High-throughput screening and machine learning classification of van der Waals dielectrics for 2D nanoelectronics.

ABSTRACT: Van der Waals (vdW) dielectrics are promising for enhancing the performance of nanoscale field-effect transistors (FETs) based on two-dimensional (2D) semiconductors due to their clean interfaces. Ideal vdW dielectrics for 2D FETs require high dielectric constants and proper band alignment with 2D semiconductors. However, high-quality dielectrics remain scarce. Here, we employed a topology-scale algorithm to screen vdW materials consisting of zero-dimensional (0D), one-dimensional (1D), and 2D motifs from Materials Project database. High-throughput first-principles calculations yielded bandgaps and dielectric properties of 189 0D, 81 1D and 252 2D vdW materials. Among which, 9 highly promising dielectric candidates are suitable for MoS₂-based FETs. Element prevalence analysis in

SUBMITTER: Li Y 

PROVIDER: S-EPMC11535525 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature