Using Voltammetry Augmented with Physics-Based Modeling and Bayesian Hypothesis Testing to Estimate Electrolyte Composition

Voltammetry is a foundational electrochemical technique that can qualitatively and quantitatively probe electroactive species in electrolytes and as such has been used in numerous fields of study. Recently, automation has been introduced into voltammetric analyses to extend their capabilities (e.g., Bayesian parameter estimation, compound identification <i>via</i> machine learning); however, opportunities exist to enable more versatile methods across a wider range of electrolyte and experimental conditions. Here, we present a protocol that uses experimental voltammetry, physics-driven models, binary hypothesis testing, and Bayesian inference to enable robust labeling of electroactive species in multicomponent electrolytes across multiple techniques. We first describe the development of this protocol, and we subsequently validate the methodology in a case study involving five <i>N</i>-functionalized phenothiazine derivatives. In this analysis, the protocol correctly labeled an electrolyte containing 10H-phenothiazine and 10-methylphenothiazine from both cyclic voltammograms and cyclic square wave voltammograms, demonstrating its ability to identify electroactive constituents of a multicomponent solution. Finally, we identify areas of further improvement (e.g., achieving greater detection accuracy) and future applications to potentially enhance <i>in situ</i> or <i>operando</i> diagnostic workflows.

Using Voltammetry Augmented with Physics-Based Modeling and Bayesian Hypothesis Testing to Estimate Electrolyte Composition

Voltammetry is a foundational electrochemical technique that can qualitatively and quantitatively probe electroactive species in electrolytes and as such has been used in numerous fields of study. Recently, automation has been introduced into voltammetric analyses to extend their capabilities (e.g., Bayesian parameter estimation, compound identification <i>via</i> machine learning); however, opportunities exist to enable more versatile methods across a wider range of electrolyte and experimental conditions. Here, we present a protocol that uses experimental voltammetry, physics-driven models, binary hypothesis testing, and Bayesian inference to enable robust labeling of electroactive species in multicomponent electrolytes across multiple techniques. We first describe the development of this protocol, and we subsequently validate the methodology in a case study involving five <i>N</i>-functionalized phenothiazine derivatives. In this analysis, the protocol correctly labeled an electrolyte containing 10H-phenothiazine and 10-methylphenothiazine from both cyclic voltammograms and cyclic square wave voltammograms, demonstrating its ability to identify electroactive constituents of a multicomponent solution. Finally, we identify areas of further improvement (e.g., achieving greater detection accuracy) and future applications to potentially enhance <i>in situ</i> or <i>operando</i> diagnostic workflows.

Electrochemical Methods and (Bio) Sensors for Rosmarinic Acid Investigation

Rosmarinic acid (RA) is an important bioactive phenolic acid with significant biochemical activities, including the antioxidant one. It is widely found in plants of the families Lamiaceae and Boraginaceae and has many uses in the food, pharmaceutical and cosmetics industries. RA is an electroactive species owing to the presence of the two catechol groups in its structure. Due to their inherent characteristics, such as sensitivity, selectivity, ease of operation and not too high costs, electrochemical methods of analysis are interesting tools for the assessment of redox-active compounds. Moreover, there is a good correlation between the redox potential of the analyte and its capability to donate electrons and, consequently, its antioxidant activity. Therefore, this paper presents a detailed overview of the electrochemical (bio)sensors and methods, in both stationary and dynamic systems, applied for RA investigation under different aspects. These comprise its antioxidant activity, its interaction with biological important molecules and the quantification of RA or total polyphenolic content in different samples.

Developing 3D-Printable Cathode Electrode for Monolithically Printed Microbial Fuel Cells (MFCs)

Microbial Fuel Cells (MFCs) employ microbial electroactive species to convert chemical energy stored in organic matter, into electricity. The properties of MFCs have made the technology attractive for bioenergy production. However, a challenge to the mass production of MFCs is the time-consuming assembly process, which could perhaps be overcome using additive manufacturing (AM) processes. AM or 3D-printing has played an increasingly important role in advancing MFC technology, by substituting essential structural components with 3D-printed parts. This was precisely the line of work in the EVOBLISS project, which investigated materials that can be extruded from the EVOBOT platform for a monolithically printed MFC. The development of such inexpensive, eco-friendly, printable electrode material is described below. The electrode in examination (PTFE_FREE_AC), is a cathode made of alginate and activated carbon, and was tested against an off-the-shelf sintered carbon (AC_BLOCK) and a widely used activated carbon electrode (PTFE_AC). The results showed that the MFCs using PTFE_FREE_AC cathodes performed better compared to the PTFE_AC or AC_BLOCK, producing maximum power levels of 286 μW, 98 μW and 85 μW, respectively. In conclusion, this experiment demonstrated the development of an air-dried, extrudable (3D-printed) electrode material successfully incorporated in an MFC system and acting as a cathode electrode.

Evaluation of dual electrode configurations for microchip electrophoresis used for voltammetric characterization of electroactive species

Dual-channel/dual-parallel electrode configuration for microchip electrophoresis with electrochemical detection for voltammetric characterization of electrochemically active analytes in biological samples.

Electrodeposition study of the Cu-Zn-Mo system in citrate/sulfate medium

Alloys and composites that contain molybdenum have been studied due to their excellent properties, such as corrosion resistance and catalytic activity. In this work, the parameters for Cu-Zn-Mo system electrodeposition were studied, such as deposition potentials and concentration of electroactive species. The deposition potentials were examined using cyclic voltammetry and anodic linear stripping voltammetry (ALSV), the deposit morphology was evaluated using scanning electron microscopy (SEM) and crystallographic characterization was carried out for X-ray diffraction (XRD). The voltammetry studies indicated co-deposition of the metals in potentials more negative than -1.2 V, and a potential deposition at -1.5 V was chosen. The coatings presented morphology compact with small agglomerated particles with cauliflower structures, and the content of molybdenum, copper, and zinc ranged from 5 to 8%, 30 to 40% and 20 to 28%, respectively.