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The development of humidity sensors with simple transduction principles attracts considerable interest by both scientific researchers and industrial companies. Capacitive humidity sensors, based on polyimide sensing material with different thickness and surface morphologies, are prepared. The surface morphology of the sensing layer is varied from flat to rough and then to nanostructure called nanograss by using an oxygen plasma etch process. The relative humidity (RH) sensor selectively responds to the presence of water vapor by a capacitance change. The interaction between polyimide and water molecules is studied by FTIR spectroscopy. The complete characterization of the prepared capacitive humidity sensor performance is realized using a gas mixing setup and an evaluation kit. A linear correlation is found between the measured capacitance and the RH level in the range of 5 to 85%. The morphology of the humidity sensing layer is revealed as an important parameter influencing the sensor performance. It is proved that a nanograss-like structure is the most effective for detecting RH, due to its rapid response and recovery times, which are comparable to or even better than the ones of commercial polymer-based sensors. This work demonstrates the readiness of the developed RH sensor technology for industrialization.
rough polyimide, flat polyimide, Chemical technology, humidity sensor; flat polyimide; nanograss polyimide; rough polyimide, TP1-1185, Article, nanograss polyimide, humidity sensor
rough polyimide, flat polyimide, Chemical technology, humidity sensor; flat polyimide; nanograss polyimide; rough polyimide, TP1-1185, Article, nanograss polyimide, humidity sensor
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 124 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |