Voltammetric Electronic Tongue Based on Carbon Paste Electrodes Modified with Biochar for Phenolic Compounds Stripping Detection

Simultaneous determination of 4-ethylphenol and 4-ethylguaicol on C60 modified dual screen-printed electrochemical sensors

4-ethylphenol and 4-ethylguaicol levels in wine are associated to organoleptic defects that cause consumer rejection accompanied by significant economic losses for producers. Thus, electrochemical sensors based on screen-printed carbon electrodes (SPCEs) modified with activated fullerene C60 (AC60) have been developed for the analysis of both phenols by direct headspace amperometric measurements. Upon optimization of the experimental variables affecting the sensors performance, the AC60/SPCE sensors presented linearity ranges from 9.9 to 65.4 μg/L and from 19.6 to 107.1 μg/L for 4-ethylphenol and 4-ethylguaicol, respectively. The achieved detection capacities were 10.3 μg/L (4-ethylphenol) and 19.6 μg/L (4-ethylguaicol), with a reproducibility of 6.3 % and 9.1 % (n = 3), respectively. In addition, dual-working AC60/SPCE devices were developed for the simultaneous analysis of both phenols using different working potentials for each electrode. The dual systems were successfully applied in the analysis of different spiked wine samples, obtaining good recoveries ranging from 94 to 108 %.

Electrochemical sensors for the determination of 4-ethylguaiacol in wine

The development of an electrochemical procedure for the determination of 4-ethylguaiacol and its application to wine analysis is described. Modified screen-printed carbon electrodes (SPCEs) with fullerene C₆₀ (C₆₀) have been shown to be efficient in this kind of analysis. The developed activated C₆₀/SPCEs (AC₆₀/SPCEs) were adequate for the determination of 4-ethylguaicol, showing a linear range from 200 to 1000 µg/L, a reproducibility of 7.6% and a capability of detection (CC_β) value of 200 µg/L, under optimized conditions. The selectivity of the AC₆₀/SPCE sensors was evaluated in the presence of possibly interfering compounds, and their practical applicability was demonstrated  in the analysis of different wine samples obtaining recoveries ranging from 96 to 106%.

Optimized production conditions and activation of biochar for effective promotion of long-chain fatty acid degradation in anaerobic digestion

Engineered biochar production and utilization in anaerobic digestion (AD) potentially overcome its limited application to the treatment of slowly degradable or inhibitory substrates. Here an attempt was made to develop an optimized biochar production procedure for use in AD to stimulate palmitic acid biodegradation via direct interspecies electron transfer (DIET). The electrical conductivity of biochar was greatly increased with an elevated pyrolysis temperature and K₂CO₃ activation, and the conductivity reached a comparable level (0.6-1.4 S/cm) to that of carbon black at 800 °C. In addition, the K₂CO₃ activation greatly improved biochar wettability. When using K₂CO₃-activated biochar produced at 800 °C, the maximum methane production rate from palmitic acid was 1.3 times that of a control without biochar addition.

Recent Advances of Biochar-Based Electrochemical Sensors and Biosensors

In the context of accelerating the global realization of carbon peaking and carbon neutralization, biochar produced from biomass feedstock via a pyrolysis process has been more and more focused on by people from various fields. Biochar is a carbon-rich material with good properties that could be used as a carrier, a catalyst, and an absorbent. Such properties have made biochar a good candidate as a base material in the fabrication of electrochemical sensors or biosensors, like carbon nanotube and graphene. However, the study of the applications of biochar in electrochemical sensing technology is just beginning; there are still many challenges to be conquered. In order to better carry out this research, we reviewed almost all of the recent papers published in the past 5 years on biochar-based electrochemical sensors and biosensors. This review is different from the previously published review papers, in which the types of biomass feedstock, the preparation methods, and the characteristics of biochar were mainly discussed. First, the role of biochar in the fabrication of electrochemical sensors and biosensors is summarized. Then, the analytes determined by means of biochar-based electrochemical sensors and biosensors are discussed. Finally, the perspectives and challenges in applying biochar in electrochemical sensors and biosensors are provided.

Evaluation of Antioxidants Using Electrochemical Sensors: A Bibliometric Analysis

