graphene

Dear iMechanicians, I would like to share our recent work on a drop confined by two adhesive graphene sheets (as illustrated below). 

Jiao, S., & Liu, M.* (2021). Snap-through in Graphene Nanochannels: With Application to Fluidic Control. ACS Appl. Mater. Interfaces, 13, 1158–1168.

Abstract: Advanced machine learning methods could be useful to obtain novel insights into some challenging nanomechanical problems. In this work, we employed artificial neural networks to predict the fracture stress of defective graphene samples. First, shallow neural networks were used to predict the fracture stress, which depends on the temperature, vacancy concentration, strain rate, and loading direction.

The extraordinary mechanical properties of graphene were measured on very small or supported samples. In our new paper published in Nature Communications, by developing a protocol for sample transfer, shaping and straining, we report the outstanding elastic properties and stretchability of free-standing single-crystalline monolayer graphene under in situ tensile tests.

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.

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

Abstract

The effect of simultaneous alignment of polyethylene (PE) lamellae and graphene nanoplatelets (GnP) on thermal conductivity (k) of PE-GnP composites is investigated. Measurements reveal a large increase of 1100% in k of the aligned PE-GnP composite using 10 weight% GnPs relative to unoriented pure PE. Rate of increase of k with applied strain for the pure PE-GnP composite with 10 wt% GnP is found to be almost a factor of two higher than the pure PE sample, pointing to the beneficial effect of GnP alignment on k enhancement.

http://dx.doi.org/10.1039/C7NR04455K Graphene has excellent mechanical, thermal and electrical properties. However, there are limitations in utilizing monolayers of graphene for mechanical engineering applications due to its atomic thickness and lack of bending rigidity. Synthesizing graphene aerogels or foams is one approach to utilize graphene in three-dimensional bulk forms. Recently, graphene with a gyroidal geometry has been proposed.

We demonstrated outstanding compressibility of holey graphene nanosheets, which is impossible for pristine graphene. Holey graphene powder can be easily compressed into dense and strong monoliths with different shapes at room temperature without using any solvents or binders. 

ACS Nano, Article ASAP, http://pubs.acs.org/doi/abs/10.1021/acsnano.7b00227

When a solid object is stretched, in general, it shrinks transversely. However, the abnormal ones are auxetic, which exhibit lateral expansion, or negative Poisson ratio. While graphene is a paradigm 2D material, surprisingly, graphene converts from normal to auxetic at certain strains. Here, we show via molecular dynamics simulations that the normal-auxeticity mechanical phase transition only occurs in uniaxial tension along the armchair direction or the nearest neighbor direction. Such a characteristic persists at temperatures up to 2400 K.

Given a distribution of defects on a structured surface, such as those represented by 2-dimensional crystalline materials, liquid crystalline surfaces, and thin sandwiched shells, what is the resulting stress field and the deformed shape? Motivated by this concern, we first classify, and quantify, the translational, rotational, and metrical defects allowable over a broad class of structured surfaces. With an appropriate notion of strain, the defect densities are then shown to appear as sources of strain incompatibility.