arXiv subjects

Zhenxing Dai

Publications and source records attributed to Zhenxing Dai.

3 recordsLinked to original sources

arXiv2026

Substitutional platinum as an efficient nonradiative recombination center in silicon

Platinum (Pt) is widely used for carrier-lifetime control in silicon power devices, yet the microscopic nonradiative recombination mechanism of the substitutional platinum ($\text{Pt}_\text{Si}$) dopant remains debated. Using first-principles calculations combined with nonradiative multiphonon theory, we systematically investigate the electronic structures and carrier capture dynamics of $\text{Pt}_\text{Si}$. Our results show that both the donor ($+/0$) and acceptor ($0/-$) levels of $\text{Pt}_\text{Si}$ exhibit large capture cross sections for electron and hole carriers, thereby making $\text{Pt}_\text{Si}$ an effective recombination center. Notably, the calculated capture cross sections are sensitive to the symmetry-equivalent defect configurations with different Jahn-Teller distortions. By accounting for two different $D_{2d}$ configurations of neutral $\text{Pt}_\text{Si}$ during transitions properly, our calculated carrier capture cross sections align well with experimental values. This work provides a microscopic picture of the carrier capture processes induced by $\text{Pt}_\text{Si}$ and emphasizes the importance of symmetry-equivalent configurations in defect-assisted nonradiative recombination.

cond-mat.mtrl-sci↗

arXiv2026

Machine learning Hamiltonian enables scalable and accurate defect calculations: The case of oxygen vacancies in amorphous SiO$_2$

Point defects critically influence the properties of materials and devices, yet density functional theory (DFT) remains computationally demanding for defect supercell calculations. Machine learning interatomic potentials (MLIPs) offer high efficiency but require extensive datasets. MLIPs trained only on defect configurations in small supercells exhibit systematic energy errors in larger supercells, demonstrating limited transferability. Here, we present a machine learning Hamiltonian (MLH) model-based method for calculating total energies and atomic forces in defect supercells with linear-scaling computational cost, enabling efficient structural relaxation and accurate formation energy predictions. We take oxygen vacancies in amorphous SiO$_2$ as an example and train the MLH model on defect configurations in 95-atom supercells, with the training data derived from 120 self-consistent field calculations and 12 structural relaxations. The MLH model enables efficient structural relaxations for host (defect-free) and defect systems in larger supercells, avoiding the systematic energy errors observed in MLIPs. The cancellation of energy errors between host and defect systems yields accurate formation energy predictions, with deviations from DFT below 50 meV. The proposed method holds significant potential for defect simulations in complex materials.

cond-mat.mtrl-sci↗

arXiv2022

DASP: Defect and Dopant ab-initio Simulation Package

In order to perform automated calculations of defect and dopant properties in semiconductors and insulators, we developed a software package, Defect and Dopant ab-initio Simulation Package (DASP), which is composed of four modules for calculating: (i) elemental chemical potentials, (ii) defect (dopant) formation energies and transition energy levels, (iii) defect and carrier densities and (iv) carrier dynamics properties of high-density defects. DASP uses the materials genome database for quick determination of competing secondary phases and calculation of the energy above convex hull when calculating the elemental chemical potential that stabilizes compound semiconductors, so it can perform high-throughput prediction of thermodynamic stability of multinary compounds. DASP calls the ab-initio softwares to perform the total energy, structural relaxation and electronic structure calculations of the defect supercells with different structure configurations and charge states, based on which the defect formation energies and transition energy levels are calculated and the corrections for electrostatic potential alignment and image charge interaction can be included. Then DASP can calculate the equilibrium densities of defects and electron and hole carriers as well as the Fermi level in semiconductors under different chemical potential conditions and different growth/working temperature. For high-density defects, DASP can calculate the carrier dynamics properties such as the photoluminescence (PL) spectrum, defect-related radiative and non-radiative carrier capture cross sections, and recombination lifetime of non-equilibrium carriers.

cond-mat.mtrl-sci↗