graphene

Materials can suffer mechanical fatigue when subjected to cyclic loading at stress levels much lower than the ultimate tensile strength, and understanding this behaviour is critical to evaluating long-term dynamic reliability. The fatigue life and damage mechanisms of two-dimensional (2D) materials, of interest for mechanical and electronic applications, are currently unknown. Here, we present a fatigue study of freestanding 2D materials, specifically graphene and graphene oxide (GO).

We've recently published our new study about Uncertainty Quantification in Molecular Dynamics (MD) Simulations. Due to the selection of functional forms of interatomic potentials or the numerical approximation, MD simulations may predict different material behavior from experiments or other high-fidelity results. In this study, we used Stochastic Reduced Order Modeling (SROM) to achieve

(1) mechanical behavior of graphene predicted by MD simulations in good agreement with the continuum model which has been calibrated by experiments;

I would like to share the codes required to perform an end-to-end molecular dynamics simulation, which will be useful to the novice researchers in the filed of atomistic simulations. I focus on simulating uniaxial tensile tests of a graphene sample in the LAMMPS molecular dynamics simulator, and I have attached two MATLAB scripts to create the input files for LAMMPS and to extract data from the LAMMPS output file.

https://doi.org/10.1002/adma.201805665 Computational modeling and simulations play an integral role in the bottom‐up design and characterization of graph‐n‐yne materials. Here, the state of the art in modeling α‐, β‐, γ‐, δ‐, and 6,6,12‐graphyne nanosheets for synthesizing graph‐2‐yne materials and 3D architectures thereof is discussed. Different synthesis methods are described and a broad overview of computational characterizations of graph‐n‐yne's electrical, chemical, and thermal properties is provided.

https://doi.org/10.1038/s41467-019-08813-x We report a transfer approach using paraffin as a support layer, whose thermal properties, low chemical reactivity and non-covalent affinity to graphene enable transfer of wrinkle-reduced and clean large-area graphene.

Wenjie Xia, Fernando Vargas-Lara, Sinan Keten, Jack F. Douglas

ACS Nano (2018), https://pubs.acs.org/doi/abs/10.1021/acsnano.8b00524

https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.121.255304

Accelerated Search and Design of Stretchable Graphene Kirigami Using Machine Learning

P.Z. Hanakata, E.D. Cubuk, D.K. Campbell and H.S. Park

   Utilizing van der Waals Slippery Interfaces to Enhance the Electrochemical Stability of Silicon Film Anodes in Lithium-Ion Batteries

    ACS Applied Materials & Interfaces [ PDF ]

Abstract