A temperature sensor based on four thin-film resistors is presented. Four resistors are made in the form of thin metal layer meanders on the surface of a silicon chip. Two resistors are covered with a layer of 2.3 µm thick hard baked photoresist. Two other resistors are exposed to ambient air. The photoresist cover on two of the resistors makes a mismatch in the temperature coefficient of resistance between the covered and exposed resistors, thus enabling functionality of the system as a temperature sensor. The resistors are connected in the Wheatstone bridge configuration in order to enhance the sensitivity of the structure. Resistor meanders are 500 µm × 500 µm in lateral dimensions, each consisting of a 10 µm wide metal strip with 10 µm clearance between the strips. The total length of each strip is 12.5 mm. The material used for the meanders is 100 nm thick sputtered gold. The sensor was tested in a temperature chamber in the range from 80 °C to −50 °C. The matching between the sensor’s output and the readings obtained by the Pt1000 reference sensor was within ±0.1 °C (static), but the influence of water vapor adsorption at the exposed resistors surface on temperature measurements was visible. The sensor has potential applications in temperature measurements in air.
Starting from the fact that monocomponent adsorption, whether modeled by Lagergren or nonlinear Riccati equation, does not sustain oscillations, we speculate about the nature of multiple steady state states in multicomponent adsorption with second-order kinetics and about the possibility that multicomponent adsorption might exhibit oscillating behavior, in order to provide a tool for better discerning possible oscillations from inevitable fluctuations in experimental results or a tool for a better control of adsorption process far from equilibrium. We perform an analysis of stability of binary adsorption with second-order kinetics in multiple ways. We address perturbations around the steady state analytically, first in a classical way, then by introducing Langevin forces and analyzing the reaction flux and cross-correlations, then by applying the stochastic chemical master equation approach, and finally, numerically, by using stochastic simulation algorithms. Our results show that stationary states in this model are stable nodes. Hence, experimental results with purported oscillations in response should be addressed from the point of view of fluctuations and noise analysis.
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