Optimization of Packaging Conditions for Long-term Stability of Colorimetric Carbon Dioxide Sensors for Capnography Applications in Non-intubated Patients
Capnography is the monitoring of concentrations of carbon dioxide in exhaled breath. It allows reliable insight into patients' metabolism, ventilation, and blood circulation. Capnography has become an integral part of anesthesiology monitoring in operating rooms. However, its used is limited in other contexts due to deeply engrained protocols, size of capnographs, and the complexity of its interpretation. Intensive care units and in-home use could greatly benefit by a widespread usage of capnographs. Measuring methods include infrared spectroscopy, mass spectroscopy, and chemical colorimetric analysis. Infrared technology is currently the most widely used and cost-effective method for measuring carbon dioxide. However, this device can be bulky and costly. A novel portable breath CO2 analyzer was developed for this purpose. The analyzer features an accurate colorimetric CO2 sensor that can analyze ETCO2 in real time. Many advancements have been in made in the sensor fabrication process. Nevertheless, research on optimal packaging conditions and accelerated aging times have been limited. In this experiment, carbon dioxide sensors were packaged at four different environmental conditions to test their long-term stability. This was done to determine if these conditions had an effect on sensor degradation. In the second part of the experiment, a separate batch of sensors was placed inside an oven at 48 oC to investigate the effect of stabilization temperature dependence and accelerated aging. In conclusion, the data obtained from the sensors packaged at different conditions could not be concluded to be statistically different. Sensors packaged at ambient conditions had the highest average value at 0.45030 V and the ones at controlled 33% humidity had the lowest at 0.39348 V. The sensors packaged at 8.25% CO2 had the smallest variance in their voltage measurements. From these data, it can be concluded that environmental testing conditions had the greatest effect on the measured signal. The oven experiment showed that sensors rapidly stabilize at high temperature and these stay constant after reaching this stabilization. For future work, the signal difference at different environmental conditions should be done. Control of environmental conditions can be achieved by building a glove box to control temperature and humidity.