Xianqiao Wang

Programmable hydrogenation of graphene for novel nanocages

Folded graphene has exhibited novel electrical and mechanical properties unmatched by pristine graphene, which implies that morphology of graphene adds the dimensionality of design space to tailor its properties. However, how to overcome the energy barrier of the folding process to fold the graphene with the specific morphology remains unexplored. Here we propose a programmable chemical functionalization by doping a pristine graphene sheet in a certain pattern with hydrogen atoms to precisely control its folding morphology. Molecular dynamics simulation has been performed to create a cross-shaped cubic graphene nanocage encapsulating a biomolecule by warping the top graphene layer downward and the bottom graphene layer upward to mimic the drug delivery vehicle. Such a paradigm, programmable enabled graphene nanocage, opens up a new avenue to control the 3D architecture of folded graphene and therefore provides a feasible way to exploit and fabricate the graphene-based unconventional nanomaterials and nanodevices for drug delivery.

Designing Nanoparticle Translocation through Cell Membranes by Varying Amphiphilic Polymer Coatings

Nanoparticle (NP)-assisted drug delivery has been emerging as an active research area. Understanding and controlling the interaction of the coated NPs with cell membranes is key to the development of the efficient drug delivery technologies and to the management of nanoparticle-related health and safety issues. Cellular uptake of nanoparticles coated with mixed hydrophilic/hydrophobic polymer ligands is known to be strongly influenced by the polymer pattern on the NP surface and remains open for further exploration. To unravel the physical mechanism behind this intriguing phenomenon, here we perform dissipative particle dynamics simulations to analyze the forces and efficacy time as the copolymer-coated NPs pass through the lipid bilayer so as to provide better design of coated NPs for future drug delivery applications. Four characteristic copolymer ligands are constructed to perform the simulations: hydrophilic-hydrophobic (AB), hydrophobic-hydrophilic (BA), hydrophobic-hydrophilic-hydrophobic-hydrophilic (BABA), and a random pattern with hydrophilic and hydrophobic beads. We mainly study the critical force and potential of mean force required for entering inside of the lipid bilayer and penetration force to pass all the way through the cell membrane as well as the translocation time for these patterned NPs across the bilayer. Through copolymer ligand pattern designing, we find a suitable nanoparticle candidate with a specific polymer coating pattern for drug delivery. These findings provide useful guidelines for the molecular design of patterned NPs for controllable cell penetrability and help establish qualitative rules for the organization and optimization of copolymer ligands for desired drug delivery.

Thermal Gradients on Graphene to Drive Nanoflake Motion

Thermophoresis has been emerging as a novel technique for manipulating nanoscale particles. Materials with good thermal conductivity and low surface friction, such as graphene, are best suited to serve as a platform for solid-solid transportations or manipulations. Here we employ nonequilibrium molecular dynamics simulations to explore the feasibility of utilizing a thermal gradient on a large graphene substrate to control the motion of a small graphene nanoflake on it. Attempts to systematically investigate the mechanism of graphene-graphene transportation have centered on the fundamental driving mechanism of the motion and the quantitative effect of significant parameters such as temperature gradient and geometry of graphene on the motion of the nanoflake. Simulation results have demonstrated that temperature gradient plays the pivotal role in the evolution of the motion of the nanoflake on the graphene surface. Also, the geometry of nanoflakes has presented an intriguing signature on the motion of the nanoflake, which shows the nanoflakes with a circular shape move slower but rotate faster than other shapes with the identical area. It reveals that edge effects can stabilize the angular motion of thermophoretically driven particles. An interesting relation between the effective initial driving force and temperature gradient has been quantitatively captured by employing the steered molecular dynamics. These findings will provide fundamental insights into the motion of nanodevices on a solid surface due to thermophoresis, and will offer the novel view for manipulating nanoscale particles on a solid surface in techniques such as cell separation, water purification, and chemical extraction.

Mechanical strength of boron nitride nanotube-polymer interfaces

We investigate the mechanical strength of boron nitride nanotube (BNNT) polymer interfaces by using in situ electron microscopy nanomechanical single-tube pull-out techniques. The nanomechanical measurements show that the shear strengths of BNNT-epoxy and BNNT-poly(methyl methacrylate) interfaces reach 323 and 219 MPa, respectively. Molecular dynamics simulations reveal that the superior load transfer capacity of BNNT-polymer interfaces is ascribed to both the strong van der Waals interactions and Coulomb interactions on BNNT-polymer interfaces. The findings of the extraordinary mechanical strength of BNNT-polymer interfaces suggest that BNNTs are excellent reinforcing nanofiller materials for light-weight and high-strength polymer nanocomposites.

Graphene folding on flat substrates

We present a combined experimental-theoretical study of graphene folding on flat substrates. The structure and deformation of the folded graphene sheet are experimentally characterized by atomic force microscopy. The local graphene folding behaviors are interpreted based on nonlinear continuum mechanics modeling and molecular dynamics simulations. Our study on self-folding of a trilayer graphene sheet reports a bending stiffness of about 6.57 eV, which is about four times the reported values for monolayer graphene. Our results reveal that an intriguing free sliding phenomenon occurs at the interlayer van der Waals interfaces during the graphene folding process. This work demonstrates that it is a plausible venue to quantify the bending stiffness of graphene based on its self-folding conformation on flat substrates. The findings reported in this work are useful to a better understanding of the mechanical properties of graphene and in the pursuit of its applications.

