Pub Date : 2026-02-01Epub Date: 2026-01-02DOI: 10.1016/j.ijoes.2026.101280
Lunxiang Li , Xiaojun Xue , Haitao Qu , Feng Liu , Liqian Liu , Xiaoyong Chen , Ruize Xu
This study aims to enhance the corrosion resistance of Ni50 laser-clad coatings in high-concentration brine. The effects of molybdenum (Mo) addition at varying concentrations (2 wt%, 4 wt%, 6 wt%) on the microstructure, phase composition, and electrochemical corrosion behavior were systematically investigated. Results indicate that the phase composition primarily consists of γ-Ni solid solution with dispersed carbides and borides. Increasing Mo content enhances solid solution strengthening and friction coefficient. At 4 wt% Mo, the coating achieves peak hardness and optimal wear resistance. Crucially, elevated Mo content significantly improves corrosion resistance, with 6 wt% Mo exhibiting the optimal performance. XPS analysis confirms that Mo incorporation facilitates the formation of multivalent molybdenum oxides (MoO₂/MoO₃), reduces passive film defect density, and enhances its physical barrier properties and stability. This mechanism substantially improves the corrosion resistance of the coating in high-concentration brine.
{"title":"Corrosion resistance of molybdenum-modified Ni-50 laser-clad coatings on 45# steel in concentrated brine","authors":"Lunxiang Li , Xiaojun Xue , Haitao Qu , Feng Liu , Liqian Liu , Xiaoyong Chen , Ruize Xu","doi":"10.1016/j.ijoes.2026.101280","DOIUrl":"10.1016/j.ijoes.2026.101280","url":null,"abstract":"<div><div>This study aims to enhance the corrosion resistance of Ni50 laser-clad coatings in high-concentration brine. The effects of molybdenum (Mo) addition at varying concentrations (2 wt%, 4 wt%, 6 wt%) on the microstructure, phase composition, and electrochemical corrosion behavior were systematically investigated. Results indicate that the phase composition primarily consists of γ-Ni solid solution with dispersed carbides and borides. Increasing Mo content enhances solid solution strengthening and friction coefficient. At 4 wt% Mo, the coating achieves peak hardness and optimal wear resistance. Crucially, elevated Mo content significantly improves corrosion resistance, with 6 wt% Mo exhibiting the optimal performance. XPS analysis confirms that Mo incorporation facilitates the formation of multivalent molybdenum oxides (MoO₂/MoO₃), reduces passive film defect density, and enhances its physical barrier properties and stability. This mechanism substantially improves the corrosion resistance of the coating in high-concentration brine.</div></div>","PeriodicalId":13872,"journal":{"name":"International Journal of Electrochemical Science","volume":"21 2","pages":"Article 101280"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-29DOI: 10.1016/j.ijoes.2025.101274
Ihsan ulhaq Toor
The emerging field of artificial intelligence (AI) and machine learning (ML) has opened new frontiers in corrosion science, particularly in the design, screening and performance prediction of corrosion inhibitors. Traditional experimental and quantum chemical approaches, while reliable, are often time-consuming and limited by empirical correlations. AI and ML driven models now offer a data-intensive alternative capable of predicting inhibitor efficiency, adsorption behavior, and electrochemical response with remarkable precision. Here in this study, recent progress in applying AI and ML algorithms such as artificial neural networks, support vector machines, decision trees, and deep learning frameworks to predict corrosion inhibition efficiency, adsorption mechanisms, and electrochemical parameters derived from potentiodynamic and impedance measurements are critically examined. The study reviews the data foundation essential for AI workflows including quantum, electrochemical, and image-based descriptors along with classical (SVR, RF, ANN), deep-learning (3L-DMPNN, ChemBERTa), and hybrid quantum ML architectures for inhibition efficiency prediction. Emerging generative models like MoIGPT have demonstrated the ability to design molecules conditioned on factors such as performance and toxicity. Meanwhile, integrated AI Electrochemistry pipelines connect machine learning predictions directly to experimental validation through electrochemical impedance spectroscopy and potentiodynamic polarization techniques. Despite remarkable advances, challenges remain in data standardization, model interpretability, scalability, and sustainability. Addressing these bottlenecks through FAIR data infrastructure, explainable and trustworthy AI, and green computational practices, will be critical for realizing the long-term vision of fully autonomous, eco-conscious, and self-optimizing corrosion-management ecosystems.
