Thermoelectric MEMS sensors for natural gas analysis

T Multivariate data analysis techniques have been used for the first time in thermoelectric MEMS sensors in order to determine the composition of natural gas mixtures. Experimental measurements with different thermoelectric devices have been performed, the gathered data have been used to calibrate the sensor responses to four main components of natural gas: CH₄, C₂H₆, N₂ and CO₂. Presence of the three first components was predicted with good accuracy while CO₂ prediction was poor. Presented results indicate that thremoelectric sensors operated at different heater temperatures open the possibility of low-cost natural gas analysis.