Mauro Castrucci

A simple, low-cost analytical platform based on a commercial direct methanol–ethanol fuel cell (D(M–E)FC) combined with chemometric data analysis is investigated for the quantitative analysis and exploratory differentiation of pharmaceutical and biomedical compounds containing at least one hydroxyl group with alcoholic or partially alcoholic character. Quantitative measurements were based on conventional calibration curves obtained from the steady-state current response, whereas compound differentiation exploited the dynamic current discharge profiles. Principal Component Analysis (PCA) and the multiblock Common Components and Specific Weights Analysis (ComDim) algorithm were employed to explore and integrate the information contained in the discharge curves and in their derived kinetic descriptors. Five representative compounds—chloramphenicol, imipenem, atropine, cortisone, and ethanol—were investigated. Steady-state calibration showed satisfactory linear responses for chloramphenicol, imipenem, and ethanol (R² = 0.9961, 0.9868, and 0.9888, respectively), whereas poorer linear behaviour was observed for atropine and cortisone (R² = 0.5076 and 0.7956), highlighting the analyte-dependent quantitative performance of the platform. Exploratory analysis of the averaged dynamic profiles revealed compound-dependent response patterns, with most of the relevant variance concentrated in the early transient. Restricting the acquisition to the first 120 s preserved the main structure observed for the complete profiles while substantially reducing the measurement time. Overall, the results indicate that dynamic fuel-cell responses contain analyte-dependent multivariate information that can be exploited for the exploratory differentiation of structurally diverse compounds, providing a proof of concept for combining commercial catalytic fuel cells with chemometric analysis.

Batteries, especially useful for portable instruments, are the most widely used alternative to direct current. Their operating principle is based on irreversible or reversible chemical reactions, which are called primary (non-rechargeable) or secondary (rechargeable), respectively. Primary batteries never completely discharge and their residual charge depends on the energy demand of the instrument in which they are used. Even if correctly disposed of, therefore, and with the possibility of recycling the constituent materials and purchasing and using consciously, only 2 of the 3Rs, namely “Recycle” and “Reuse”, are respected; recovering the residual charge would also allow compliance with the last of the 3Rs, namely “Reduce”. Direct energy recovery methods have been proposed but the simplest method to “reduce”, analogously to what is done with secondary batteries, remains being recharging, which, unfortunately, is a risky operation, as it can cause the battery to explode or leak corrosive solution. Following our previous research, in which we proposed a method for measuring the residual charge of alkaline batteries, we now propose a method for charging the batteries whose residual charge we measured in our previous work. In this research, a hand-built external circuit, Arduino UNO R3, was used to generate the charging pulses and as a controller and measuring instrument and an Open-Source protocol for the recharging process. The results demonstrated the feasibility of the method, as the voltage of 50% of the batteries increased and, further, only 18% of the batteries leaked and none exploded.

Portable devices are powered in direct current (DC) or by batteries (primary battery), accumulators (secondary battery), and now supercapacitors, which can also be used for energy storage. The European Portable Battery Association states that approximately 239,000 tons of batteries were placed on the market in the European Economic Area (EEA) plus Switzerland in 2022. Even if they were all disposed of correctly respecting the 3R paradigm (Reduce, Reuse and Recycle), non-rechargeable batteries create an environmental problem because they do not discharge completely with an obvious waste of energy. Secondary batteries and supercapacitors can be recharged because they use reversible chemical/physical processes while primary batteries cannot be recharged because they are based on irreversible redox reactions; nevertheless, it is possible to try to recover their residual charge if this is higher than a threshold beyond which the reactions can be reversible. The most used batteries are alkaline zinc/manganese dioxide and they are non-rechargeable; an inappropriate recharge attempt can lead to serious harm to the operator and the environment. This paper describes a simple Arduino-based circuit and the protocol to measure and graph the residual charge of an alkaline battery in order to establish if it can be recharged. The circuit, design, the Arduino Uno R3 sketch (i.e., microprocessor software) and the full protocol are here presented under the open source license (Copyright Creative Commons Public license, CC BY-NC-ND 4.0 EN) so that they could become a pilot system and then a commercial product. The residual charge of 158 batteries, obtained after discharging those that, by eye, appeared damaged, was measured. Results evidenced that 49% of batteries had a residual voltage, under low load, between 1.2 and 1.6 V, making them good candidates for a recharge attempt.

A diagnostic chemical analysis has been performed on a Roman Cippus funebris in precious white marble located close to an ancient Roman road. The Cippus was in good condition but almost completely covered by a black patina, requiring a conservative cleaning intervention. The restorer in charge of the restoration asked us to make a preliminary diagnosis, on the basis of which we could suggest the most appropriate intervention. The Cippus was dedicated to the young Quintus Cornelius Proclianus, who died at the age of 15, by his mother Valeria Calpurnia Scopele. It perfectly fits into the Roman funerary liturgy and also shows an Etruscan-type iconography that seems to confirm the Etruscan Gens of the family and its dating to the 1st century AD. Ion chromatography (IC) analyses were performed to determine anions and cations on solutions obtained from the extraction of salts from the four samples of the Cippus. pH, conductivity, and red-ox potential measures, as well as UV-visible spectra were carried out on the same solutions. A small fragment, spontaneously fallen from the Cippus’ surface, was also observed by optical microscopy (OM) and scanning electron microscopy (SEM) coupled with energy dispersive spectroscopy (EDS). From the analyses, the dark patina that covered the surface before cleaning turned out to be made of black crusts, that is, smog particles adsorbed on sulfates, but above all, by a layer of microflora. The results allowed us to suggest some conservative interventions.

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.

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.

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.

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.

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.