Daye Zheng
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View article: Accelerating discovery of infrared nonlinear optical materials with large shift current via high-throughput screening
Accelerating discovery of infrared nonlinear optical materials with large shift current via high-throughput screening Open
Discovering nonlinear optical (NLO) materials with strong shift current response, particularly in the infrared (IR) regime, is essential for next-generation optoelectronics yet remains highly challenging in both experiments and theory, whi…
View article: Integrating Deep-Learning-Based Magnetic Model and Non-Collinear Spin-Constrained Method: Methodology, Implementation and Application
Integrating Deep-Learning-Based Magnetic Model and Non-Collinear Spin-Constrained Method: Methodology, Implementation and Application Open
We propose a non-collinear spin-constrained method that generates training data for deep-learning-based magnetic model, which provides a powerful tool for studying complex magnetic phenomena that requires large-scale simulations at the ato…
View article: ABACUS: An Electronic Structure Analysis Package for the AI Era
ABACUS: An Electronic Structure Analysis Package for the AI Era Open
ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It mainly features density functional theory (DFT) and molecu…
View article: Implementation of the SCAN Exchange-Correlation Functional with Numerical Atomic Orbitals
Implementation of the SCAN Exchange-Correlation Functional with Numerical Atomic Orbitals Open
Kohn-Sham density functional theory (DFT) is nowadays widely used for electronic structure theory simulations, and the accuracy and efficiency of DFT rely on approximations of the exchange-correlation functional. By inclusion of the kineti…
View article: DeePKS + ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials
DeePKS + ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials Open
Recently, the development of machine learning (ML) potentials has made it possible to perform large-scale and long-time molecular simulations with the accuracy of quantum mechanical (QM) models. However, for different levels of QM methods,…
View article: DeePKS+ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials
DeePKS+ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials Open
Recently, the development of machine learning (ML) potentials has made it possible to perform large-scale and long-time molecular simulations with the accuracy of quantum mechanical (QM) models. However, for high-level QM methods, such as …
View article: Calculation of Berry curvature using nonorthogonal atomic orbitals
Calculation of Berry curvature using nonorthogonal atomic orbitals Open
We present a derivation of the full formula to calculate the Berry curvature on non-orthogonal numerical atomic orbital (NAO) bases.Because usually, the number of NAOs is larger than that of the Wannier bases, we use a orbital contraction …
View article: Peculiar diffusion behavior of AlCl<sub>4</sub> intercalated in graphite from nanosecond-long molecular dynamics simulations*
Peculiar diffusion behavior of AlCl<sub>4</sub> intercalated in graphite from nanosecond-long molecular dynamics simulations* Open
The diffusion property of the intercalated species in the graphite materials is at the heart of the rate performance of graphite-based metal-ion secondary battery. Here we study the diffusion process of a AlCl4 molecule within graphite – a…
View article: Retention and recycling of deuterium in liquid lithium-tin slab studied by first-principles molecular dynamics
Retention and recycling of deuterium in liquid lithium-tin slab studied by first-principles molecular dynamics Open
View article: First-principles molecular dynamics study of deuterium diffusion in liquid tin
First-principles molecular dynamics study of deuterium diffusion in liquid tin Open
Understanding the retention of hydrogen isotopes in liquid metals, such as lithium and tin, is of great importance in designing a liquid plasma-facing component in fusion reactors. However, experimental diffusivity data of hydrogen isotope…