Here we report on the fabrication and characterization of a novel type of strain gauge based on percolative networks of 2D materials. The high sensitivity of the percolative carrier transport to strain induced morphology changes was exploited in strain sensors that can be produced from a wide variety of materials. Highly reliable and sensitive graphene-based thin film strain gauges were produced from solution processed graphene flakes by spray deposition. Control of the gauge sensitivity could be exerted through deposition-induced changes to the film morphology. This exceptional property was explained through modeling of the strain induced changes to the flake-flake overlap for different percolation networks. The ability to directly deposit strain gauges on complex-shaped and transparent surfaces was presented. The demonstrated scalable fabrication, superior sensitivity over conventional sensors, and unique properties of the described strain gauges have the potential to improve existing technology and open up new fields of applications for strain sensors.
Superfast water transport discovered in graphitic nanoconduits, including carbon nanotubes and graphene nanochannels, implicates crucial applications in separation processes and energy conversion. Yet lack of complete understanding at the single-conduit level limits development of new carbon nanofluidic structures and devices with desired transport properties for practical applications. Here, we show that the hydraulic resistance and slippage of single graphene nanochannels can be accurately determined using capillary flow and a novel hybrid nanochannel design without estimating the capillary pressure. Our results reveal that the slip length of graphene in the graphene nanochannels is around 16 nm, albeit with a large variation from 0 to 200 nm regardless of the channel height. We corroborate this finding with molecular dynamics simulation results, which indicate that this wide distribution of the slip length is due to the surface charge of graphene as well as the interaction between graphene and its silica substrate.
Flexible and transparent pressure sensor arrays can find applications in many places such as touch panels, artificial skin, or human motion detection. However, conventional strain gauges are rigid and opaque and are not suitable for such applications. Graphene‐based percolative strain gauges can overcome these challenges but currently are still in the infancy of their development. In this work, the performance of graphene‐based percolative strain gauges is investigated and guidelines to improve the durability and sensitivity of graphene films as sensing elements are developed. It is found that the gauge factor depends on the initial resistance of the graphene film. For the same film resistance, it is found that graphene flake size and film morphology also play a role in determining the gauge factor. Increasing the flake–flake resistance through assembly of surfactant molecules between graphene flakes provides an additional route to enhance the gauge factor. Furthermore, encapsulating the percolative film in micrometer‐thin Poly(methyl methacrylate) does not disrupt the sensing process but significantly improves the sensor's durability. Finally, thus enhanced graphene strain gauges are integrated into flexible and transparent pressure sensor arrays that exhibit high reproducibility and sensitivity.
Two-dimensional materials such as graphene have shown great promise as biosensors, but suffer from large device-to-device variation due to non-uniform material synthesis and device fabrication technologies. Here, we develop a robust bioelectronic sensing platform composed of more than 200 integrated sensing units, custom-built high-speed readout electronics, and machine learning inference that overcomes these challenges to achieve rapid, portable, and reliable measurements. The platform demonstrates reconfigurable multi-ion electrolyte sensing capability and provides highly sensitive, reversible, and real-time response for potassium, sodium, and calcium ions in complex solutions despite variations in device performance. A calibration method leveraging the sensor redundancy and device-to-device variation is also proposed, while a machine learning model trained with multi-dimensional information collected through the multiplexed sensor array is used to enhance the sensing system’s functionality and accuracy in ion classification.
Large area graphene grown by chemical vapor deposition (CVD) has been the main focus of many researchers due to its vast areas of applications such as sensing or photovoltaics.Addressing the main challenges in transfer techniques such as Roll-to-Roll (R2R) process is a critical step for scaling up and commercialization of graphene. In this work, we employ a R2R transfer technique and improve the electrical properties of transferred graphene on flexible substrates using parylene as an interfacial layer. We deposit a layer of parylene on graphene/copper (Cu) foils grown by CVD and laminate them onto EVA/PET. Then, the samples are delaminated from the Cu using an electrochemical transfer process, resulting in flexible and conductive substrates with sheet resistance of below 300 Ω/sq, which is significantly better (4-fold) than the sample transferred by R2R without parylene (1200 Ω/sq). By scanning over different types of parylene (N, C, and D) here, we find that parylene C and D are better candidates than parylene N, given the higher conductivity measured on the as-transferred graphene samples. Our characterization results indicate that parylene C and D dope graphene due to the presence of chlorine atoms in their structure, resulting in higher carrier density and thus lower sheet resistance. Density functional theory (DFT) calculations reveal that the binding energy between parylene and graphene is stronger than that of EVA and graphene, which may lead to less tear in graphene during the R2R transfer. Finally, we fabricate organic solar cells (OSCs) on the ultrathin and flexible parylene/graphene substrates and achieve an ultra-lightweight device with a power conversion efficiency (PCE) of 5.86% comparable with PET/ITO ones, which has also a high power-per-weight of 6.46 W/g. In this study, we employ PV2000/PC 60 BM blend for the device fabrication, which does not require any encapsulation due to its superior air-stability.
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