{"title":"Artificial intelligence and machine learning in corrosion inhibitor design & development: Advances, challenges, and future perspectives","authors":"Ihsan ulhaq Toor","doi":"10.1016/j.ijoes.2025.101274","DOIUrl":"10.1016/j.ijoes.2025.101274","url":null,"abstract":"<div><div>The emerging field of artificial intelligence (AI) and machine learning (ML) has opened new frontiers in corrosion science, particularly in the design, screening and performance prediction of corrosion inhibitors. Traditional experimental and quantum chemical approaches, while reliable, are often time-consuming and limited by empirical correlations. AI and ML driven models now offer a data-intensive alternative capable of predicting inhibitor efficiency, adsorption behavior, and electrochemical response with remarkable precision. Here in this study, recent progress in applying AI and ML algorithms such as artificial neural networks, support vector machines, decision trees, and deep learning frameworks to predict corrosion inhibition efficiency, adsorption mechanisms, and electrochemical parameters derived from potentiodynamic and impedance measurements are critically examined. The study reviews the data foundation essential for AI workflows including quantum, electrochemical, and image-based descriptors along with classical (SVR, RF, ANN), deep-learning (3L-DMPNN, ChemBERTa), and hybrid quantum ML architectures for inhibition efficiency prediction. Emerging generative models like MoIGPT have demonstrated the ability to design molecules conditioned on factors such as performance and toxicity. Meanwhile, integrated AI Electrochemistry pipelines connect machine learning predictions directly to experimental validation through electrochemical impedance spectroscopy and potentiodynamic polarization techniques. Despite remarkable advances, challenges remain in data standardization, model interpretability, scalability, and sustainability. Addressing these bottlenecks through FAIR data infrastructure, explainable and trustworthy AI, and green computational practices, will be critical for realizing the long-term vision of fully autonomous, eco-conscious, and self-optimizing corrosion-management ecosystems.</div></div>","PeriodicalId":13872,"journal":{"name":"International Journal of Electrochemical Science","volume":"21 2","pages":"Article 101274"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145882448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-02DOI: 10.1016/j.ijoes.2025.101279
Jie Pan , Xi Huang , Haojun Jiang , Kun Cao
3-Hydroxy-2-naphthoylamide (HNA) was investigated in a 1 mol·L−1 hydrochloric acid solution using various techniques, including weight loss test, polarization curve analysis, electrochemical impedance spectroscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), and X-ray photoelectron spectroscopy (XPS). The electrochemical test revealed that the corrosion inhibition efficiency showed a gradual increase with increasing concentration, and achieved maximum inhibitory efficiencies of 94 % at a concentration of 10 mmol·L−1. HNA acted as a mixed-type corrosion inhibitors, primarily inhibiting anodic metal dissolution. The surface analysis of carbon steel using SEM, AFM, and XPS confirmed that the corrosion inhibitors adsorbed onto the metal surface, effectively separating the corrosion medium. The adsorption of the inhibitor followed the Langmuir isothermal adsorption model, further supporting their adsorption behavior on the metal surface.
