Independent component analysis of nanomechanical responses of cantilever arrays

被引:22
作者
Archibald, Rick [1 ]
Datskos, Panos
Devault, Gerald
Lamberti, Vincent
Lavrik, Nickolay
Noid, Don
Sepaniak, Michael
Dutta, Pampa
机构
[1] Oak Ridge Natl Lab, Oak Ridge, TN 37831 USA
[2] Y12 Natl Secur Complex, Oak Ridge, TN 37831 USA
[3] Univ Tennessee, Knoxville, TN 37996 USA
关键词
independent component analysis; functionalized cantilever arrays; neural networks; nanomechanical sensors;
D O I
10.1016/j.aca.2006.11.007
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The ability to detect and identify chemical and biological elements in air or liquid environments is of far reaching importance. Performing this task using technology that minimally impacts the perceived environment is the ultimate goal. The development of functionalized cantilever arrays with nanomechanical sensing is an important step towards this goal. This report couples the feature extraction abilities of independent component analysis (ICA) and the classification techniques of neural networks to analyze the signals produced by microcantilever-array-based nanomechanical sensors. The unique capabilities of this analysis unleash the potential of this sensing technology to accurately identify chemical mixtures and concentrations. Furthermore, it is demonstrated that the knowledge of how the sensor array reacts to individual analytes in isolation is sufficient information to decode mixtures of analytes-a substantial benefit, significantly increasing the analytical utility of these sensing devices. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:101 / 105
页数:5
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