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

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.