{"title":"3-Hydroxy-2-naphthoylamide as corrosion inhibitor for carbon steel in 1 M HCl","authors":"Jie Pan , Xi Huang , Haojun Jiang , Kun Cao","doi":"10.1016/j.ijoes.2025.101279","DOIUrl":"10.1016/j.ijoes.2025.101279","url":null,"abstract":"<div><div>3-Hydroxy-2-naphthoylamide (HNA) was investigated in a 1 mol·L<sup>−1</sup> hydrochloric acid solution using various techniques, including weight loss test, polarization curve analysis, electrochemical impedance spectroscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), and X-ray photoelectron spectroscopy (XPS). The electrochemical test revealed that the corrosion inhibition efficiency showed a gradual increase with increasing concentration, and achieved maximum inhibitory efficiencies of 94 % at a concentration of 10 mmol·L<sup>−1</sup>. HNA acted as a mixed-type corrosion inhibitors, primarily inhibiting anodic metal dissolution. The surface analysis of carbon steel using SEM, AFM, and XPS confirmed that the corrosion inhibitors adsorbed onto the metal surface, effectively separating the corrosion medium. The adsorption of the inhibitor followed the Langmuir isothermal adsorption model, further supporting their adsorption behavior on the metal surface.</div></div>","PeriodicalId":13872,"journal":{"name":"International Journal of Electrochemical Science","volume":"21 2","pages":"Article 101279"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145882450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-26DOI: 10.1016/j.ijoes.2025.101277
Yingnan Zhang , Ying Liu , Yunyao Jiang , Liang Zhou , Shubao Yang
In this work, a novel carbon nanotube-polyaniline (PANI@CNTs) composite electrode-based sensor for the detection of β-glucans, an edible polysaccharide found in mushrooms, is introduced. The sensor offers excellent sensitivity, selectivity, and quick reaction times by utilizing the special qualities of electrochemical sensing in conjunction with nanostructures. The collaborative enhancement mechanism of the sensor is achieved through the distinct and synergistic roles of each component: β-glucanase (βg) selectively hydrolyzes β-glucan into glucose, glucose oxidase (GOx) catalyzes the oxidation of glucose to gluconic acid and H2O2 to amplify the electrochemical signal, while carbon nanotubes (CNTs) provide a high surface area and fast electron transfer pathways, and polyaniline (PANI) offers a conductive and biocompatible matrix for stable enzyme immobilization. An electropolymerization process yields a nanocomposite of PANI and CNTs for the modified electrode, immobilizing the enzymes βg and GOx. The effective production of the composite and the immobilization of the enzyme are confirmed by structural analysis. The βg/GOx/PANI@CNTs/GCE sensor shows a strong cathodic peak for β-glucan reduction and quasi-reversible redox peaks, with a linear increase in peak current matching to β-glucan concentration, according to electrochemical tests. The limit of detection (LOD) of the sensor is set at 9 ng/mL, its sensitivity is 0.616 µA/µg. mL−1, and the linear concentration range is 0.5–52 µg/mL. It has exceptional durability, repeatability, and selectivity. Real sample testing shows recovery rates ranging from 97.00 % to 99.00 %, indicating the sensor's accuracy and reliability. After 27 days, the sensor maintained 96.95 % of its initial catalytic activity, demonstrating exceptional stability. The results indicate that the βg/GOx/PANI@CNTs/GCE sensor has great potential for quality control in the pharmaceutical and food sectors.
{"title":"Carbon nanotube–polyaniline (PANI@CNTs) composite electrode-based enzymatic sensor for β-glucan detection","authors":"Yingnan Zhang , Ying Liu , Yunyao Jiang , Liang Zhou , Shubao Yang","doi":"10.1016/j.ijoes.2025.101277","DOIUrl":"10.1016/j.ijoes.2025.101277","url":null,"abstract":"<div><div>In this work, a novel carbon nanotube-polyaniline (PANI@CNTs) composite electrode-based sensor for the detection of β-glucans, an edible polysaccharide found in mushrooms, is introduced. The sensor offers excellent sensitivity, selectivity, and quick reaction times by utilizing the special qualities of electrochemical sensing in conjunction with nanostructures. The collaborative enhancement mechanism of the sensor is achieved through the distinct and synergistic roles of each component: β-glucanase (βg) selectively hydrolyzes β-glucan into glucose, glucose oxidase (GOx) catalyzes the oxidation of glucose to gluconic acid and H<sub>2</sub>O<sub>2</sub> to amplify the electrochemical signal, while carbon nanotubes (CNTs) provide a high surface area and fast electron transfer pathways, and polyaniline (PANI) offers a conductive and biocompatible matrix for stable enzyme immobilization. An electropolymerization process yields a nanocomposite of PANI and CNTs for the modified electrode, immobilizing the enzymes βg and GO<sub>x</sub>. The effective production of the composite and the immobilization of the enzyme are confirmed by structural analysis. The βg/GOx/PANI@CNTs/GCE sensor shows a strong cathodic peak for β-glucan reduction and quasi-reversible redox peaks, with a linear increase in peak current matching to β-glucan concentration, according to electrochemical tests. The limit of detection (LOD) of the sensor is set at 9 ng/mL, its sensitivity is 0.616 µA/µg. mL<sup>−1</sup>, and the linear concentration range is 0.5–52 µg/mL. It has exceptional durability, repeatability, and selectivity. Real sample testing shows recovery rates ranging from 97.00 % to 99.00 %, indicating the sensor's accuracy and reliability. After 27 days, the sensor maintained 96.95 % of its initial catalytic activity, demonstrating exceptional stability. The results indicate that the β<sub>g</sub>/GO<sub>x</sub>/PANI@CNTs/GCE sensor has great potential for quality control in the pharmaceutical and food sectors.</div></div>","PeriodicalId":13872,"journal":{"name":"International Journal of Electrochemical Science","volume":"21 2","pages":"Article 101277"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-04DOI: 10.1016/j.ijoes.2026.101283
