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Functionality Evaluation of Micro-Electro-Mechanical-Systems Sensor for Varied Selective Functionalization Thickness to Determine Creatinine Concentration

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The sensitivity and the selectivity are the most significant parameters of any sensor. In this paper, the effect of the coating (functionalization) thickness on the performance associated with the sensitivity… Click to show full abstract

The sensitivity and the selectivity are the most significant parameters of any sensor. In this paper, the effect of the coating (functionalization) thickness on the performance associated with the sensitivity of a Micro-Electro-Mechanical-Systems (MEMS) planar interdigital (ID) sensor is studied. The MEMS sensors are preferred due to their small size and high sensitivity. With acrylic resin and the Molecularly Imprinted Polymer (MIP), selective functionalization’s over the MEMS sensor sensing area and their detection capability is successfully analysed with heat-inactivated human serum samples having varying creatinine concentration. The performance-based coated-sensor analysis has been identified. The developed MIP coated MEMS ID sensors detection limit is 50 ppm, which is three times higher than the level of creatinine in real human serum. The MIP-coated selective MEMS sensor functionalization exhibited the highest sensitivity while measuring creatinine levels from the heat-inactivated human serum samples. The net effect of material properties, speed of withdrawal and time of dipping on the functionalization layer thickness is efficaciously investigated. This study found out that the faster speed of withdrawal would result in a thinner layer of functionalization. The functionalization layer thickness is increased with an increase in the net time of dipping. However, the findings have effectively shown that rising the sensor functionalization thickness substantially raises the saturation level.

Keywords: functionalization; functionalization thickness; creatinine; thickness; micro electro; electro mechanical

Journal Title: IEEE Sensors Journal
Year Published: 2021

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