Hasil untuk "Industrial electrochemistry"

S. Trasatti

Akeem Babatunde Akinwola, Abdulaziz Alkuhayli

The rapid integration of photovoltaic (PV) generation into modern power networks introduces significant operational challenges, including intermittent power production, uneven charge distribution, and reduced system reliability in multi-battery energy storage systems. Addressing these challenges requires intelligent, adaptive, and physically consistent control strategies capable of operating under uncertain environmental and load conditions. This study proposes a Physics-Informed Neural Network (PINN)-based charge allocation framework that explicitly embeds physical constraints—namely charge conservation and State-of-Charge (SoC) equalization—directly into the learning process, enabling real-time adaptive control under varying irradiance and load conditions. The proposed controller exploits real-time measurements of PV voltage, current, and irradiance to achieve optimal charge distribution while ensuring converter stability and balanced battery operation. The framework is implemented and validated in MATLAB/Simulink under Standard Test Conditions of 1000 W·m⁻² irradiance and 25 °C ambient temperature. Simulation results demonstrate stable PV voltage regulation within the 230–250 V range, an average PV power output of approximately 95 kW, and effective duty-cycle control within the range of 0.35–0.45. The system maintains balanced three-phase grid voltages and currents with stable sinusoidal waveforms, indicating high power quality during steady-state operation. Compared with conventional Proportional–Integral–Derivative (PID) and Model Predictive Control (MPC) methods, the PINN-based approach achieves faster SoC equalization, reduced transient fluctuations, and more than 6% improvement in overall system efficiency. These results confirm the strong potential of physics-informed intelligent control as a scalable and reliable solution for smart PV–battery energy systems, with direct relevance to renewable microgrids and electric vehicle charging infrastructures.

Ruomu Tan, Martin W Hoffmann

The integration of artificial intelligence (AI) into the industrial sector has not only driven innovation but also expanded the ethical landscape, necessitating a reevaluation of principles governing technology and its applications and awareness in research and development of industrial AI solutions. This chapter explores how AI-empowered industrial innovation inherently intersects with ethics, as advancements in AI introduce new challenges related to transparency, accountability, and fairness. In the chapter, we then examine the ethical aspects of several examples of AI manifestation in industrial use cases and associated factors such as ethical practices in the research and development process and data sharing. With the progress of ethical industrial AI solutions, we emphasize the importance of embedding ethical principles into industrial AI systems and its potential to inspire technological breakthroughs and foster trust among stakeholders. This chapter also offers actionable insights to guide industrial research and development toward a future where AI serves as an enabler for ethical and responsible industrial progress as well as a more inclusive industrial ecosystem.

Lin Liu, Rita Machacy, Simi Kuniyilh

The Industrial Internet of Things (IIoT) integrates intelligent sensing, communication, and analytics into industrial environments, including manufacturing, energy, and critical infrastructure. While IIoT enables predictive maintenance and cross-site optimization of modern industrial control systems, such as those in manufacturing and energy, it also introduces significant privacy and confidentiality risks due to the sensitivity of operational data. Contrastive learning, a self-supervised representation learning paradigm, has recently emerged as a promising approach for privacy-preserving analytics by reducing reliance on labeled data and raw data sharing. Although contrastive learning-based privacy-preserving techniques have been explored in the Internet of Things (IoT) domain, this paper offers a comprehensive review of these techniques specifically for privacy preservation in Industrial Internet of Things (IIoT) systems. It emphasizes the unique characteristics of industrial data, system architectures, and various application scenarios. Additionally, the paper discusses solutions and open challenges and outlines future research directions.

Wenwen Zheng, Kaichen Zhu, Sebastian Pazos et al.

When using two-dimensional (2D) materials to build electronic devices, adjacent metallic films need to be deposited to form electrodes. However, weak adhesion in high-quality van der Waals interfaces often leads to a low fabrication yield due to materials cracking and even peeling during photolithography. Several researchers use ultra-thin adhesive metallic layers, such as Ti, Cr, or Ni; while this method effectively enhances adhesion, all these metals are oxygen scavengers (in more or less degree) and they significantly alter the charge transport. Here we present a fabrication process for 2D-materials-based electronic devices that leads to high yield without the need of using adhesive metallic layers. Our method consists on using a discontinuous coverage of the 2D material during the photolithography step assisted by a negative photoresist, combined by electron beam evaporation of metal under moderate vacuum (5 × 10−6 Torr) to produce a truly van der Waals interface and avoid damaging the 2D material. When using this improved method, we systematically achieve defect-free Au/hBN interfaces with good adhesion, which lead to 100 % fabrication yield (340 devices were fabricated correctly). Electrical characterization reveals low leakage currents below 10 pA and minimal device-to-device variability, demonstrating the process’s effectiveness. Our method provides a viable pathway towards the fabrication of 2D material-based electronic devices and circuits with higher performance and reliability.

