相关论文: Atomic cluster expansion potential for the Si-H sy…

Using empirical scheme, atomic structure of a new exotic class of silicon nanoclusters was elaborated upon the central icosahedral core (Si-IC) and pentagonal petals (Si-PP) growing from Si-IC vertexes. It was shown that Si-IC/Si-PP…

Machine-Learned Interatomic Potentials (MLIPs) require vast amounts of atomic structure data to learn forces and energies, and their performance continues to improve with training set size. Meanwhile, the even greater quantities of…

Amorphous phosphorus (a-P) has long attracted interest because of its complex atomic structure, and more recently as an anode material for batteries. However, accurately describing and understanding a-P at the atomistic level remains a…

Si-anodes have long been candidates thanks to an expected ten-fold increase in capacity compared to graphite. However, details of the mechanisms governing their degradation remain elusive, hindering science-guided development of long-lived…

A ubiquitous approach to obtain transferable machine learning-based models of potential energy surfaces for atomistic systems is to decompose the total energy into a sum of local atom-centred contributions. However, in many systems…

In this paper we carried out theoretical study of the general issues related to the efficiency of SiC:H/a-Si:H single- and multi-junction tandem solar cells. Implementation of numerical simulations by the use of AMPS-1D program of…

Materials used in commercial D-T fusion reactors will be exposed to irradiation and a mixture of helium and hydrogen plasma. Modeling the microstructural evolution of such materials requires the use of large-scale molecular dynamics…

We propose a scheme to construct predictive models for Hamiltonian matrices in atomic orbital representation from ab initio data as a function of atomic and bond environments. The scheme goes beyond conventional tight binding descriptions…

The Algebraic Cluster Model(ACM) is an interacting boson model that gives the relative motion of the cluster configurations in which all vibrational and rotational degrees of freedom are present from the outset. We schemed a solvable…

Amorphous silicon nitride (a-SiN) is a material which has found wide application due to its excellent mechanical and electrical properties. Despite the significant effort devoted in understanding how the microscopic structure influences the…

Silicon anodes promise high energy densities of next-generation lithium-ion batteries, but suffer from shorter cycle life. The accelerated capacity fade stems from the repeated fracture and healing of the solid-electrolyte interphase (SEI)…

We have studied hydrogen/lithium complexes in crystalline silicon using density-functional-theory methods and the ab initio random structure searching (AIRSS) method for predicting structures. A method based on the Maxwell construction and…

We present a theoretical study of Ge-core/Si-shell nanocrystals in a wide bandgap matrix and compare the results with experimental data obtained from the samples prepared by co-sputtering. The empirical tight-binding technique allows us to…

We discuss an inverse approach for atomistic modeling of glassy materials. The focus is on structural modeling and electronic properties of hydrogenated amorphous silicon and glassy GeSe2 alloy. The work is based upon a new approach…

We have performed an approximate ab initio calculation of vibrational properties of hydrogenated amorphous silicon (a-Si:H) using a molecular dynamics method. A 216 atom model for pure amorphous silicon (a-Si) has been employed as a…

A potential function is presented for describing a system of flexible H$_2$O molecules based on the single center multipole expansion (SCME) of the electrostatic interaction. The model, referred to as SCME/f, includes the variation of the…

Thermal decomposition of silicon carbide is a promising approach for the fabrication of graphene. However, the atomistic growth mechanism of graphene remains unclear. This paper describes the development of a new charge-transfer interatomic…

Numerical simulation of a solar cell can provide various information that can be useful to maximize its power conversion efficiency (PCE). In that respect we carried out a set of numerical simulation using AFORS-HET simulation program.…

Machine learning models are changing the paradigm of molecular modeling, which is a fundamental tool for material science, chemistry, and computational biology. Of particular interest is the inter-atomic potential energy surface (PES). Here…

We establish a computational framework to explore the atomic configuration of a metal-hydrogen (M-H) system when in equilibrium with a H environment. This approach combines Diffusive Molecular Dynamics with an iteration strategy, aiming to…