Li Jin , Ertao Lei , Junkun Zhang , Kai Ma , Quanhui Li , Xiaoxue Yan , Feng Li
In recent years, with the rapid development of the new energy industry, the scale of new energy storage facilities centered around lithium-ion batteries has continued to climb. Additionally, there have been several significant safety incidents in energy storage power plants across the globe in recent years, raising concerns for the industry. It is worth noting that the widely used traditional Battery Management Systems (BMS) can only detect the structural integrity and physical parameter abnormalities of the battery, which has obvious monitoring limitations and cannot detect condensation inside of the battery pack. In this paper, we propose an Edge Aware Instance Segmentation Network (EAIS-Net) based on the visual features of condensation inside of battery packs. Specifically, the proposed EAIS-Net is used to enhance the perception ability of condensation phenomenon in battery images, and its core components is the Edge Perception Module (EPM). EPM is committed to enhancing the blurred edge structure of condensation on the surface of battery cell caused by factors such as light exposure and scattering, highlighting the edge characteristics of condensation. The proposed algorithm can provide early warning for energy storage power plants, and experimental results show that the proposed network is superior to other advanced algorithms.
{"title":"Design of a visual detection algorithm for condensation inside energy-storage lithium-ion battery packs","authors":"Li Jin , Ertao Lei , Junkun Zhang , Kai Ma , Quanhui Li , Xiaoxue Yan , Feng Li","doi":"10.1016/j.ijoes.2026.101283","DOIUrl":"10.1016/j.ijoes.2026.101283","url":null,"abstract":"<div><div>In recent years, with the rapid development of the new energy industry, the scale of new energy storage facilities centered around lithium-ion batteries has continued to climb. Additionally, there have been several significant safety incidents in energy storage power plants across the globe in recent years, raising concerns for the industry. It is worth noting that the widely used traditional Battery Management Systems (BMS) can only detect the structural integrity and physical parameter abnormalities of the battery, which has obvious monitoring limitations and cannot detect condensation inside of the battery pack. In this paper, we propose an Edge Aware Instance Segmentation Network (EAIS-Net) based on the visual features of condensation inside of battery packs. Specifically, the proposed EAIS-Net is used to enhance the perception ability of condensation phenomenon in battery images, and its core components is the Edge Perception Module (EPM). EPM is committed to enhancing the blurred edge structure of condensation on the surface of battery cell caused by factors such as light exposure and scattering, highlighting the edge characteristics of condensation. The proposed algorithm can provide early warning for energy storage power plants, and experimental results show that the proposed network is superior to other advanced algorithms.</div></div>","PeriodicalId":13872,"journal":{"name":"International Journal of Electrochemical Science","volume":"21 2","pages":"Article 101283"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-23DOI: 10.1016/j.ijoes.2025.101275
Qiaoling Zheng , Jiang Zhu
Vigorous physical activity disrupts cellular redox homeostasis by increasing the production of reactive oxygen species (ROS), which act both as potential mediators of damage and as essential signals for exercise adaptation. This review summarizes current knowledge of the main ROS sources during high-intensity exercise and critically assesses electroanalytical strategies for monitoring their dynamics in vivo. We outline how mitochondrial electron leakage, NADPH oxidase activity and xanthine oxidase flux generate rapid, compartment-specific ROS bursts that are shaped by endogenous antioxidant networks. We then compare conventional indirect assays with emerging electrochemical approaches, highlighting how enzyme-modified microelectrodes, nanostructured redox interfaces and wearable electrochemical biosensors enable real-time, site-specific ROS quantification with improved sensitivity and selectivity. These advances have revealed new spatiotemporal patterns of ROS generation and helped clarify the dose–response relationship between exercise intensity, oxidative stress and redox signaling. Finally, we discuss translational opportunities and remaining challenges for electroanalytical ROS sensing in exercise science, including calibration in complex biological matrices, biofouling control and long-term stability in continuous monitoring formats.
