Bridging the gap between density functional theory and quantum tensor networks to accurately model strongly correlated nanostructured materials

01 January 2023 → 31 December 2027
Regional and community funding: Special Research Fund
Research disciplines
  • Natural sciences
    • Nanophysics and nanosystems
    • Quantum information, computation and communication
    • Computational physics
    • Theory and design of materials
    • Theoretical and computational chemistry not elsewhere classified
Correlated electron systems density functional theory tensor networks functional nanomaterials
Project description

One of the biggest challenges in computational materials science is the accurate property prediction of nanomaterials exhibiting strong electron correlations, where the behavior is dominated by strong interactions. By merging quantum tensor network concepts with commonly used density functional theory (DFT) methods, we will develop a new tensor/DFT framework, which will be applied on a series of technological relevant nanomaterials.