Particle Technology Laboratory , ETH Zurich , Zurich CH-8092 , Switzerland.
Institute for Breath Research of the University of Innsbruck , Dornbirn AT-6850 , Austria.
Anal Chem. 2018 Apr 17;90(8):4940-4945. doi: 10.1021/acs.analchem.8b00237. Epub 2018 Apr 5.
Earthquakes are lethal natural disasters frequently burying people alive under collapsed buildings. Tracking entrapped humans from their unique volatile chemical signature with hand-held devices would accelerate urban search and rescue (USaR) efforts. Here, a pilot study is presented with compact and orthogonal sensor arrays to detect the breath- and skin-emitted metabolic tracers acetone, ammonia, isoprene, CO, and relative humidity (RH), all together serving as sign of life. It consists of three nanostructured metal-oxide sensors (Si-doped WO, Si-doped MoO, and Ti-doped ZnO), each specifically tailored at the nanoscale for highly sensitive and selective tracer detection along with commercial CO and humidity sensors. When tested on humans enclosed in plethysmography chambers to simulate entrapment, this sensor array rapidly detected sub-ppm acetone, ammonia, and isoprene concentrations with high accuracies (19, 21, and 3 ppb, respectively) and precision, unprecedented by portable sensors but required for USaR. These results were in good agreement (Pearson's correlation coefficients ≥0.9) with benchtop selective reagent ionization time-of-flight mass spectrometry (SRI-TOF-MS). As a result, an inexpensive sensor array is presented that can be integrated readily into hand-held or even drone-carried detectors for first responders to rapidly screen affected terrain.
地震是致命的自然灾害,经常导致建筑物倒塌将人活埋。使用手持式设备追踪被困人员独特的挥发性化学特征,将加速城市搜索和救援(USaR)工作。在这里,提出了一项初步研究,使用紧凑型和正交传感器阵列来检测呼吸和皮肤排放的代谢示踪剂丙酮、氨、异戊二烯、CO 和相对湿度(RH),所有这些都作为生命迹象。它由三个纳米结构金属氧化物传感器(Si 掺杂 WO、Si 掺杂 MoO 和 Ti 掺杂 ZnO)组成,每个传感器都在纳米尺度上进行了专门设计,以实现对痕量气体的高灵敏度和选择性检测,同时还包括商用 CO 和湿度传感器。当在模拟被困的 plethysmography 室中的人体上进行测试时,该传感器阵列能够快速检测到亚 ppm 级的丙酮、氨和异戊二烯浓度,具有很高的准确性(分别为 19、21 和 3 ppb)和精度,这是便携式传感器前所未有的,但对于 USaR 却是必需的。这些结果与台式选择性试剂电离飞行时间质谱(SRI-TOF-MS)具有很好的一致性(Pearson 相关系数≥0.9)。因此,提出了一种廉价的传感器阵列,可以很容易地集成到手持式甚至无人机携带的探测器中,以便第一响应者能够快速筛查受影响的区域。