Hasil untuk "Industrial electrochemistry"

Samantha Michelle Gateman, O. Gharbi, H. G. de Melo et al.

Several techniques can be used to experimentally determine the interfacial capacitance of an electrode, which is a crucial parameter used for quantifying the efficiency of super-capacitors. However, the values obtained from cyclic voltam-metry can be significantly different from those extracted from electrochemical impedance spectroscopy analysis. This is particularly due to the fact that the interface does not behave like an ideal (i

A.P. Rethickshaa, T. Priyadharshini, A.V. Ravindra

Cobalt benzene dicarboxylic acid (Co-BDC) metal-organic frameworks (MOFs), exhibiting superior hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) activities, are synthesized under solvothermal conditions both in the absence (CoB) and presence (CoB-W) of a water modulator. The electrocatalytic performances of these materials are systematically compared to elucidate the effect of the modulator. The incorporation of water as a green modulator significantly influences the crystal morphology and defect formation. X-ray diffraction (XRD) patterns of CoB and CoB-W match well with the simulated profiles, confirming the phase purity, while Fourier-transform infrared (FTIR) spectroscopy reveals the modulation-induced variation in the electronic structure of CoB-W. UV–Vis spectroscopy indicates narrow band gaps of 2.39 eV and 2.48 eV for CoB and CoB-W, respectively. Scanning electron microscopy (SEM) further confirms distinct morphological changes upon modulation. Electrochemical studies demonstrate that CoB-W exhibits an overpotential of 452 mV for OER and 211 mV for HER at a current density of 10 mA/cm2 in 1 M KOH, with corresponding Tafel slopes of 90 and 80 mV/dec. Moreover, CoB-W shows excellent HER performance characterized by low overpotential, high current density, and remarkable stability over 15 h of continuous operation. This study establishes a clear structure-property-performance correlation, highlighting the role of water as an effective and eco-friendly modulator in tailoring Co-BDC MOFs for high-efficiency bifunctional electrocatalysis toward sustainable energy conversion.

L. Kavan

This paper reviews selected problems, which appear in literature dealing with TiO_2, SnO_2, and ZnO. Some of them have more universal impact to semiconductor electrochemistry. The electronic band structure is a key for understanding fundamental properties and for rational design of applications, but the uncertainty of specific values determined experimentally or by theoretical calculations should not be ignored. The inappropriate use of Mott-Schottky plot for characterization of certain semiconductor electrodes is another source of problems. Some other technical and formal issues in research and development of semiconductors are discussed.

Michael A. Pence, Gavin Hazen, Joaquín Rodríguez-López

A. Mota-Lima

Plasma water treatment has emerged as a powerful technology capable of abate perfluoroalkyl substances (PFAS) in water matrices. With the electrochemical configuration and cathodic polarity, the electrified plasma/liquid interface (EPLI) not only produces in-situ hydrated electrons ( ) that readily react with PFAS, but also produced radicals in the plasma effluent. This study uses chemical reaction networks (CRN) to investigate the chemical pathways of PFAS degradation by EPLI-induced , allowing for a direct comparison with the bench experiments of Stratton et al. (Environ. Sci. Technol. 2017, 51, 3, 1643) and Alam et al. (Chemical Engineering Journal, 2024, 489, 151349). The computational results indicate that Perfluorooctanoic Acid (PFOA) degradation by EPLI-induced  has a Faradaic efficiency of less than 0.01% given the typically low concentration of PFOA in water matrices, meaning that the majority of  engages with water reduction, generating gaseous hydrogen. EPLI-induced  alone cannot account for the energy efficiency observed in bench experiment of Stratton et al. and Alam et al., suggesting the presence of other plasma-induced radicals. This work evaluates the gas-phase H radical as crucial for degrading PFOA at the gas/liquid interface, which is created by the plasma effluent in contact with the water matrix. This work paves the way for construct effective plasma-based industrial reactors to degrade PFAS, suggesting the formation of radical-H in the plasma effluent as a key parameter to be optimized.

Marcos Soto

In industrial environments, data acquisition accuracy is crucial for process control and optimization. Wireless telemetry has proven to be a valuable tool for improving efficiency in well-testing operations, enabling bidirectional communication and real-time control of downhole tools. However, high sampling frequencies present challenges in telemetry, including data storage, transmission, computational resource consumption, and battery life of wireless devices. This study explores how optimizing data acquisition strategies can reduce aliasing effects and systematic errors while improving sampling rates without compromising measurement accuracy. A reduction of 80% in sampling frequency was achieved without degrading measurement quality, demonstrating the potential for resource optimization in industrial environments.

Christian Internò, Andrea Castellani, Sebastian Schmitt et al.

