Self-powered sensors are gaining a lot of attention in recent years due to their possible application in the Internet of Things, medical implants and wireless and wearable devices. Human breath detection has applications in diagnostics, medical therapy and metabolism monitoring. One possible approach for breath monitoring is detecting the humidity in exhaled air. Here, we present an extremely sensitive, self-powered sensor for breath humidity monitoring. As a power source, the sensor uses electromagnetic energy harvested from the environment. Even electromagnetic energy harvested from the human body is enough for the operation of this sensor. The signal obtained using the human body as a source was up to 100 mV with an estimated power of 1 nW. The relatively low amount of energy that could be harvested in this way was producing a signal that was modulated by an interdigitated capacitor made out of electrochemically activated aluminum. The signal obtained in this way was rectified by a set of Schottky diodes and measured by a voltmeter. The sensor was capable of following a variety of different respiration patterns during normal breathing, exercise and rest, at the same time powered only by electromagnetic energy harvested from the human body. Everything happened in the normal environment used for everyday work and life, without any additional sources, and at a safe level of electromagnetic radiation.
TiO2 and CeO2 are well known as oxygen sensing materials. Despite high sensitivity, the actual utilization of these materials in gas detection remains limited. Research conducted over the last two decades has revealed synergistic effects of TiO2-CeO2 mixed oxides that have the potential to improve some aspects of oxygen monitoring. However, there are no studies on the sensing properties of the TiO2-CeO2 obtained by mechanochemical treatment. We have tested the applicability of the mechanochemically treated TiO2-CeO2 for oxygen detection and presented the results in this study. The sensing layers are prepared as a porous structure by screen printing a thick film on a commercial substrate. The obtained structures were exposed to various O2 concentrations. The results of electrical measurements showed that TiO2-CeO2 films have a significantly lower resistance than pure oxide films. Mixtures of composition TiO2:CeO2 = 0.8:0.2, ground for 100 min, have the lowest electrical resistance among the tested materials. Mixtures of composition TiO2:CeO2 = 0.5:0.5 and ground for 100 min proved to be the most sensitive. The operating temperature can be as low as 320 °C, which places this sensor in the class of semiconductor sensors working at relatively lower temperatures.
Surfaces of adsorption-based gas sensors are often heterogeneous, with adsorption sites that differ in their affinities for gas particle binding. Knowing adsorption/desorption energies, surface densities and the relative abundance of sites of different types is important, because these parameters impact sensor sensitivity and selectivity, and are relevant for revealing the response-generating mechanisms. We show that the analysis of the noise of adsorption-based sensors can be used to study gas adsorption on heterogeneous sensing surfaces, which is applicable to industrially important liquid-phase exfoliated (LPE) graphene. Our results for CO2 adsorption on an LPE graphene surface, with different types of adsorption sites on graphene flake edges and basal planes, show that the noise spectrum data can be used to characterize such surfaces in terms of parameters that determine the sensing properties of the adsorbing material. Notably, the spectrum characteristic frequencies are an unambiguous indicator of the relative abundance of different types of adsorption sites on the sensing surface and their surface densities. We also demonstrate that spectrum features indicate the fraction of the binding sites that are already occupied by another gas species. The presented study can be applied to the design and production of graphene and other sensing surfaces with an optimal sensing performance.
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