15 results on '"Mok, Dong Hyeon"'
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2. Validating ΔΔG Selectivity Descriptor for Electrosynthesis of H2O2 from Oxygen Reduction Reaction.
3. Data-driven discovery of electrocatalysts for CO2 reduction using active motifs-based machine learning.
4. Accelerating the Search for New Solid Electrolytes: Exploring Vast Chemical Space with Machine Learning-Enabled Computational Calculations.
5. Combined High-Throughput DFT and ML Screening of Transition Metal Nitrides for Electrochemical CO2 Reduction.
6. Explainable formation energy prediction for uncovering the relationship between the electronic structure and stability of the heterogeneous catalyst
7. A chemically inspired convolutional neural network using electronic structure representation.
8. Direction-Based Graph Representation to Accelerate Stable Catalyst Discovery.
9. Facet-Defined Strain-Free Spinel Oxide for Oxygen Reduction.
10. Atomic Structure Modification of Fe‒N‒C Catalysts via Morphology Engineering of Graphene for Enhanced Conversion Kinetics of Lithium–Sulfur Batteries.
11. Unraveling Surface Reconstruction During Oxygen Evolution Reaction on the Defined Spinel Oxide Surface.
12. Electrifying HCOOH synthesis from CO 2 building blocks over Cu-Bi nanorod arrays.
13. Validating ΔΔG Selectivity Descriptor for Electrosynthesis of H 2 O 2 from Oxygen Reduction Reaction.
14. Electrochemical Hydrogen Peroxide Synthesis from Selective Oxygen Reduction over Metal Selenide Catalysts.
15. Atomic Structure-Free Representation of Active Motifs for Expedited Catalyst Discovery.
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