Industrial Non-Intrusive Load Monitoring (NILM) is limited by the scarcity of high-quality datasets and the complex variability of industrial energy consumption patterns. To address data scarcity and privacy issues, we introduce the Synthetic Industrial Dataset for Energy Disaggregation (SIDED), an open-source dataset generated using Digital Twin simulations. SIDED includes three types of industrial facilities across three different geographic locations, capturing diverse appliance behaviors, weather conditions, and load profiles. We also propose the Appliance-Modulated Data Augmentation (AMDA) method, a computationally efficient technique that enhances NILM model generalization by intelligently scaling appliance power contributions based on their relative impact. We show in experiments that NILM models trained with AMDA-augmented data significantly improve the disaggregation of energy consumption of complex industrial appliances like combined heat and power systems. Specifically, in our out-of-sample scenarios, models trained with AMDA achieved a Normalized Disaggregation Error of 0.093, outperforming models trained without data augmentation (0.451) and those trained with random data augmentation (0.290). Data distribution analyses confirm that AMDA effectively aligns training and test data distributions, enhancing model generalization.

Marcos Lima Romero, Ricardo Suyama

The recent development of Agentic AI systems, empowered by autonomous large language models (LLMs) agents with planning and tool-usage capabilities, enables new possibilities for the evolution of industrial automation and reduces the complexity introduced by Industry 4.0. This work proposes a conceptual framework that integrates Agentic AI with the intent-based paradigm, originally developed in network research, to simplify human-machine interaction (HMI) and better align automation systems with the human-centric, sustainable, and resilient principles of Industry 5.0. Based on the intent-based processing, the framework allows human operators to express high-level business or operational goals in natural language, which are decomposed into actionable components. These intents are broken into expectations, conditions, targets, context, and information that guide sub-agents equipped with specialized tools to execute domain-specific tasks. A proof of concept was implemented using the CMAPSS dataset and Google Agent Developer Kit (ADK), demonstrating the feasibility of intent decomposition, agent orchestration, and autonomous decision-making in predictive maintenance scenarios. The results confirm the potential of this approach to reduce technical barriers and enable scalable, intent-driven automation, despite data quality and explainability concerns.

Jiaqi Li, Xizhong Guo, Yang Zhao et al.

Rapid industrial digitalization has created intricate cybersecurity demands that necessitate effective validation methods. While cyber ranges and simulation platforms are widely deployed, they frequently face limitations in scenario diversity and creation efficiency. In this paper, we present SpiderSim, a theoretical cybersecurity simulation platform enabling rapid and lightweight scenario generation for industrial digitalization security research. At its core, our platform introduces three key innovations: a structured framework for unified scenario modeling, a multi-agent collaboration mechanism for automated generation, and modular atomic security capabilities for flexible scenario composition. Extensive implementation trials across multiple industrial digitalization contexts, including marine ranch monitoring systems, validate our platform's capacity for broad scenario coverage with efficient generation processes. Built on solid theoretical foundations and released as open-source software, SpiderSim facilitates broader research and development in automated security testing for industrial digitalization.

Dr. Rosalba A. Rincón

José Gabriel O. Pinto, João P. D. Miranda, Luis A. M. Barros et al.

This paper presents the design, implementation and experimental validation of a modular battery management system (BMS) featuring active cell balancing. The proposed BMS consists of a master module and multiple slave submodules responsible for monitoring and balancing 22 cells connected in series. The master module collects voltage and temperature data from the slave submodules and measures the battery current to estimate the cells’ state of charge (SoC). Each slave module performs cell voltage and temperature measurements and controls a balancing circuit based on dc-dc converters. This work describes in detail the development and validation of the dc-dc converter based in the switched inductor topology, presenting the converter’s operational principles, a theoretical and simulation-based analysis of its performance, the implementation of the MOSFETs driver circuits based on PNP transistors and experimental results obtained from a submodule prototype. The results demonstrate the capability of the switched inductor converter to achieve effective voltage equalization by transferring energy from the cells with higher voltages to cells with lower voltages.

Yao Yang, J. Feijóo, V. Briega-Martos et al.

Shamsa Munir, Bakhtiar Ali, Salma Gul

3D-printed electrodes (3DPEs) have ushered in a new era of possibilities in electrochemical applications resulting in groundbreaking research in electrochemistry. This review explores the exceptional potential of 3DPEs in transforming the fields of electrochemical sensing, electro-catalysis, and energy storage. As sensors, these electrodes offer great flexibility and customization, allowing for the manufacturing of highly sensitive and selective sensors. 3D printing technology has enabled precise control of the electrode's geometry and surface properties resulting in enhanced signal transduction and improved analytical performance. The 3DPEs have also evolved as promising electro-catalysts, particularly for hydrogen evolution reaction and CO2 reduction in aqueous solutions. The control over reaction kinetics and product formation can be achieved through the fabrication of intricate catalytic designs employing 3D printing. When used in batteries and supercapacitors, these electrodes manifest distinctive properties, such as high surface area and porous structures, making them ideal candidates for energy storage applications. They provide higher energy densities, faster-charging rates, and longer cycle life. Thus, the unique features, customizable designs, and enhanced performance of 3DPEs have driven advancements in sensing, catalysis, and energy storage, creating exciting opportunities for their application in the field of electrochemistry.

