Swelling-induced patterning in soft microchannels.

We study the effect of inflation on the swelling-induced wrinkling of thin elastic membranes in a set-up that is commonly used to create microchannels in lab-on-chip applications. Using a combination of experiments and associated numerical simulations, we demonstrate that the out-of-plane deformation of the inflated membrane and the resulting anisotropic stress lead to two distinct instabilities as the swelling progresses. The membrane first develops small-amplitude wrinkles that retain the cross-channel symmetry. Their wavelength depends on the pressure and is set in a process similar to the axisymmetric buckling of pressurised, uni-axially compressed cylindrical shells. As swelling increases, the membrane undergoes a secondary instability during which the wrinkles coarsen into large-amplitude folds whose morphology can be controlled by the degree of pre-inflation. We elucidate the fundamental mechanisms responsible for this behaviour and explain how inflation can be used as a control mechanism in the manufacture of microchannels.

Modeling Graphene-Polymer Heterostructure MEMS Membranes with the Föppl-von Kármán Equations.

Ultra-thin graphene-based membranes have shown significant promise for high-performance nano-electro-mechanical (NEMS) devices. The key challenge in the modeling of such membranes is that they often operate in deflection regimes where the assumptions or approximations of "pure bending" or "pure stretching" are not satisfied. We present a model of graphene-polymer heterostructure (GPH) NEMS membranes based on Föppl-von Kármán (FvK) equations which take into account both bending and stretching forces. The experimental GPH membrane shape obtained through atomic force microscopy topography mapping is compared to the inflation shapes predicted by FvK-based finite element method simulation, and they show excellent agreement with each other. When the GPH membranes are deflected under pressure in a capacitive pressure sensor configuration, the effectiveness of this model is further exemplified through accurately predicting the capacitance change of deflecting GPH membrane devices at varying pressures. This model serves as a powerful new tool in the design and development of graphene-based NEMS devices, being able to predict the performance of graphene NEMS devices or to aid in the design of device geometries to match required performances.