Graphene has demonstrated great promise for technological use, yet control over material growth and understanding of how material imperfections affect the performance of devices are challenges that hamper the development of applications. In this work, we reveal new insight into the connections between the performance of the graphene devices as environmental sensors and the microscopic details of the interactions at the sensing surface. We monitor changes in the resistance of the chemical-vapor deposition grown graphene devices as exposed to different concentrations of ethanol. We perform thermal surface treatments after the devices are fabricated, use scanning probe microscopy to visualize their effects down to nanometer scale and correlate them with the measured performance of the device as an ethanol sensor. Our observations are compared to theoretical calculations of charge transfers between molecules and the graphene surface. We find that, although often overlooked, the surface cleanliness after device fabrication is responsible for the device performance and reliability. These results further our understanding of the mechanisms of sensing in graphene-based environmental sensors and pave the way to optimizing such devices, especially for their miniaturization, as with decreasing size of the active zone the potential role of contaminants will rise.
Laplace pressure driven snap-off is a technique that is used to produce droplets for emulsions and microfluidics purposes. Previous predictions of droplet size have assumed a quasi-equilibrium low flow limit. We present a simple model to predict droplet sizes over a wide range of flow rates, demonstrating a rich landscape of droplet stability depending on droplet size and growth rate. The model accounts for the easily adjusted experimental parameters of geometry, interfacial tension, and the viscosities of both phases.
Fabrication of custom-built heterostructures based on stacked 2D materials provides an effective method to controllably tune electronic and optical properties. To that end, optimizing fabrication techniques for building these heterostructures is imperative. A common challenge in layer-by-layer assembly of 2D materials is the formation of bubbles at atomically thin interfaces. We propose a technique for addressing this issue by removing the bubbles formed at the heterostructure interface in a custom-defined area using the heat generated by a laser equipped with raster scanning capabilities. We demonstrate that the density of bubbles formed at graphene-ReS2 interfaces can be controllably reduced using this method. We discuss an understanding of the flattening mechanism by considering the interplay of interface thermal conductivities and adhesion energies between two atomically thin 2D materials.
We explore the substrate-dependent charge carrier dynamics of large area graphene films using contact-free non-invasive terahertz spectroscopy. The graphene samples are deposited on seven distinct substrates relevant to semiconductor technologies and flexible/photodetection devices. Using a Drude model for Dirac fermions in graphene and a fitting method based on statistical signal analysis, we extract transport properties such as the charge carrier density and carrier mobility. We find that graphene films supported by substrates with minimal charged impurities exhibit an enhanced carrier mobility, while substrates with a high surface roughness generally lead to a lower transport performance. The smallest amount of doping is observed for graphene placed on the polymer Zeonor, which also has the highest carrier mobility. This work provides valuable guidance in choosing an optimal substrate for graphene to enable applications where high mobility is required.
The ability to detect and recognize airborne chemical species is essential to enable applications in security, health, and environmental monitoring. Here, we report a sensing platform based on graphene field-effect transistor (GFET) devices combined with optical illumination for the detection of volatile compounds. We compare the change in resistance of GFET sensors upon exposure to analytes such as ethanol, dimethyl methylphosphonate (DMMP), and water vapors with and without the presence of a local illuminating ultraviolet (UV) light-emitting diode (LED). Our results show that UV illumination acts as a control knob for the electronic transport properties of graphene, increasing the device’s response to ethanol, water, and DMMP, up to a factor of 54, and enabling ppb-level detection of DMMP at 800 ppb without chemical functionalization of the graphene layer. The sensing response can be optimized to reveal an analyte-specific interplay between the induced changes in carrier concentration and mobility of the GFET. These findings provide a pathway to enhancing the sensitivity of GFET sensors and a differentiation channel to improve their selectivity.
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