Electrochemical Impedance Pattern Recognition for Detection of Microbially Influenced Corrosion

这个小型企业创新研究(SBIR)第一阶段项目是在分析和表面化学的一般领域，以及在电化学的子领域。本研究的目的是确定利用电化学阻抗模式识别技术检测发生在金属表面的微生物影响腐蚀(MIC)的可行性。该方法旨在开发基于在可疑腐蚀位置使用快速傅立叶变换电化学阻抗谱(FFTEIS)仪器在线获取电化学阻抗谱的模式识别方案。随后将使用主成分分析(PCA)技术对电化学阻抗谱数据进行处理。然后，将通过基于软件的模式识别技术对得到的PCA变换数据进行分析，以对MIC腐蚀位置进行分类。由于拟议方法的所有方面都可以由便携式计算机驱动的硬件和软件处理，因此计划中的多相SBIR活动的最终目标是开发用于在线测定MIC的便携式诊断仪器。%此第一阶段项目结合了快速傅立叶变换、主成分分析和模式识别中不同的电化学阻抗谱技术，以识别微生物引起的腐蚀和非生物腐蚀。为第一阶段制定的概念论证计划应确定这种方法在诊断具有巨大经济重要性的问题上的可行性。

This Small Business Innovation Research (SBIR) Phase I project is in the general area of analytical and surface chemistry and in the subfield of electrochemistry. The goal of this research effort is to establish the feasibility of using electrochemical impedance pattern recognition for the detection of microbially influenced corrosion (MIC) occurring at metal surfaces. The approach is directed towards development of pattern recognition schemes based upon the on-line acquisition of electrochemical impedance spectra using fast Fourier transform electrochemical impedance spectroscopy (FFTEIS) instrumentation at the suspect corrosion site. This will be followed by treatment of the electrochemical impedance spectral data using the principal components analysis (PCA) technique. The resulting PCA transformed data will then be subjected to analysis by software based pattern recognition techniques to classify the MIC corrosion site. Because all aspects of the proposed approach can be handled by portable computer driven hardware and software, the ultimate goal of the planned multi-Phase SBIR activity is the development of portable diagnostic instrumentation for the on-line determination of MIC. %%% This Phase I project brings together disparate technologies of electrochemical impedance spectroscopy in the fast Fourier transform implementation, principal components analysis, and pattern recognition for the purpose of identifying microbially induced corrosion in contrast with abiotic corrosion. The proof of concept plan set forth for Phase I should determine the feasibility of this approach to diagnosing problems of enormous economic importance.