Drugs photostability plays two different opposite roles; a real advantage arises considering the longer expiration time of the drugs while the consequent persistence in the environment involves an obvious negative effect bound to their harmfulness.

It was already demonstrated by our research group that a direct catalytic methanol (or ethanol) fuel cell (DMFC) device can be used also for analytical purposes, such as the determination of ethanol content in beverages. In the present research we extended the application to the analysis of several ethanol-based pharmaceutical products, i.e., pharmaceutical tinctures (dyes) and disinfectants. In recent work we have also shown that the use of alcohol dehydrogenase enzyme as a component of the anodic section of a direct catalytic methanol (or ethanol) fuel cell significantly improves the performance of a simple DMFC device, making it more suitable to measure ethanol (or methanol) in real samples by this cell. At the same time, we have also shown that DMFC can respond to certain organic compounds that are more complex than methanol and ethanol and having R(R’)CH-OH group in the molecule. Firstly, pharmaceutical dyes were analyzed for their ethanol content using the simple catalytic DMFC device, with good accuracy and precision. The results are illustrated in the present paper. Additionally, a detailed investigation carried out on commercial denatured alcoholic samples evidenced several interferences due to the contained additives. Secondly, we hypothesized that by using the enzymatic fuel cell it would be possible to improve the determination, for instance, of certain antibiotics, such as imipenem, or else carry out determinations of ethanol content in saliva and serum (simulating forensic tests, correlated to drivers “breath test”); even if this has already been hypothesized in previous papers, the present study is the first to perform them experimentally, obtaining satisfactory results. In practice, all of the goals which we proposed were reached, confirming the remarkable opportunities of the enzymatic (or non-enzymatic) DMFC device.

This paper reports the analytical detection and energetic properties of a glucose-fed Direct Catalytic Fuel Cell (DCFC) operated in association with yeast cells (Saccharomyces Cerevisiae). The cell was tested in a potentiostatic mode, and the operating conditions were optimized to maximize the current produced by a given concentration of glucose. Results indicate that the DCFC is characterized by a glucose detection limit of the order to 21 mmol L⁻¹. The cell was used to estimate the “pool” of carbohydrate content in commercial soft drinks. Furthermore, the use of different carbohydrates, such as fructose and sucrose, has been shown to result in a good current yield.

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.

Direct catalytic methanol fuel cells (DCMFCs) have been studied for several years for energy conversion. Less extensive is the investigation of their analytical properties. In this paper, we demonstrate that the behavior of both the discharge and charger curves of DCMFCs depends on the chemical composition of the solution injected in the fuel cell. Their discharge and charge curves, analyzed using a chemometric data fusion method named ComDim, enable the identification of various types of aliphatic alcohols diluted in water. The results also show that the identification of alcohols can be obtained from the first portion of the discharge and charge curves. To this end, the curves have been described by a set of features related to the slope and intercept of the initial portion of the curves. The ComDim analysis of this set of features shows that the identification of alcohols can be obtained in a time that is about thirty times shorter than the time taken to achieve steady-state voltage.

A novel strategy for the qualitative analysis of carbohydrates is developed, utilizing a direct catalytic fuel cell (DCFC) as a sensor, combined with chemometric tools for processing the resulting response curves. Specifically, carbohydrate solutions were incubated with yeast to produce alcohol, and the corresponding current decay trends were measured using a direct catalytic fuel cell designed for ethanol detection. Multiple data processing approaches were then evaluated. Initially, the entire set of data points from the response curves was analyzed using principal component analysis (PCA). To reduce analysis time, chemometric processing was subsequently restricted to the initial portion of the response curves. Finally, to enhance the results, the current decay curves were analyzed in conjunction with the linear fitting parameters derived from the quasi-linear region of the initial response curves, utilizing the common dimension (ComDim) algorithm.