4 papers
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…
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…