Omnics Research Group, Department of Mathematics and Physics University of Salento, CNR-Institute of Nanotechnology, INFN Sezione di Lecce, Via per Monteroni, 73100 Lecce, Italy.
Department of Biological and Environmental Sciences and Technologies, University of Salento, Via Monteroni, 73100 Lecce, Italy.
Biosensors (Basel). 2023 Jan 28;13(2):197. doi: 10.3390/bios13020197.
In this work, we report the parametric optimization of surface acoustic wave (SAW) delay lines on Lithium niobate for environmental monitoring applications. First, we show that the device performance can be improved by acting opportunely on geometrical design parameters of the interdigital transducers such as the number of finger pairs, the finger overlap length and the distance between the emitter and the receiver. Then, the best-performing configuration is employed to realize SAW sensors. As aerosol particulate matter (PM) is a major threat, we first demonstrate a capability for the detection of polystyrene particles simulating nanoparticulates/nanoplastics, and achieve a limit of detection (LOD) of 0.3 ng, beyond the present state-of-the-art. Next, the SAW sensors were used for the first time to implement diagnostic tools able to detect Grapevine leafroll-associated virus 3 (GLRaV-3), one of the most widespread viruses in wine-growing areas, outperforming electrochemical impedance sensors thanks to a five-times better LOD. These two proofs of concept demonstrate the ability of miniaturized SAW sensors for carrying out on-field monitoring campaigns and their potential to replace the presently used heavy and expensive laboratory instrumentation.
在这项工作中，我们报告了用于环境监测应用的铌酸锂表面声波（SAW）延迟线的参数优化。首先，我们表明通过适时作用于叉指换能器的几何设计参数（例如指对数、指重叠长度和发射器与接收器之间的距离）可以提高器件性能。然后，采用性能最佳的配置来实现 SAW 传感器。由于气溶胶颗粒物（PM）是主要威胁，我们首先展示了检测模拟纳米颗粒/纳米塑料的聚苯乙烯颗粒的能力，并实现了 0.3ng 的检测限（LOD），超过了当前的最先进水平。接下来，首次使用 SAW 传感器来实现诊断工具，能够检测到葡萄卷叶相关病毒 3（GLRaV-3），这是葡萄酒产区最广泛的病毒之一，其检测限（LOD）比电化学阻抗传感器好五倍。这两个概念验证证明了小型化 SAW 传感器在进行现场监测活动方面的能力及其替代目前使用的重型和昂贵的实验室仪器的潜力。