Cortical Folding Pattern and its Consistency Induced by Biological Growth

Cortical folding, characterized by convex gyri and concave sulci, has an intrinsic relationship to the brain’s functional organization. Understanding the mechanism of the brain’s convoluted patterns can provide useful clues into normal and pathological brain function. In this paper, the cortical folding phenomenon is interpreted both analytically and computationally, and, in some cases, the findings are validated with experimental observations. The living human brain is modeled as a soft structure with a growing outer cortex and inner core to investigate its developmental mechanism. Analytical interpretations of differential growth of the brain model provide preliminary insight into critical growth ratios for instability and crease formation of the developing brain. Since the analytical approach cannot predict the evolution of cortical complex convolution after instability, non-linear finite element models are employed to study the crease formation and secondary morphological folds of the developing brain. Results demonstrate that the growth ratio of the cortex to core of the brain, the initial thickness, and material properties of both cortex and core have great impacts on the morphological patterns of the developing brain. Lastly, we discuss why cortical folding is highly correlated and consistent by presenting an intriguing gyri-sulci formation comparison.

Cholesterol Extraction from Cell Membrane by Graphene Nanosheets: A Computational Study

The health risk associated with high cholesterol levels in the human body has motivated intensive efforts to lower them by using specialized drugs. However, little research has been reported on utilizing nanomaterials to extract extra cholesterol from living tissues. Graphene possesses great potential for cholesterol extraction from cell membranes due to its distinct porous structure and outstanding surface adhesion. Here we employ dissipative dynamic simulations to explore pathways for cholesterol extraction from a cell membrane by a sheet of graphene using a coarse-grained graphene nanosheets (CGGN) model. We first demonstrate that the self-assembly process among a single layer of graphene and a group of randomly distributed cholesterol molecules in the aqueous environment, which provides a firm foundation for graphene-cholesterol interactions and the dynamic cholesterol extraction process from the cell membrane. Simulations results show that graphene is capable of removing cholesterol molecules from the bilayer membrane. The interaction between graphene and cholesterol molecules plays an important role in determining the amount of extracted cholesterol molecules from the cell membrane. Our findings open up a promising avenue to exploit the capability of graphene for biomedical applications.

An atomistic methodology of energy release rate for graphene at nanoscale

Graphene is a single layer of carbon atoms packed into a honeycomb architecture, serving as a fundamental building block for electric devices. Understanding the fracture mechanism of graphene under various conditions is crucial for tailoring the electrical and mechanical properties of graphene-based devices at atomic scale. Although most of the fracture mechanics concepts, such as stress intensity factors, are not applicable in molecular dynamics simulation, energy release rate still remains to be a feasible and crucial physical quantity to characterize the fracture mechanical property of materials at nanoscale. This work introduces an atomistic simulation methodology, based on the energy release rate, as a tool to unveil the fracture mechanism of graphene at nanoscale. This methodology can be easily extended to any atomistic material system. We have investigated both opening mode and mixed mode at different temperatures. Simulation results show that the critical energy release rate of graphene is indepen...

The role of cohesive zone properties on intergranular to transgranular fracture transition in polycrystalline solids

A cohesive zone model is employed to simulate the fracture evolution and crack propagation in polycrystalline solids. Numerical simulations of fracture growth with various cohesive zone properties are presented and the simulation results capture the fracture transition from intergranular to transgranular mode. Three different random Voronoi grain cell tessellations are presented to study the grain size effects. The simulation results show that the intergranular to transgranular fracture transition in the polycrystalline solid is sensitive to key cohesive law parameters such as fracture energy and cohesive strength along grain boundaries and in grain cells. This study also provides evidence that tensile strength of polycrystalline solid increases as grain cell size decreases.

Role of mechanical factors in cortical folding development.

Deciphering mysteries of the structure-function relationship in cortical folding has emerged as the cynosure of recent research on brain. Understanding the mechanism of convolution patterns can provide useful insight into the normal and pathological brain function. However, despite decades of speculation and endeavors the underlying mechanism of the brain folding process remains poorly understood. This paper focuses on the three-dimensional morphological patterns of a developing brain under different tissue specification assumptions via theoretical analyses, computational modeling, and experiment verifications. The living human brain is modeled with a soft structure having outer cortex and inner core to investigate the brain development. Analytical interpretations of differential growth of the brain model provide preliminary insight into the critical growth ratio for instability and crease formation of the developing brain followed by computational modeling as a way to offer clues for brains postbuckling morphology. Especially, tissue geometry, growth ratio, and material properties of the cortex are explored as the most determinant parameters to control the morphogenesis of a growing brain model. As indicated in results, compressive residual stresses caused by the sufficient growth trigger instability and the brain forms highly convoluted patterns wherein its gyrification degree is specified with the cortex thickness. Morphological patterns of the developing brain predicted from the computational modeling are consistent with our neuroimaging observations, thereby clarifying, in part, the reason of some classical malformation in a developing brain.