{"title":"Advances in electroanalytical detection of reactive oxygen species during intense physical exercise","authors":"Qiaoling Zheng , Jiang Zhu","doi":"10.1016/j.ijoes.2025.101275","DOIUrl":"10.1016/j.ijoes.2025.101275","url":null,"abstract":"<div><div>Vigorous physical activity disrupts cellular redox homeostasis by increasing the production of reactive oxygen species (ROS), which act both as potential mediators of damage and as essential signals for exercise adaptation. This review summarizes current knowledge of the main ROS sources during high-intensity exercise and critically assesses electroanalytical strategies for monitoring their dynamics in vivo. We outline how mitochondrial electron leakage, NADPH oxidase activity and xanthine oxidase flux generate rapid, compartment-specific ROS bursts that are shaped by endogenous antioxidant networks. We then compare conventional indirect assays with emerging electrochemical approaches, highlighting how enzyme-modified microelectrodes, nanostructured redox interfaces and wearable electrochemical biosensors enable real-time, site-specific ROS quantification with improved sensitivity and selectivity. These advances have revealed new spatiotemporal patterns of ROS generation and helped clarify the dose–response relationship between exercise intensity, oxidative stress and redox signaling. Finally, we discuss translational opportunities and remaining challenges for electroanalytical ROS sensing in exercise science, including calibration in complex biological matrices, biofouling control and long-term stability in continuous monitoring formats.</div></div>","PeriodicalId":13872,"journal":{"name":"International Journal of Electrochemical Science","volume":"21 2","pages":"Article 101275"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145839362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-02DOI: 10.1016/j.ijoes.2026.101281
Yongxiang Zhang , Ye Zhang
The integrity of competitive sports is perpetually challenged by the illicit use of performance-enhancing drugs. While laboratory-based methods like mass spectrometry represent the gold standard for confirmatory analysis, their inherent limitations in terms of cost, complexity, and turnaround time preclude their use for widespread, on-site screening. Electrochemical sensors have emerged as a powerful alternative, offering the potential for rapid, portable, and low-cost detection. This paradigm shift has been significantly accelerated by the advent of two-dimensional (2D) materials, whose unique physicochemical properties provide an ideal platform for developing next-generation sensing devices. This review provides a comprehensive and critical analysis of the application of 2D materials, including the graphene family, transition metal dichalcogenides (TMDs), and MXenes, in electrochemical sensors for detecting various classes of doping agents. Representative 2D-material-based platforms already achieve figures of merit compatible with anti-doping requirements, with rGO/CTAB-modified electrodes detecting testosterone down to 0.1 nM in urine and blood, MXene Ti₃C₂Tₓ–Fe₂O₃ aptasensors reaching limits of detection as low as 1.53 pg/mL across clinically relevant concentration ranges, and graphene-based stimulant sensors delivering stable electrochemical readouts from complex samples within tens of seconds to a few minutes. We critically examine the core arguments, controversies, and supporting evidence surrounding the performance of each material class, focusing on the intrinsic trade-offs between conductivity, functionalizability, and environmental stability. Furthermore, we delve into the overarching challenges that impede the transition from laboratory prototypes to field-deployable devices, namely the difficulties in scalable and reproducible material synthesis, the pervasive issue of biofouling in complex biological matrices, and the imperative for achieving high selectivity. Strategic solutions, including advanced surface modification techniques and the integration of specific molecular recognition elements like aptamers and molecularly imprinted polymers, are discussed in detail. Finally, we explore the future trajectory of the field, highlighting the integration of 2D material sensors into advanced systems such as wearable devices and microfluidic platforms, the development of multiplexed sensor arrays for simultaneous multi-analyte detection, and the transformative role of machine learning in processing complex sensor data to deliver actionable insights. The convergence of these technologies promises to revolutionize anti-doping enforcement, shifting the paradigm from reactive, post-competition testing to proactive, continuous monitoring to safeguard the health of athletes and ensure fair play.
