One type of device that is of particular interest to the NDML is graphene-based nanoelectromechanical resonators (GNEMS). This is because GNEMS can be used as both extremely sensitive mass/force detectors for biosensing applications and as highly tunable, reconfigurable electromechanical filters for communications applications. GNEMS resonators offer the potential to overcome many of the limitations of traditional MEMS-based resonators because of graphene’s outstanding electrical and mechanical properties. For example, graphene has an extremely high stiffness-to-weight ratio, which makes it possible to construct graphene resonators with very high natural frequencies. Also, graphene has a very high yield strain, which allows it to be stretched to very large tensions before failure. These properties allow us to tune the resonance frequency of a single graphene resonator over an extremely wide range (~ three orders of magnitude from MHz to GHz), which is important in communications and sensing applications.
One of the major challenges in producing highly accurate graphene-based sensors and filters is the poor fabrication repeatability of graphene resonators due to small variations in the residual stress and initial tension of the graphene film. This has meant that graphene-based nanoelectromechanical resonators tend to have large variations in natural frequency and quality factor from device to device. This poor repeatability makes it impossible to use these resonators to make accurate, high-precision force and displacement sensors or electromechanical filters. However, by actively controlling the tension on the graphene resonator it is possible both to increase repeatability between devices and to increase the force/mass sensitivity of the nanoelectromechanical resonators produced. Such tension control makes it possible to produce electrometrical filters that can be precisely tuned over a frequency range of up to several orders-of-magnitude.
In order to controllably strain the graphene resonator, a microelectromechanical system (MEMS) is be used to apply tension to the graphene. The MEMS device consists of a graphene resonator connected between a set of gold electrodes, as shown in Figure 9A. Each gold electrode is located on a different MEMS stage. Each stage is connected to a set of flexural bearings which are used to guide the motion of the stage. The displacement stage is actuated using a thermal actuator that allows a uniform and constant tension to be applied to the graphene resonator. The displacement of the actuator and the tension applied to the graphene are measured using a pair of differential capacitive actuators. The resonator is actuated electrostatically using the electrical backgate, and the resonant frequency is measured from the change in conductance of the graphene as it approaches resonance. Using this setup, it is possible to tune the natural frequency of the graphene resonator with high precision and accuracy.
In addition to designing devices that can compensate for manufacturing errors in nanomanufactured devices, the NDML is also developing methods that can greatly expand the scope and rate at which nanomaterials-based devices can be fabricated. For example, the NDML has developed a transfer-free, wafer-scale manufacturing process to produce suspended graphene-based devices such as the graphene-based NEMS resonators. This new method involves the growth of graphene directly on the device wafer and release of the graphene-based device through etching of the copper catalyst layer. This method replaces traditional graphene fabrication methods, such as mechanical exfoliation, electron beam lithography, or transfer from copper foils, which are slow and require a transfer step that is the source of much of inconsistency in suspended graphene-based devices. Therefore, these new transfer-free, wafer-scale fabrication methods developed in the NDML offer the potential to increase the throughput, yield, and repeatability of manufacturing processes for graphene resonators while reducing manufacturing costs and complexity.