生物传感器
纳米技术
表征(材料科学)
示意图
计算机科学
扫描探针显微镜
材料科学
曲面(拓扑)
接口(物质)
生物系统
电子工程
毛细管作用
工程类
复合材料
生物
数学
几何学
毛细管数
作者
Dan Bizzotto,Ian J. Burgess,Thomas Doneux,Takamasa Sagara,Hua‐Zhong Yu
出处
期刊:ACS Sensors
[American Chemical Society]
日期:2017-12-28
卷期号:3 (1): 5-12
被引量:113
标识
DOI:10.1021/acssensors.7b00840
摘要
Design and development of surface-based biosensors is challenging given the multidisciplinary nature of this enterprise, which is certainly the case for electrochemical biosensors. Self-assembly approaches are used to modify the surface with capture probes along with electrochemical methods for detection. Complex surface structures are created to improve the probe-target interaction. These multicomponent surface structures are usually idealized in schematic representations. Many rely on the analytical performance of the sensor surface as an indication of the quality of the surface modification strategy. While directly linked to the eventual device, arguments for pursuing a more extensive characterization of the molecular environments at the surface are presented as a path to understanding how to make electrochemical sensors that are more robust, reliable with improved sensitivity. This is a complex task that is most often accomplished using methods that only report the average characteristics of the surface. Less often applied are methods that are sensitive to the probe (or adsorbate) present in nonideal configurations (e.g., aggregates, clusters, nonspecifically adsorbed). Though these structures may compose a small fraction of the overall modified surface, they have an uncertain impact on sensor performance and reliability. Addressing this issue requires application of imaging methods over a variety of length scales (e.g., optical microscopy and/or scanning probe microscopy) that provide valuable insight into the diversity of surface structures and molecular environments present at the sensing interface. Furthermore, using in situ analytical methods, while complex, can be more relevant to the sensing environment. Reliable measurements of the nature and extent of these features are required to assess the impact of these nonideal configurations on the sensing process. The development and use of methods that can characterize complex surface based biosensors is arguably required, highlighting the need for a multidisciplinary approach toward the preparation and analysis of the biosensor surface. In many ways, representing the surface without reliance on overly simplified cartoons will highlight these important considerations for improving sensor characteristics.
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