The imbalance of oxidation and antioxidant systems in the biological system can lead to oxidative stress, which is closely related to the pathogenesis of many diseases. Substances with antioxidant capacity can effectively resist the harmful damage of oxidative stress. How to measure the antioxidant capacity of antioxidants has essential application value in medicine and food. Techniques such as DPPH radical scavenging have been developed to measure antioxidant capacity. However, these traditional analytical techniques take time and require large instruments. It is a more convenient method to evaluate the antioxidant capacity of antioxidants based on their electrochemical oxidation and reduction behaviors. This review summarizes the evaluation of antioxidants using electrochemical sensors by bibliometrics. The development of this topic was described, and the research priorities at different stages were discussed. The topic was investigated in 1999 and became popular after 2010 and has remained popular ever since. A total of 758 papers were published during this period. In the early stages, electrochemical techniques were used only as quantitative techniques and other analytical techniques. Subsequently, cyclic voltammetry was used to directly study the electrochemical behavior of different antioxidants and evaluate antioxidant capacity. With methodological innovations and assistance from materials science, advanced electrochemical sensors have been fabricated to serve this purpose. In this review, we also cluster the keywords to analyze different investigation directions under the topic. Through co-citation of papers, important papers were analyzed as were how they have influenced the topic. In addition, the author’s country distribution and category distribution were also interpreted in detail. In the end, we also proposed perspectives for the future development of this topic.

Fabrication and application of three-dimensional nanocomposites modified electrodes for evaluating the aging process of Huangjiu (Chinese rice wine)

In this study, three modified glassy carbon electrodes based on three-dimensional conducting polymer nanocomposites (TDCPNs) were fabricated for evaluating the aging process of Huangjiu (Chinese rice wines). The electrochemical activity and experimental conditions of the TDCPNs modified electrodes were investigated by cyclic voltammetry, the aging information obtained by the modified electrodes were optimized by variance inflation factor (VIF). Principal components analysis (PCA), locally linear embedding (LLE), and locality preserving projection (LPP, which presented the best classification result) based on the optimized data were applied to classify the wine samples. Then, the dimensionality reduction data of PCA, LLE, and LPP were used as input variables of the logistic regression and extreme learning machine (ELM) for evaluating the aging process of Huangjiu, and the LLE-ELM method exhibited the best prediction results. These results demonstrated that the TDCPNs modified electrodes presented the potential for the quality analysis of food and beverages.

The electrochemical redox mechanism and antioxidant activity of polyphenolic compounds based on inlaid multi-walled carbon nanotubes-modified graphite electrode

The electrochemical redox mechanism of polyphenolic compounds (gallic acid [GA], caffeic acid [CA], ferulic acid [FA], and vanillic acid [VA]) were investigated by electrochemical methods at the inlaid multi-walled carbon nanotubes-modified graphite electrode (MWCNTs/GCE). The obtained micro-information such as the number of electrons and protons were used to deduce the electrochemical oxidation mechanism of four polyphenolic compounds. The antioxidation activities of these compounds were also studied by two methods. The radical scavenging activity followed the order: GA > CA > FA > VA, which was in agreement with the result from the spectrophotometry method. The result indicated that compounds with lower oxidation peak potential (E pa) showed stronger antioxidation activity. At the same time, compounds with high E pa showed lower antioxidant activity. The greater the number of hydroxyls linked to the aromatic ring, the greater the antioxidation activities of four compounds. Structural analysis of these phenolic-based compounds suggested that multiple OH substitutions and conjugations determine their free radical scavenging activity and electrochemical behavior.

Environmental footprint of voltammetric sensors based on screen-printed electrodes: An assessment towards "green" sensor manufacturing

Voltammetric sensors based on screen-printed electrodes (SPEs) await diverse applications in environmental monitoring, food, agricultural and biomedical analysis. However, due to the single-use and disposable characteristics of SPEs and the scale of measurements performed, their environmental impacts should be considered. A life cycle assessment was conducted to evaluate the environmental footprint of SPEs manufactured using various substrate materials (SMs: cotton textile, HDPE plastic, Kraft paper, graphic paper, glass, and ceramic) and electrode materials (EMs: platinum, gold, silver, copper, carbon black, and carbon nanotubes (CNTs)). The greatest environmental impact was observed when cotton textile was used as SM. HDPE plastic demonstrated the least impact (13 out of 19 categories), followed by ceramic, glass and paper. However, considering the end-of-life scenarios and release of microplastics into the environment, ceramic, glass or paper could be the most suitable options for SMs. Amongst the EMs, the replacement of metals, especially noble metals, by carbon-based EMs greatly reduces the environmental footprint of SPEs. Compared with other materials, carbon black was the least impactful on the environment. On the other hand, copper and waste-derived CNTs (WCNTs) showed low impacts except for terrestrial ecotoxicity and human toxicity (non-cancer) potentials. In comparison to commercial CNTs (CCNTs), WCNTs demonstrated lower environmental footprint and comparable voltammetric performance in heavy metal detections, justifying the substitution of CCNTs with WCNTs in commercial applications. In conclusion, a combination of carbon black or WCNTs EMs with ceramic, glass or paper SMs represents the most environmentally friendly SPE configurations for voltammetric sensor arrangement.

