Computer simulations have revealed a mechanism by which nanostructures of the material graphene can be driven in one direction by controlling the stiffness of the underlying substrate.
The ability to move when and where we want is fundamental to our way of life, and our capacity for directing the natural motion of other objects and materials is essential for a range of technologies, from medicine to power generation. Although the same principles apply at the nanometre scale, miniature machines based on conventional macro-scale mechanisms have suffered from various problems, including lack of directional control, crippling frictional forces and permanent adhesion to adjacent components through strong chemical bonding. Writing in Physical Review Letters, Chang et al.1 introduce a new way of moving nanoscale materials that overcomes some of these challenges, and that does not need an external power source to drive it.
Being able to control the motion of nanomaterials would be extremely useful for processes that require the delivery of molecules and other nanoscale objects, and for the functioning of nanodevices such as energy-conversion systems. With specific applications in mind, several techniques for moving various nanostructures have been proposed, using electrical currents2 (or charge3), selective heating4 or complicated chemical reactions5. But none of these methods is intrinsic — the nanostructures do not move spontaneously, and each technique requires an energy source to sustain the motion. Furthermore, all the techniques can potentially damage the materials, which reduces the repeatability of each process. This is a problem, because viable nanotechnology must be reliable, reusable and cost-effective to run.
To find a method that fulfils these requirements and that has no need for external intervention, Chang et al. set up a series of virtual experiments using computer simulations. This approach offers some advantages over real-world experiments: one can be sure that the materials are free of defects and impurities, and that they are electrically, thermally and chemically isolated. Such isolation is particularly important when seeking intrinsic phenomena.
In their simulations, the authors first laid a nano-flake of graphene on top of a continuous graphene substrate, taking care to ensure that the lattices were not aligned. Graphene is a hexagonal lattice of carbon atoms, only one atomic layer thick, but its structure at the highly reactive edges varies depending on how the edges have been cut6. In the simulations, the flake was rotated by 30° with respect to the substrate, so that its edges did not line up with the lattice beneath. This reduced the risk of the flake becoming permanently attached to the substrate as a result of strong covalent bonding between the edges of the flake and the edges of the substrate.
Once it was in position, the authors made no further changes to the flake, but applied a stiffness gradient to the substrate, ranging from 0.801 to 4.005 newtons per metre along one direction. When the molecular-dynamics simulation was engaged, the nano-flake moved spontaneously — from a standing start — from the soft side to the hard side of the substrate (Fig. 1). Then, when it reached the end of the substrate, it rebounded because of a retraction force that pulled it back. Similar forces have been observed to pull extruded cores of multi-walled nanotubes back into the nanotubes7.
Another advantage of computer simulations is that it allows animations of modelled processes to be made. In the present case, the overall motion is dramatically displayed in an animation provided with the paper's supplementary material. One can see that the graphene flake accelerates as it approaches the hard side of the substrate, and decelerates as it rebounds towards the soft side. This is clear evidence that the stiff side is energetically preferred.
Such stiffness-guided directional motion (termed durotaxis) was first observed in living cells, which also prefer rigidity8. Although the biological mechanism for durotaxis in cells remains a mystery, it has another similarity to the nanodurotaxis observed by Chang and co-workers in their simulated system: in both cases, weak van der Waals interactions are present, and in the latter case they were found to be crucial.
To prove this, the authors systematically repeated their virtual experiments under different simulation conditions, varying temperatures, stiffness gradients and stiffness configurations. The results unambiguously showed that the strength of the effective van der Waals potential — the interaction between the flake and the substrate — was inversely proportional to the stiffness. Lower potential energies are always more stable than higher ones, so this explains why the flake moves towards a rigid spot on the substrate: by doing so, it adopts a thermodynamically preferred state. At this stage, it is unclear whether perturbations to the system could be devised to reverse the motion, driving the flake back to soft regions.
Chang and colleagues' findings could have great potential in nanodevices, in part because the observed motion is conveniently unidirectional, but also because the underlying forces fall within a useful and technologically accessible range. The driving force for the nanoscale locomotion is about 320 kilopascals per square nanometre for a 6-nm-wide nanoflake on a stiffness gradient of 0.801–2.403 N m−1. This is not too dissimilar from the forces in biological systems, such as the traction force per unit area exerted by a living cell on a substrate8,9 and the driving force generated in a protein biomotor10.
The challenge now is to fabricate graphene substrates that contain deliberate patterns of soft and hard regions, so that the experiments can be recreated in the real world. This will undoubtedly be difficult. It might also be possible to do this for other nanomaterials, but whether the simulated mechanism of nanodurotaxis will work for materials other than graphene is unknown. Nevertheless, the effort is certainly warranted, because strategic patterning of substrates might enable more-complicated trajectories to be realized, opening up new opportunities in nanoscale science and technology. Footnote 1
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