相关论文: Young's moduli of carbon materials investigated by…
The determination of mechanical properties such as the Young's modulus provides an important means to compare classical molecular dynamics simulations with materials. In this respect, ultra-thin materials hold several challenges: their…
Carbon nanomembranes made from aromatic precursor molecules are free standing nanometer thin materials of macroscopic lateral dimensions. Although produced in various versions for about two decades not much is known about their internal…
Carbon nanomembranes (CNMs) are nanometer-thin disordered carbon materials that are suitable for a range of applications, from energy generation and storage, through to water filtration. The structure-property relationships of these…
This paper the utilizes atomistic-continuum mechanics (ACM) to investigate the mechanical properties of single-walled carbon nanotubes (SWCNTs). By establishing a linkage between structural mechanics and molecular mechanics, not only the…
A new approach is theoretically proposed to study the glass transition of active pharmaceutical ingredients and a glass-forming anisotropic molecular liquid at high pressures. We describe amorphous materials as a fluid of hard spheres.…
The multicomponent oxide solid solution is a versatile platform to tune the delicate balance between competing spin, charge, orbital, and lattice degrees of freedom for materials design and discovery. The development of compositionally…
The Young's modulus of a two-dimensional truss-like structure is simulated by using the finite element method. A power-law expression is proposed for the effective Young's modulus of the system. The obtained numerical results are compared…
We present an accurate machine learning (ML) model for atomistic simulations of carbon, constructed using the Gaussian approximation potential (GAP) methodology. The potential, named GAP-20, describes the properties of the bulk crystalline…
The temperature dependence of mechanical properties of steel nanowires with varying carbon content was studied using molecular dynamics simulations. Four interatomic potentials were assessed, with the Modified Embedded Atom Method (MEAM)…
Carbon fiber and graphene-based nanostructures such as carbon nanotubes (CNTs) and defective structures have extraordinary potential as strong and lightweight materials. A longstanding bottleneck has been lack of understanding and…
Based on structure prediction method, the machine learning method is used instead of the density function theory (DFT) method to predict the material properties, thereby accelerating the material search process. In this paper, we…
Free-standing carbon nanomembranes (CNM) with molecular thickness and macroscopic size are fascinating objects both for fundamental reasons and for applications in nanotechnology. Although being made from simple and identical precursors…
Examination of thermal expansion of two-dimensional (2D) nanomaterials is a challenging theoretical task with either ab-initio or classical molecular dynamics simulations. In this regard, while ab-initio molecular dynamics (AIMD)…
Amorphous carbon (a-C) materials have diverse interesting and useful properties, but the understanding of their atomic-scale structures is still incomplete. Here, we report on extensive atomistic simulations of the deposition and growth of…
An important yet challenging aspect of atomistic materials modeling is reconciling experimental and computational results. Conventional approaches involve generating numerous configurations through molecular dynamics or Monte Carlo…
The central approximation made in classical molecular dynamics simulation of materials is the interatomic potential used to calculate the forces on the atoms. Great effort and ingenuity is required to construct viable functional forms and…
We study the structural and mechanical properties of nanoporous (NP) carbon materials by extensive atomistic machine-learning (ML) driven molecular dynamics (MD) simulations. To this end, we retrain a ML Gaussian approximation potential…
We introduce a Gaussian approximation potential (GAP) for atomistic simulations of liquid and amorphous elemental carbon. Based on a machine-learning representation of the density-functional theory (DFT) potential-energy surface, such…
A fundamental objective of materials modeling is identifying atomic structures that align with experimental observables. Conventional approaches for disordered materials involve sampling from thermodynamic ensembles and hoping for an…
Development of high strength carbon fibers (CFs) requires an understanding of the relationship between the processing conditions, microstructure and resulting properties. We developed a molecular model that combines kinetic Monte Carlo…