Abstract
Silicon quantum dots are nanomaterials that are attractive candidates for photovoltaic applications. Doping of these materials creates p-n junctions and is important for solar cells. In this work, we present a first-principles study of the coupled influence of doping and strain on the stability, energy gap, Fermi level, electronic density, and density of states of hydrogen-passivated silicon quantum dots. We find that the cohesive energy and the energy gap decrease with increasing quantum dot size and are strongly influenced by strain. Furthermore, the response to strain also depends on the size of the quantum dot and dopant type. We present expressions of cohesive energy and energy gap as power-law of size and polynomial dependence on strain. We also show that the Fermi energy increases with size for pristine and p-type doping but decreases with size for n-type doping. We also discuss the influence of strain and dopant type on the density of states and electron density of the quantum dots.
| Original language | English |
|---|---|
| Article number | 19909 |
| Journal | Scientific Reports |
| Volume | 15 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2025 |
Funding
We gratefully acknowledge the valuable suggestions of the anonymous reviewers. This research used resources of the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility operated by the Oak Ridge National Laboratory under contract DE-AC05-00OR22725. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research.\u00A0This research also used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan (DOE Public Access Plan). We gratefully acknowledge the valuable suggestions of the anonymous reviewers. This research used resources of the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility operated by the Oak Ridge National Laboratory under contract DE-AC05-00OR22725. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research. This research also used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan ( DOE Public Access Plan ).