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Direct Catalytic Fuel Cell Device Coupled to Chemometric Methods to Detect Organic Compounds of Pharmaceutical and Biomedical Interest

机译：直接催化燃料电池装置耦合到化学计量方法以检测药物和生物医学兴趣的有机化合物

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Making use of a small direct methanol fuel cell device (DMFC), used as an analytical sensor, chemometric methods, organic compounds very different from one another, can be determined qualitatively and quantitatively. In this research, the following seven different organic compounds of pharmaceutical and biomedical interest, having in common only one –OH group, were considered: chloramphenicol, imipenem, methanol, ethanol, propanol, atropine and cortisone. From a quantitative point of view, the traditional approach, involving the building of individual calibration curves, which allow the quantitative determination of the corresponding organic compounds, even if with different sensitivities, was followed. For the qualitative analysis of each compound, this approach has been much more innovative. In fact, by processing the data from each of the individual response curves, obtained through the fuel cell, using chemometric methods, it is possible to directly identify and recognize each of the seven organic compounds. Since the study is a proof of concept to show the potential of this innovative methodological approach, based on the combination of direct methanol fuel cell with advanced chemometric tools, at this stage, concentration ranges that may not be the ones found in some real situations were investigated. The three methods adopted are all explorative methods with very limited computation costs, which have different characteristics and, therefore, may provide complementary information on the analyzed data. Indeed, while PCA (principal components analysis) provides the most parsimonious summary of the variability observed in the current response matrix, the analysis of the current response behavior was performed by the “slicing” method, in order to transform the current response profiles into numerical matrices, while PARAFAC (Parallel Factor Analysis) allows to obtain a finer deconvolution of the exponential curves. On the other hand, the multiblock nature of “ComDim” (Common Components and Specific Weight Analysis) has been the basis to relate the variability observed in the current response behavior with the parameters of the linear calibrations.
机译：利用小型直接甲醇燃料电池装置（DMFC），用作分析传感器，化学计量方法，彼此彼此不同的有机化合物，可以定性和定量地确定。在本研究中，七种不同的药物和生物医学兴趣的有机化合物，具有常见的一个-OH基团，被认为是：氯霉素，亚胺尼，甲醇，乙醇，丙醇，阿托品和可可酮。从定量的角度来看，涉及构建单个校准曲线的传统方法，这允许定量测定相应的有机化合物，即使有不同的敏感性。对于每个化合物的定性分析，这种方法更具创新性。事实上，通过使用化学计量方法处理通过燃料电池获得的每个单独的响应曲线的数据，可以直接识别和识别七种有机化合物中的每一个。自该研究是概念证据，以展示这种创新方法方法的潜力，基于直接甲醇燃料电池与先进化学计量工具的组合，在此阶段，浓度范围可能不是一些真实情况中的发现。调查。采用的三种方法是所有具有非常有限的计算成本的探索方法，具有不同的特征，因此可以提供有关分析数据的互补信息。实际上，虽然PCA（主成分分析）提供了在当前响应矩阵中观察到的可变性的最常见的概述，但是通过“切片”方法执行当前响应行为的分析，以便将电流响应轮廓转换为数字矩阵，而PARAFAC（并行因子分析）允许获得指数曲线的更精细的解构。另一方面，“comdim”（常见组件和特定权重分析）的多块性质是在与线性校准的参数中涉及当前响应行为中观察到的可变性的基础。

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