emerging technology in semiconductor manufacturing. However, accurately understanding inhibitor reactivity on surfaces remains…

cond-mat.mtrl-sci2025

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

Hyungmin An, Sangmin Oh, Dongheon Lee +4

Plasma etching, a critical process in semiconductor fabrication, utilizes hydrofluorocarbons both as etchants and as precursors for carbon film formation, where precise control ove…

cond-mat.mtrl-sci2025

Unveiling defect motifs in amorphous GeSe using machine learning interatomic potentials

Minseok Moon, Seungwoo Hwang, Jaesun Kim +3

Ovonic threshold switching (OTS) selectors play a critical role in non-volatile memory devices because of their nonlinear electrical behavior and polarity-dependent threshold volta…

A Computational Study for Screening High-Selectivity Inhibitors in Area-Selective Atomic Layer Deposition on Amorphous Surfaces

Etching-to-deposition transition in SiO2​/Si3​N4​ using CHx​Fy​ ion-based plasma etching: An atomistic study with neural network potentials

Unveiling defect motifs in amorphous GeSe using machine learning interatomic potentials

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