We fabricate SERS sensors by inkjet printing of colloidal Au nanoparticles on porous paper substrates. Using a modified commercial inkjet-printer, SERS sensors are prepared with multiple printing passes. SERS response is correlated with their diffuse reflectance characteristics. Chemical analyte detection is only possible with both SERS and diffuse reflectance measurements from sensors that has been subjected to more than 5 printing passes. This suggests that the simpler diffuse reflectance measurement can be used as an alternative method to characterize and optimize the SERS performance of the printed sensors. Sensors with a higher number of printing passes exhibit a much stronger SERS response from strong adsorbing analytes such as benzenethiol molecule. We compare the performances of 8 and 15 printing passes sensors with the commercially available paper-based sensors, p-SERS. We calculate their Relative Enhancement Factor (REF) by comparing their performances to the first order phonon vibration of Si, which serves as a reference standard. Lastly, we demonstrate the use of such sensors for the detection of chemical aerosols.
Inkjet-printed surface enhanced Raman spectroscopy (SERS) sensors are fabricated on cellulose based paper or fabric substrates. These flexible sensors provides basic point-of-sampling advantages that is particularly useful in field applications. Due to the heterogeneous loading of nanoparticles on the substrate, SERS intensities inevitably vary across the active area of the printed sensor. This paper will discuss the use of receiver operating characteristics (ROC) for the analysis of inkjet-printed SERS sensors. The aim is to provide an alternative measurand to the SERS enhancement factor that can be used to compare different types of SERS substrates. We have developed statistical analysis from multiple data sets obtained from sensors exposed to both analyte and control to determine the probability of positive detection (PD) at various analyte concentration. This dependence describes the ROC of the sensor and also provides confidence level associated with a given detection limit. We propose this methodology for the evaluation of SERS sensors to enable their field applications.
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