For many applications, gas sensors need to be very sensitive, selective and exhibit a good stability. Moreover, they should also be cheap and small, and allow a fast response time. Usually, sensors are optimized for specific applications with a compromise between the mentioned criteria. Here, we show a method that allows very sensitive, but rather slow, graphene metal oxide hybrid sensors to be used in a much faster and more effective way with a focus on targeting trace level concentrations of some common toxic air pollutants. By exploiting the first-order time-derivative of the measured resistance signal after a concentration step, the response peak is achieved much faster, while also being more robust against sensor exposure and relaxation times, and concomitantly maintaining the very high sensitivities inherent to graphene. We propose to use this method to generate an additional signal to allow using sensors that are normally rather slow in applications where steep concentration changes need to be detected with much faster time constants.

对于许多应用，气体传感器需要非常灵敏，选择性强并且具有良好的稳定性。而且，它们还应该便宜且体积小，并允许快速的响应时间。通常，传感器会针对特定应用进行优化，但要在上述标准之间做出折衷。在这里，我们展示了一种方法，该方法允许以更快，更有效的方式使用非常灵敏但相当慢的石墨烯金属氧化物混合传感器，重点是针对某些常见有毒空气污染物的痕量浓度。通过在浓缩步骤之后利用所测电阻信号的一阶时间导数，可以更快地获得响应峰，同时对传感器的曝光和弛豫时间也更加鲁棒，并因此保持了石墨烯固有的非常高的灵敏度。