{"title":"Applications and challenges of graphene, MXenes, and transition metal dichalcogenides in electrochemical sensors for doping detection","authors":"Yongxiang Zhang , Ye Zhang","doi":"10.1016/j.ijoes.2026.101281","DOIUrl":"10.1016/j.ijoes.2026.101281","url":null,"abstract":"<div><div>The integrity of competitive sports is perpetually challenged by the illicit use of performance-enhancing drugs. While laboratory-based methods like mass spectrometry represent the gold standard for confirmatory analysis, their inherent limitations in terms of cost, complexity, and turnaround time preclude their use for widespread, on-site screening. Electrochemical sensors have emerged as a powerful alternative, offering the potential for rapid, portable, and low-cost detection. This paradigm shift has been significantly accelerated by the advent of two-dimensional (2D) materials, whose unique physicochemical properties provide an ideal platform for developing next-generation sensing devices. This review provides a comprehensive and critical analysis of the application of 2D materials, including the graphene family, transition metal dichalcogenides (TMDs), and MXenes, in electrochemical sensors for detecting various classes of doping agents. Representative 2D-material-based platforms already achieve figures of merit compatible with anti-doping requirements, with rGO/CTAB-modified electrodes detecting testosterone down to 0.1 nM in urine and blood, MXene Ti₃C₂Tₓ–Fe₂O₃ aptasensors reaching limits of detection as low as 1.53 pg/mL across clinically relevant concentration ranges, and graphene-based stimulant sensors delivering stable electrochemical readouts from complex samples within tens of seconds to a few minutes. We critically examine the core arguments, controversies, and supporting evidence surrounding the performance of each material class, focusing on the intrinsic trade-offs between conductivity, functionalizability, and environmental stability. Furthermore, we delve into the overarching challenges that impede the transition from laboratory prototypes to field-deployable devices, namely the difficulties in scalable and reproducible material synthesis, the pervasive issue of biofouling in complex biological matrices, and the imperative for achieving high selectivity. Strategic solutions, including advanced surface modification techniques and the integration of specific molecular recognition elements like aptamers and molecularly imprinted polymers, are discussed in detail. Finally, we explore the future trajectory of the field, highlighting the integration of 2D material sensors into advanced systems such as wearable devices and microfluidic platforms, the development of multiplexed sensor arrays for simultaneous multi-analyte detection, and the transformative role of machine learning in processing complex sensor data to deliver actionable insights. The convergence of these technologies promises to revolutionize anti-doping enforcement, shifting the paradigm from reactive, post-competition testing to proactive, continuous monitoring to safeguard the health of athletes and ensure fair play.</div></div>","PeriodicalId":13872,"journal":{"name":"International Journal of Electrochemical Science","volume":"21 2","pages":"Article 101281"},"PeriodicalIF":2.4,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145882487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2025-12-08DOI: 10.1016/j.ijoes.2025.101267
Chun-Jern Pan , Yi-Yu Chen , Shih-Che Lin , Bing-Joe Hwang , Chia-Hsin Wang , Chun-I. Lee
