Theory of ‘Selectivity’ of Label-Free NanoBiosensors – A Geometro-Physical Perspective
Date of this Version
2010Citation
Journal of Applied Physics: Volume 107, Issue 6. doi: 10.1063/1.3310531
This document has been peer-reviewed.
Abstract
Modern label-free biosensors are generally far more sensitive and require orders of magnitude less incubation time compared to their classical counterparts. However, a more important characteristic regarding the viability of this technology for applications in Genomics/Proteomics is defined by the ‘Selectivity’, i.e., the ability to concurrently and uniquely detect multiple target biomolecules in the presence of interfering species. Currently, there is no theory of Selectivity that allows optimization of competing factors and there are few experiments to probe this problem systematically. In this article, we use the elementary considerations of surface exclusion, diffusion limited transport, and void distribution function to provide guidance for optimum incubation time required for effective surface functionalization, and to identify the dominant components of unspecific adsorption. We conclude that optimally designed label-free schemes can compete favorably with other assay techniques, both in sensitivity as well as in selectivity.
Discipline(s)
Biomedical | Biomedical Devices and Instrumentation | Biomedical Engineering and Bioengineering | Electronic Devices and Semiconductor Manufacturing | Nanoscience and Nanotechnology | Nanotechnology Fabrication
Download
Comments
Copyright (2010) American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in Journal of Applied Physics: Volume 107, Issue 6 and may be found at http://dx.doi.org/10.1063/1.3310531. The following article has been submitted to/accepted by Journal of Applied Physics. Copyright (2010) Pradeep R. Nair and Muhammad A. Alam. This article is distributed under a Creative Commons Attribution 3.0 Unported License.