41 citations · 80 across the 5 of their papers we have counts for
5 papers
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…
Etching-to-deposition transition in SiO/SiN using CHF 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…
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…
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials
Sungwoo Kang, Wonseok Jeong, Changho Hong +3
The discovery of new multicomponent inorganic compounds can provide direct solutions to many scientific and engineering challenges, yet the vast size of the uncharted material spac…
Training machine-learning potentials for crystal structure prediction using disordered structures
Changho Hong, Jeong Min Choi, Wonseok Jeong +6
Prediction of the stable crystal structure for multinary (ternary or higher) compounds with unexplored compositions demands fast and accurate evaluation of free energies in explori…