Moreira Inês Pimentel, Sato Laura, Alves Cláudia, Palma Susana, Roque Ana Cecília
UCIBIO, Chemistry Department, School of Science and Technology, NOVA University of Lisbon, 2829-516 Caparica, Portugal.
Biomed Eng Syst Technol Int Jt Conf BIOSTEC Revis Sel Pap. 2021 Feb;2021:32-39. doi: 10.5220/0010206200320039.
Electronic noses (e-noses) mimic the complex biological olfactory system, usually including an array of gas sensors to act as the olfactory receptors and a trained computer with signal-processing and pattern recognition tools as the brain. In this work, a new stimuli-responsive material is shown, consisting of self-assembled droplets of liquid crystal and ionic liquid stabilised within a fish gelatin matrix. These materials change their opto/electrical properties upon contact with volatile organic compounds (VOCs). By using an in-house developed e-nose, these new gas-sensing films yield characteristic optical signals for VOCs from different chemical classes. A support vector machine classifier was implemented based on 12 features of the signals. The results show that the films are excellent identifying hydrocarbon VOCs (toluene, heptane and hexane) (95% accuracy) but lower performance was found to other VOCs, resulting in an overall 60.4% accuracy. Even though they are not reusable, these sustainable gas-sensing films are stable throughout time and reproducible, opening several opportunities for future optoelectronic devices and artificial olfaction systems.
电子鼻模仿复杂的生物嗅觉系统,通常包括一系列充当嗅觉感受器的气体传感器,以及一台配备信号处理和模式识别工具的经过训练的计算机作为“大脑”。在这项研究中,展示了一种新型的刺激响应材料,它由液晶自组装液滴和稳定在鱼明胶基质中的离子液体组成。这些材料在与挥发性有机化合物(VOCs)接触时会改变其光学/电学性质。通过使用自行开发的电子鼻,这些新型气敏薄膜对来自不同化学类别的VOCs产生特征性光学信号。基于信号的12个特征实现了支持向量机分类器。结果表明,这些薄膜在识别碳氢化合物VOCs(甲苯、庚烷和己烷)方面表现出色(准确率95%),但对其他VOCs的性能较低,总体准确率为60.4%。尽管它们不可重复使用,但这些可持续的气敏薄膜在整个时间内都是稳定的且可重现的,为未来的光电器件和人工嗅觉系统开辟了多个机会。