Computational Materials Theory Group29
Research Interests
Computation is assuming a progressively crucial role in the design of functional materials with practical applications. Employing quantum mechanics and atomic simulations enables us to comprehend and manipulate matter, energy, and information at the fundamental scales of materials physics. Integration with machine learning further opens avenues for innovative approaches in materials science, offering potential breakthroughs in first-principles materials theory.
- Materials by design
- Machine learning
- Simple complexity
Advisor Professor : Kang, Joongoo
Computational Materials Theory Group Homepage
Computation is assuming a progressively crucial role in the design of functional materials with practical applications. Employing quantum mechanics and atomic simulations enables us to comprehend and manipulate matter, energy, and information at the fundamental scales of materials physics. Integration with machine learning further opens avenues for innovative approaches in materials science, offering potential breakthroughs in first-principles materials theory.
- Materials by design
- Machine learning
- Simple complexity
Advisor Professor : Kang, Joongoo
Computational Materials Theory Group Homepage
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Recent Submissions
RSS 1.0
RSS 2.0
ATOM 1.0
- Unveiling the Nanocluster Conversion Pathway for Highly Monodisperse InAs Colloidal Quantum Dots
- Identifying and clearing individual oxygen impurities on graphene through the use of NO2 as a radical scavenger
- First-principles Study of Non-Isovalent Si2AlP And Si2ZnS Alloys Covalent, Ionic and Their Mixed Phases
- Synthesis of alpha-Borylmethyl-(E)-allylborons via Cu-Catalyzed Diboration of 1-Substituted Allenols and Their Application in Stereoselective Aldehyde Allylation
- Enhanced Reactivity of Magic-Sized Inorganic Clusters by Engineering the Surface Ligand Networks