Lithium metal batteries have shown great potential in energy storage applications, and the development of novel electrolytes provide new opportunities to enhance their performance. This study proposes an innovative dual-lithium-salt electrolyte composed of lithium nitrate (LiNO3) and lithium bis(oxalato)borate (LiBOB) in sulfolane solvent. The electrolyte exhibits high Li plating/stripping reversibility and stability, effectively improving electrode interfacial compatibility. The introduction of LiBOB regulates the solvation structure, optimizes lithium-ion transport, and promotes the formation of a robust solid electrolyte interphase, which is crucial for interfacial stability and prolonged battery life. NMR spectra reveal that oxygen-rich groups in bis(oxalato)borate anion (BOB-) participate in Li+ solvation, increasing electron cloud density. This structural reorganization facilitates Li+ dissociation and further improves ionic conductivity. The electrolyte maintains stable Li plating/stripping voltage profiles with significantly lower polarization over long-term cycling in Li//Li cells, demonstrating smooth Li+ transport and stable interfaces that suppress dendrite growth and impedance rise. In Li//Cu cell, the electrolyte achieves an average coulombic efficiency of 97.85 %, showing high reversibility and stable interfacial behavior. Furthermore, in the Li//LiMn2O4 half-cell tests, the electrolyte demonstrated outstanding performance under various operating conditions. It achieved stable cycling for 680 cycles at 100 mA g−1 while maintaining an average coulombic efficiency of 99.2 % and a capacity retention of 84.54 %. Even at a high current rate of 500 mA g−1, the cell continued to operate stably for more than 260 cycles with a coulombic efficiency of approximately 99.2 %. Under elevated-temperature conditions of 60 °C, the electrolyte also exhibited excellent cycling stability and thermal tolerance. Overall, the novel electrolyte combines high ionic conductivity, superior thermal and electrochemical stability, and long cycling life, confirming its potential as a safe and high-performance electrolyte candidate for lithium metal batteries.
锂金属电池在储能应用中显示出巨大的潜力，新型电解质的开发为提高其性能提供了新的机遇。本研究提出了一种在亚砜溶剂中由硝酸锂（LiNO3）和硼酸锂（LiBOB）组成的新型双锂盐电解质。该电解质具有较高的镀/剥离锂的可逆性和稳定性，有效地改善了电极界面相容性。LiBOB的引入调节了溶剂化结构，优化了锂离子的输运，促进了坚固的固体电解质界面相的形成，这对界面稳定性和延长电池寿命至关重要。核磁共振谱显示，硼酸铋阴离子（BOB-）中的富氧基团参与Li+溶剂化，增加了电子云密度。这种结构重组有利于Li+解离，进一步提高离子电导率。电解质在Li//Li电池中长期循环时保持稳定的镀/剥离电压分布，极化显著降低，显示出Li+的平滑传输和稳定的界面，抑制枝晶生长和阻抗上升。在Li//Cu电池中，电解质的平均库仑效率为97.85 %，具有较高的可逆性和稳定的界面行为。此外，在Li//LiMn2O4半电池测试中，电解质在各种操作条件下都表现出优异的性能。在100 mA g−1下稳定循环680次，平均库仑效率为99.2% %，容量保持率为84.54 %。即使在500 mA g−1的高电流下，电池也能以约99.2% %的库仑效率持续稳定运行260多个循环。在60℃的高温条件下，电解质也表现出良好的循环稳定性和耐热性。总的来说，这种新型电解质结合了高离子电导率、优异的热稳定性和电化学稳定性以及长循环寿命，证实了其作为锂金属电池安全和高性能电解质候选材料的潜力。
{"title":"Lithium nitrate/Lithium bis(oxalate)borate dual-salt in sulfolane as nonflammable electrolyte for stable lithium-metal batteries","authors":"Chun-Jern Pan , Yi-Yu Chen , Shih-Che Lin , Bing-Joe Hwang , Chia-Hsin Wang , Chun-I. Lee","doi":"10.1016/j.ijoes.2025.101267","DOIUrl":"10.1016/j.ijoes.2025.101267","url":null,"abstract":"<div><div>Lithium metal batteries have shown great potential in energy storage applications, and the development of novel electrolytes provide new opportunities to enhance their performance. This study proposes an innovative dual-lithium-salt electrolyte composed of lithium nitrate (LiNO<sub>3</sub>) and lithium bis(oxalato)borate (LiBOB) in sulfolane solvent. The electrolyte exhibits high Li plating/stripping reversibility and stability, effectively improving electrode interfacial compatibility. The introduction of LiBOB regulates the solvation structure, optimizes lithium-ion transport, and promotes the formation of a robust solid electrolyte interphase, which is crucial for interfacial stability and prolonged battery life. NMR spectra reveal that oxygen-rich groups in bis(oxalato)borate anion (BOB<sup>-</sup>) participate in Li<sup>+</sup> solvation, increasing electron cloud density. This structural reorganization facilitates Li<sup>+</sup> dissociation and further improves ionic conductivity. The electrolyte maintains stable Li plating/stripping voltage profiles with significantly lower polarization over long-term cycling in Li//Li cells, demonstrating smooth Li<sup>+</sup> transport and stable interfaces that suppress dendrite growth and impedance rise. In Li//Cu cell, the electrolyte achieves an average coulombic efficiency of 97.85 %, showing high reversibility and stable interfacial