Search

Highly stretchable electrodes with electrically robust behavior are critical for wide applications of soft robots, electronic skins, and flexible sensors. However, it remains challenging to fabricate such electrodes with traditional fabrication methods, such as lithography, conductive composite material synthetization, stencil printing, and microchannel injection. Herein, a facile method is proposed to construct robust and stretchable electrodes by direct‐written liquid metal (LM) onto a predeposited interface bonding layer, which greatly improves the interfacial force between the LM and substrate. An electrospun graphene oxide/thermoplastic polyurethane composite nanofiber membrane is used as the bonding layer, which provides rich –OH on the interface and in situ forming of hydrogen bond (H‐bond) with the LM oxide layer. A prototype electrode shows stretchability of 580%. The resistance remains stable that varies from 2.8 to 19.3 Ω at 500% elongation, and varies slightly after 7500 stretching cycles under 50% elongation, from 2.6–4.0 to 4.4–6.4 Ω. The fabrication technique is demonstrated with applications in stretchable circuit board assemblies and stretchable electronic cables, indicating a potential effective method for fabricating high‐performance stretchable electrodes. [ABSTRACT FROM AUTHOR]

Until now, input function is still required in quantification of local cerebral metabolic rate of glucose (LCMRGlc) using positron emission tomography (PET) and (18)F-fluoro-2-deoxy-D-glucose (FDG). Some image-derived methods were developed to get input function noninvasively instead of the arterial blood sampling method, but they needed to make complicated corrections manually, so they cannot always be applied in clinic directly. Here, we propose a simple method based on the Patlak approach by using a reference tissue region and without using any information of input function. This simulation study revealed that the present method was in good agreement with Patlak method; the difference between two methods was less than 5%. The statistical errors with two methods were also obtained, and the results showed the accuracy of LCMRGlc estimated with present method was better than that with Patlak method slightly. The simulation results indicated that the calculation of LCMRGlc with present method was quite stable and independent of the choosing of reference tissue region. All of these show that the present method is a good approximation to Patlak method. The calculation with this method is very simple and easy to perform voxel by voxel; therefore, it can be widely used not only in laboratory studies but also in clinical applications although it only provides the relative rates.