We report electrical characterization of monolayer molybdenum disulfide (MoS 2 ) devices using a thin layer of polymer electrolyte consisting of poly(ethylene oxide) (PEO) and lithium perchlorate (LiClO 4 ) as both a contact-barrier reducer and channel mobility booster. We find that bare MoS 2 devices (without polymer electrolyte) fabricated on Si/SiO 2 have low channel mobility and large contact resistance, both of which severely limit the field-effect mobility of the devices. A thin layer of PEO/ LiClO 4 deposited on top of the devices not only substantially reduces the contact resistance but also boost the channel mobility, leading up to three-orders-ofmagnitude enhancement of the field-effect mobility of the device. When the polymer electrolyte is used as a gate medium, the MoS 2 field-effect transistors exhibit excellent device characteristics such as a near ideal subthreshold swing and an on/off ratio of 10 6 as a result of the strong gatechannel coupling.
This paper introduces a new robust method for the removal of background tissue fluorescence from Raman spectra. Raman spectra consist of noise, fluorescence and Raman scattering. In order to extract the Raman scattering, both noise and background fluorescence must be removed, ideally without human intervention and preserving the original data. We describe the rationale behind our robust background subtraction method, determine the parameters of the method and validate it using a Raman phantom against other methods currently used. We also statistically compare the methods using the residual mean square (RMS) with a fluorescence-to-signal (F/S) ratio ranging from 0.1 to 1000. The method, 'adaptive minmax', chooses the subtraction method based on the F/S ratio. It uses multiple fits of different orders to maximize each polynomial fit. The results show that the adaptive minmax method was significantly better than any single polynomial fit across all F/S ratios. This method can be implemented as part of a modular automated real-time diagnostic in vivo Raman system.
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