73 citations · 128 across the 8 of their papers we have counts for
8 papers
Machine vision for vial positioning detection toward the safe automation of material synthesis
Leslie Ching Ow Tiong, Hyuk Jun Yoo, Na Yeon Kim +3
Although robot-based automation in chemistry laboratories can accelerate the material development process, surveillance-free environments may lead to dangerous accidents primarily…
Predicting failure characteristics of structural materials via deep learning based on nondestructive void topology
Leslie Ching Ow Tiong, Gunjick Lee, Seok Su Sohn +1
Accurate predictions of the failure progression of structural materials is critical for preventing failure-induced accidents. Despite considerable mechanics modeling-based efforts,…
High-Throughput Computational-Experimental Screening Protocol for the Discovery of Bimetallic Catalysts
Byung Chul Yeo, Hyunji Nam, Hyobin Nam +6
For decades of catalysis research, the d-band center theory that correlates the d-band center and the adsorbate binding energy has successfully enabled the accelerated discovery of…
Accelerated Mapping of Electronic Density of States Patterns of Metallic Nanoparticles via Machine-Learning
Kihoon Bang, Byung Chul Yeo, Donghun Kim +2
Within first-principles density functional theory (DFT) frameworks, accurate but fast prediction of electronic structures of nanoparticles (NPs) remains challenging. Herein, we pro…
Identification of Crystal Symmetry from Noisy Diffraction Patterns by A Shape Analysis and Deep Learning
Leslie Ching Ow Tiong, Jeongrae Kim, Sang Soo Han +1
The robust and automated determination of crystal symmetry is of utmost importance in material characterization and analysis. Recent studies have shown that deep learning (DL) meth…
Slab Graph Convolutional Neural Network for Discovery of N2 Electroreduction Catalysts
Myungjoon Kim, Byung Chul Yeo, Sang Soo Han +1
The catalyst development for N2 electroreduction reaction (NRR) with low onset potential and high Faradaic efficiency is highly desired, but remains challenging. Machine learning (…
Pattern Learning Electronic Density of States
Byung Chul Yeo, Donghun Kim, Chansoo Kim +1
Electronic density of states (DOS) is a key factor in condensed matter physics and material science that determines the properties of metals. First-principles density-functional th…
Electron-Hole Separation in Ferroelectric Oxides for Efficient Photovoltaic Responses
Donghoon Kim, Hyeon Han, June Ho Lee +3
Despite their potential to exceed the theoretical Shockley-Queisser limit, ferroelectric photovoltaics (FPVs) have performed inefficiently due to their extremely low photocurrents.…