D. Bograchev, T. Kabanova, A. Davydov

Yuhan Xing, Yingyue Yin, Fulan Wei et al.

K. L. Vernon, T. Pungsrisai, O. Wahab et al.

We demonstrate the application and benefit of optically transparent carbon electrodes (OTCEs) for single entity nanoelectrochemistry. OTCEs are prepared by pyrolyzing thin photoresist films on fused quartz coverslips to create conductive, transparent, thin films. Optical, electrical, topographical, and electrochemical properties of OTCEs are characterized to evaluate their suitability for single entity electrochemistry. Nanoscale electrochemical imaging of the OTCEs using scanning electrochemical cell microscopy (SECCM) revealed uniform electrochemical activity for reduction of the hexaammineruthenium(III) redox complex, that was comparable to Au-coated glass, and in contrast to the heterogeneity observed with commonly used indium tin oxide (ITO) substrates. Additionally, we demonstrate the utility of the prepared OTCEs for correlative SECCM—scanning electron microscopy studies of the hydrogen evolution reaction at the surface of Au nanocubes. Lastly, we demonstrate the benefit of OTCEs for optoelectrochemical experiments by optically monitoring the electrodissolution of Au nanocrystals. These results establish OTCE as a viable transparent support electrode for multimode electrochemical and optical microscopy of nanocrystals and other entities.

Kayvan Moradi, Marko M. Melander

Semiconductor electrodes (SCEs) play a decisive role in e.g. clean energy conversion technologies but understanding their complex electrochemistry remains an outstanding challenge. Herein, we review electronic structure meth-ods for describing the applied electrode potential in simulations of semiconductor-electrolyte interfaces. We emphasize that inclusion of the electrode potential is significantly more challenging for SCEs than for metallic electrodes because SCEs require accurate models of semiconductor capacitance, including the space-charge region and surface effects, as well as the electrolyte double-layer capacitance. We discuss how these physicochemical complications challenge the development of atomistic models of SCE and how they impact the applicability of the computational hydrogen electrode, capacitance correction, grand canonical DFT, and Green function methods to model SCEs. We highlight the need for continued methodological development and conclude that integrating advanced atomistic models of SCEs with grand canonical, constant inner potential DFT or Green function methods holds promise for accurate SCE simulations.

Kang Wang, Yucheng Wang, M. Pera-Titus

Electrochemistry plays a pivotal role in a vast number of domains spanning from sensing and manufacturing to energy storage, environmental conservation, and healthcare. Electrochemical applications encompassing gaseous or organic substrates encounter shortcomings ascribed to high mass transfer/internal resistances and low solubility in aqueous electrolytes, resulting in high overpotentials. In practice, strong acids and expensive organic electrolytes are required to promote charge transfer in electrochemical cells, resulting in a high carbon footprint. Liquid–liquid (L–L) and gas–liquid (G–L) dispersions involve the dispersion of a nano/micro gas or liquid into a continuous liquid phase such as micelles, (macro)emulsions, microemulsions, and microfoams stabilised by surface-active agents such as surfactants and colloidal particles. These dispersions hold promise in addressing the drawbacks of electrochemical reactions by fostering the interfacial surface area between immiscible reagents and mass transfer of electroactive organic and gas reactants and products from/to the bulk to/from the electrode surface. This tutorial review provides a taxonomy of liquid–liquid and gas–liquid dispersions for applications in electrochemistry, with emphasis on their assets and challenges in industrially relevant reactions for fine chemistry and depollution.

Haotian Chen, Enno Kätelhön, R. Compton

Mauro Aquiles La Scalea, L. Chiavassa, Charles L. Brito

The heterocyclic and aromatic nitro compounds are industrially and commercially important chemicals, used in drugs, explosives, pesticides, and dyes. Despite their economic importance, the advent of these chemicals also brought serious human health and environmental problems due to their toxic characteristics as contaminants and pollutants. The nitro group is catalyzed in vivo by nitroreductases promoting a six-electron reduction to form sequentially the nitro radical anion, nitroso-, N-hydroxylamino and amino-functional groups. These reactions can be electrochemically reproduced, involving the development of analytical methods and electrochemical sensors, degradation and removal of organic compounds in effluents, corrosion studies, and studies of action mechanism of drugs on DNA bases. In this sense, a bibliometric analysis has been performed based on the Web of Science Core Collection in conjunction with VOSviewer software for generating network visualizations. This research covered the database until 2023, describing the main research areas and the annual publication trends, the collaborations and contributions among countries and research institutions, in addition to identifying the most cited articles, hotspots, and the analysis of evolution and relevance of keywords. This investigation made it possible to recognize the main research focuses and what is under development, providing a comprehensive overview on electrochemistry of nitro compounds.