Graphene for the Building of Electroanalytical Enzyme-Based Biosensors. Application to the Inhibitory Detection of Emerging Pollutants

Graphene and its derivates offer a wide range of possibilities in the electroanalysis field, mainly owing to their biocompatibility, low-cost, and easy tuning. This work reports the development of an enzymatic biosensor using reduced graphene oxide (RGO) as a key nanomaterial for the detection of contaminants of emerging concern (CECs). RGO was obtained from the electrochemical reduction of graphene oxide (GO), an intermediate previously synthesized in the laboratory by a wet chemistry top-down approach. The extensive characterization of this material was carried out to evaluate its proper inclusion in the biosensor arrangement. The results demonstrated the presence of GO or RGO and their correct integration on the sensor surface. The detection of CECs was carried out by modifying the graphene platform with a laccase enzyme, turning the sensor into a more selective and sensitive device. Laccase was linked covalently to RGO using the remaining carboxylic groups of the reduction step and the carbodiimide reaction. After the calibration and characterization of the biosensor versus catechol, a standard laccase substrate, EDTA and benzoic acid were detected satisfactorily as inhibiting agents of the enzyme catalysis obtaining inhibition constants for EDTA and benzoic acid of 25 and 17 mmol·L⁻¹, respectively, and a maximum inhibition percentage of the 25% for the EDTA and 60% for the benzoic acid.

Rapid visualized characterization of phenolic taste compounds in tea extract by high-performance thin-layer chromatography coupled to desorption electrospray ionization mass spectrometry

Phenolic compounds are the important taste source of tea infusion. In this paper, the phenolic compounds in tea extracts were separated by high-performance thin-layer chromatography (HPTLC), and then in-situ determined by desorption electrospray ionization mass spectrometry (DESI-MS). Total 44 phenolic compounds in tea extracts were accurately confirmed by NIST library as well as reference substances. The clustering results of heat-map can better reflect the differences of phenolic compounds in different categories and subcategories of teas. Besides, the contents of hydrolyzable tannins, including galloylglucose, digalloylglucose, trigalloyglucose and strictinin, were positively correlated with the grades of green tea. The method validation and quantification results of exemplified five phenolic compounds in teas were also obtained, and LODs, LOQs and recoveries were ranging between 1.5-15.9 μg/mL, 5.1-53.1 μg/mL, and 79%-117.6%, respectively. Moreover, HPTLC-DESI-MS can save tenfold analytical time compared to HPLC-MS. Therefore, HPTLC-DESI-MS was a rapid, efficient characterization method of phenolic compounds in tea extracts.

Analytical performance of functional nanostructured biointerfaces for sensing phenolic compounds

Electrochemical biointerfaces are constructed with a wide range of nanomaterials and conducting polymers that strongly affect the analytical performance of biosensors. The analysis of progress toward electrochemical sensing platforms offers opportunities to provide devices for commercial use. The investigation of different methods for the synthesis of phenol biointerfaces leads to design challenges in the field of monitoring phenolic compounds. This paper review the innovative strategies and feature techniques in the construction of phenolic compound biosensors. The focus was made on the preparation methods of nanostructures and nanomaterials design for catalytic improvements of sensing interfaces. The paper also provides a comprehensive overview in the field of enzyme immobilization approaches at solid supports and technical formation of polymer nanocomposites, as well as applications of hybrid organic-inorganic nanocomposites in phenolic biosensors. This review also highlights the recent progress in the electrochemical detection of phenolic compounds and summarizes analytical performance parameters including sensitivity, storage stability, limit of detection, linear range, and Michaelis-Menten kinetic analysis. It also emphasizes advances from the past decade including technical challenges for the construction of suitable biointerfaces for monitoring phenolic compounds.

Data-Driven Modeling of Smartphone-Based Electrochemiluminescence Sensor Data Using Artificial Intelligence

Understanding relationships among multimodal data extracted from a smartphone-based electrochemiluminescence (ECL) sensor is crucial for the development of low-cost point-of-care diagnostic devices. In this work, artificial intelligence (AI) algorithms such as random forest (RF) and feedforward neural network (FNN) are used to quantitatively investigate the relationships between the concentration of Ru(bpy)32+ luminophore and its experimentally measured ECL and electrochemical data. A smartphone-based ECL sensor with Ru(bpy)32+/TPrA was developed using disposable screen-printed carbon electrodes. ECL images and amperograms were simultaneously obtained following 1.2-V voltage application. These multimodal data were analyzed by RF and FNN algorithms, which allowed the prediction of Ru(bpy)32+ concentration using multiple key features. High correlation (0.99 and 0.96 for RF and FNN, respectively) between actual and predicted values was achieved in the detection range between 0.02 µM and 2.5 µM. The AI approaches using RF and FNN were capable of directly inferring the concentration of Ru(bpy)32+ using easily observable key features. The results demonstrate that data-driven AI algorithms are effective in analyzing the multimodal ECL sensor data. Therefore, these AI algorithms can be an essential part of the modeling arsenal with successful application in ECL sensor data modeling.