Ward Simon J, Cao Tengfei, Zhou Xiang, Chang Catie, Weiss Sharon M
Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA.
Interdisciplinary Material Science Program, Vanderbilt University, Nashville, TN 37235, USA.
Biosensors (Basel). 2023 Sep 9;13(9):879. doi: 10.3390/bios13090879.
We report a versatile platform based on an array of porous silicon (PSi) thin films that can identify analytes based on their physical and chemical properties without the use of specific capture agents. The ability of this system to reproducibly classify, quantify, and discriminate three proteins separately is demonstrated by probing the reflectance of PSi array elements with a unique combination of pore size and buffer pH, and by analyzing the optical signals using machine learning. Protein identification and discrimination are reported over a concentration range of two orders of magnitude. This work represents a significant first step towards a low-cost, simple, versatile, and robust sensor platform that is able to detect biomolecules without the added expense and limitations of using capture agents.
我们报道了一种基于多孔硅（PSi）薄膜阵列的多功能平台，该平台无需使用特定的捕获剂即可根据分析物的物理和化学性质识别它们。通过用孔径和缓冲液pH的独特组合探测PSi阵列元件的反射率，并使用机器学习分析光信号，证明了该系统能够分别对三种蛋白质进行可重复的分类、定量和区分。在两个数量级的浓度范围内报道了蛋白质的识别和区分。这项工作代表了朝着低成本、简单、通用和强大的传感器平台迈出的重要第一步，该平台能够检测生物分子，而无需使用捕获剂带来的额外成本和限制。
