Showing papers by "Xiaoding Wei published in 2015"
TL;DR: A mechanochemical phenomenon in graphene oxide membranes, covalent epoxide-to-ether functional group transformations that deviate from epoxide ring-opening reactions are reported, discovered through nanomechanical experiments and density functional-based tight binding calculations.
Abstract: The ability to bias chemical reaction pathways is a fundamental goal for chemists and material scientists to produce innovative materials. Recently, two-dimensional materials have emerged as potential platforms for exploring novel mechanically activated chemical reactions. Here we report a mechanochemical phenomenon in graphene oxide membranes, covalent epoxide-to-ether functional group transformations that deviate from epoxide ring-opening reactions, discovered through nanomechanical experiments and density functional-based tight binding calculations. These mechanochemical transformations in a two-dimensional system are directionally dependent, and confer pronounced plasticity and damage tolerance to graphene oxide monolayers. Additional experiments on chemically modified graphene oxide membranes, with ring-opened epoxide groups, verify this unique deformation mechanism. These studies establish graphene oxide as a two-dimensional building block with highly tuneable mechanical properties for the design of high-performance nanocomposites, and stimulate the discovery of new bond-selective chemical transformations in two-dimensional materials.
92 citations
TL;DR: The model shows that the staggered arrangement of constituents grants composites a unique size effect on mechanical strength in contrast to homogenous continuous materials.
38 citations
TL;DR: Measurements of the adhesive energy of CNT-graphite interfaces functionalized with various coverages of arylpropionic acid reveal a novel functional group interdiffusion mechanism, which arises for intermediate coverages in the presence of water, and provides significant insights for use in the development of next-generation nanocomposites.
Abstract: Weak interfilament van der Waals interactions are potentially a significant roadblock in the development of carbon nanotube- (CNT-) and graphene-based nanocomposites. Chemical functionalization is envisioned as a means of introducing stronger intermolecular interactions at nanoscale interfaces, which in turn could enhance composite strength. This paper reports measurements of the adhesive energy of CNT–graphite interfaces functionalized with various coverages of arylpropionic acid. Peeling experiments conducted in situ in a scanning electron microscope show significantly larger adhesive energies compared to previously obtained measurements for unfunctionalized surfaces (Roenbeck et al. ACS Nano 2014, 8 (1), 124–138). Surprisingly, however, the adhesive energies are significantly higher when both surfaces have intermediate coverages than when one surface is densely functionalized. Atomistic simulations reveal a novel functional group interdiffusion mechanism, which arises for intermediate coverages in the ...
25 citations
TL;DR: In this article, a Monte Carlo model was developed for predicting the mechanical properties of fiber yarns that includes statistical variation in fiber strength, and a statistical shear load transfer law based on the shear lag analysis was derived and implemented to simulate the interactions between adjacent fibers and provide a more accurate tensile stress distribution along the overlap distance.
Abstract: Understanding the complicated failure mechanisms of hierarchical composites such as fiber yarns is essential for advanced materials design. In this study, we developed a new Monte Carlo model for predicting the mechanical properties of fiber yarns that includes statistical variation in fiber strength. Furthermore, a statistical shear load transfer law based on the shear lag analysis was derived and implemented to simulate the interactions between adjacent fibers and provide a more accurate tensile stress distribution along the overlap distance. Simulations on two types of yarns, made from different raw materials and based on distinct processing approaches, predict yarn strength values that compare favorably with experimental measurements. Furthermore, the model identified very distinct dominant failure mechanisms for the two materials, providing important insights into design features that can improve yarn strength.
24 citations