behavior. Furthermore, in the Li//LiMn<sub>2</sub>O<sub>4</sub> half-cell tests, the electrolyte demonstrated outstanding performance under various operating conditions. It achieved stable cycling for 680 cycles at 100 mA g<sup>−1</sup> while maintaining an average coulombic efficiency of 99.2 % and a capacity retention of 84.54 %. Even at a high current rate of 500 mA g<sup>−1</sup>, the cell continued to operate stably for more than 260 cycles with a coulombic efficiency of approximately 99.2 %. Under elevated-temperature conditions of 60 °C, the electrolyte also exhibited excellent cycling stability and thermal tolerance. Overall, the novel electrolyte combines high ionic conductivity, superior thermal and electrochemical stability, and long cycling life, confirming its potential as a safe and high-performance electrolyte candidate for lithium metal batteries.</div></div>","PeriodicalId":13872,"journal":{"name":"International Journal of Electrochemical Science","volume":"21 1","pages":"Article 101267"},"PeriodicalIF":2.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145733569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Diroximel fumarate (DRF) is a new oral fumarate applied in the treatment of multiple sclerosis (MS). The present work introduces a new method for the detection of DRF drugs through a molecularly imprinted polymer (MIP). The MIP was synthesized on the glassy carbon electrode (GCE) using the electropolymerization of monomer α‑cyclodextrin (α-CD) and the DRF template. In this sense, an electrochemical sensor incorporating a MIP was designed particularly to detect DRF for the first time. The modified GCE was investigated via differential pulse voltammetry (DPV), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and scanning electron microscopy (SEM). The designed sensor provided acceptable selectivity, reproducibility, repeatability, and stability. Additionally, the modified electrode showed a good linear response from 0.01 to 1300 nM with a low detection limit (LOD) of 0.0033 nM. The MIP/GCE was applied for DRF detection in a real sample with success. To find out the reliability of the proposed strategy, high performance liquid chromatography (HPLC) technique was employed to detect DRF in the real sample.
{"title":"Electrochemical detection of diroximel fumarate using an α-cyclodextrin-based molecularly imprinted polymer sensor in human serum","authors":"Mahmoud Roushani , Zahra Mirzaei Karazan , Husam Jalil Abdulkahim","doi":"10.1016/j.ijoes.2025.101265","DOIUrl":"10.1016/j.ijoes.2025.101265","url":null,"abstract":"<div><div>Diroximel fumarate (DRF) is a new oral fumarate applied in the treatment of multiple sclerosis (MS). The present work introduces a new method for the detection of DRF drugs through a molecularly imprinted polymer (MIP). The MIP was synthesized on the glassy carbon electrode (GCE) using the electropolymerization of monomer α‑cyclodextrin (α-CD) and the DRF template. In this sense, an electrochemical sensor incorporating a MIP was designed particularly to detect DRF for the first time. The modified GCE was investigated via differential pulse voltammetry (DPV), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and scanning electron microscopy (SEM). The designed sensor provided acceptable selectivity, reproducibility, repeatability, and stability. Additionally, the modified electrode showed a good linear response from 0.01 to 1300 nM with a low detection limit (LOD) of 0.0033 nM. The MIP/GCE was applied for DRF detection in a real sample with success. To find out the reliability of the proposed strategy, high performance liquid chromatography (HPLC) technique was employed to detect DRF in the real sample.</div></div>","PeriodicalId":13872,"journal":{"name":"International Journal of Electrochemical Science","volume":"21 1","pages":"Article 101265"},"PeriodicalIF":2.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145733571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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