43 research outputs found
Adaptive Finite Element Approximations for Kohn-Sham Models
The Kohn-Sham equation is a powerful, widely used approach for computation of
ground state electronic energies and densities in chemistry, materials science,
biology, and nanosciences. In this paper, we study the adaptive finite element
approximations for the Kohn-Sham model. Based on the residual type a posteriori
error estimators proposed in this paper, we introduce an adaptive finite
element algorithm with a quite general marking strategy and prove the
convergence of the adaptive finite element approximations. Using D{\" o}rfler's
marking strategy, we then get the convergence rate and quasi-optimal
complexity. We also carry out several typical numerical experiments that not
only support our theory,but also show the robustness and efficiency of the
adaptive finite element computations in electronic structure calculations.Comment: 38pages, 7figure
Self-regulation mechanism for charged point defects in hybrid halide perovskites
Hybrid halide perovskites such as methylammonium lead iodide (CH3NH3PbI3)
exhibit unusually low free carrier concentrations despite being processed at
low-temperatures from solution. We demonstrate, through quantum mechanical
calculations, that the origin of this phenomenon is a prevalence of ionic over
electronic disorder in stoichiometric materials. Schottky defect formation
provides a mechanism to self-regulate the concentration of charge carriers
through ionic compensation of charged point defects. The equilibrium charged
vacancy concentration is predicted to exceed 0.4% at room temperature. This
behaviour, which goes against established defect conventions for inorganic
semiconductors, has implications for photovoltaic performance
Prediction of Silicon-Based Layered Structures for Optoelectronic Applications
A method based on the particle swarm optimization (PSO) algorithm is
presented to design quasi-two-dimensional (Q2D) materials. With this
development, various single-layer and bi-layer materials in C, Si, Ge, Sn, and
Pb were predicted. A new Si bi-layer structure is found to have a much-favored
energy than the previously widely accepted configuration. Both single-layer and
bi-layer Si materials have small band gaps, limiting their usages in
optoelectronic applications. Hydrogenation has therefore been used to tune the
electronic and optical properties of Si layers. We discover two hydrogenated
materials of layered Si8H2 and Si6H2 possessing quasi-direct band gaps of 0.75
eV and 1.59 eV, respectively. Their potential applications for light emitting
diode and photovoltaics are proposed and discussed. Our study opened up the
possibility of hydrogenated Si layered materials as next-generation
optoelectronic devices.Comment: 21 pages,6 figures, 1 tabe
Transferable E(3) equivariant parameterization for Hamiltonian of molecules and solids
Using the message-passing mechanism in machine learning (ML) instead of
self-consistent iterations to directly build the mapping from structures to
electronic Hamiltonian matrices will greatly improve the efficiency of density
functional theory (DFT) calculations. In this work, we proposed a general
analytic Hamiltonian representation in an E(3) equivariant framework, which can
fit the ab initio Hamiltonian of molecules and solids by a complete data-driven
method and are equivariant under rotation, space inversion, and time reversal
operations. Our model reached state-of-the-art precision in the benchmark test
and accurately predicted the electronic Hamiltonian matrices and related
properties of various periodic and aperiodic systems, showing high
transferability and generalization ability. This framework provides a general
transferable model that can be used to accelerate the electronic structure
calculations on different large systems with the same network weights trained
on small structures.Comment: 33 pages, 6 figure