Pradeep Raj Sharma, Bogeun Jang, Gaojie Zhang et al.

Spin-orbit torque (SOT) is a highly viable mechanism for achieving low-energy and high-speed switching in spintronic devices. Two-dimensional (2D) van der Waals (vdW) materials and their heterostructures have proven their scalability and energy effectiveness for device operation. Here, we demonstrate that SOT can be robustly realized in a heterostructure composed of the 2D-vdW ferromagnetic material (FM) Fe3GaTe2 (FGaT) and the 2D-vdW topological semimetal WTe2 at room temperature. The anisotropic Fermi surface originating from the uniquely reduced crystal symmetry of WTe2 enables field-free deterministic SOT switching. We report an unprecedentedly low threshold switching current density of 6.5 × 109 A m−2 at zero field and a spin Hall angle (θSH) of 8.5. These results demonstrate a nearly 100-fold improvement in device performance over all previously reported 3D heavy metal (HM)/FM systems, supported by a second harmonic-modulated nonlinear signal measurement implemented to ensure SOT analysis and reliability. The spin Hall conductivity (σSH) and the switching power density (Psw) reported are about 1.3 × 106 S m−1 and 0.33 × 1015 W m−3, respectively, supporting the efficient device performance at low power consumption. Our result highlights that Fe3GaTe2, coupled with the strong spin–orbit coupling and low crystal symmetry of WTe2, in the form of 2D-vdW heterostructure (WTe2/Fe3GaTe2), offers a promising platform for generating substantial torque on magnetization at room temperature. This leads to more efficient and easier switching, paving the way for developing next-generation, highly advanced, room-temperature spin-electronic devices.

Zhaoxuan Zhu, Sihan Xiong, Jing Li et al.

In the original publication [...]

Viswanathan S. Saji

Plasma electrolytic oxidation (PEO) is a pivotal method to create a thick and adherent protective oxide layer on magnesium (Mg) alloys, significantly enhancing their wear and corrosion resistance. The functional oxide layers fabricated via PEO have diverse potential applications, including automobile, aerospace, machinery, biomedical, thermal protection, catalysis, and energy materials. The type and nature of the electrolyte and electrolyte additives used in PEO play a decisive role in shaping the morphology, compactness, porosity, composition, thickness, wear/corrosion resistance, mechanical properties, and other functionalities of the resulting layer. The in-situ integration of chemicals/particles into the PEO layer, facilitated by optimized electrolyte additives, is a well-established method for producing enhanced composite oxide layers. This potential for creating enhanced composite PEO oxide layers is a promising aspect of PEO technology, and this review explores the latest strategies in optimizing electrolyte and electrolyte additives for superior PEO layers in various applications.

Sahithi Maddipatla, Huzaifa Rauf, Michael Osterman et al.

Electrochemical processes within a lithium-ion battery cause electrode expansion and gas generation, thus resulting in battery swelling and, in severe cases, reliability and safety issues. This paper presents the mechanisms responsible for swelling, including thermal expansion, lithium intercalation, electrode interphase layer growth, lithium plating, and gas generation, while highlighting their dependence on material properties, design considerations, C-rate, temperature, state of charge (SoC), and voltage. The paper then discusses how swelling correlates with capacity fade, impedance rise, and thermal runaway, and demonstrates the potential of using swelling as a diagnostic and prognostic metric for battery health. Swelling models that connect microscopic mechanisms to macroscopic deformation are then presented. Finally, the paper presents strategies to mitigate swelling, including materials engineering, surface coatings, electrolyte formulation, and mechanical design modifications.

Jay Lee, Hanqi Su

Recent advancements in industrial artificial intelligence (AI) are reshaping the industry by driving smarter manufacturing, predictive maintenance, and intelligent decision-making. However, existing approaches often focus primarily on algorithms and models while overlooking the importance of systematically integrating domain knowledge, data, and models to develop more comprehensive and effective AI solutions. Therefore, the effective development and deployment of industrial AI require a more comprehensive and systematic approach. To address this gap, this paper reviews previous research, rethinks the role of industrial AI, and proposes a unified industrial AI foundation framework comprising three core modules: the knowledge module, data module, and model module. These modules help to extend and enhance the industrial AI methodology platform, supporting various industrial applications. In addition, a case study on rotating machinery diagnosis is presented to demonstrate the effectiveness of the proposed framework, and several future directions are highlighted for the development of the industrial AI foundation framework.

Hang Yu, Yuzhou Lai, Li Zhang et al.

The rapid advancement of large language models (LLMs) is fundamentally reshaping software engineering (SE), driving a paradigm shift in both academic research and industrial practice. While top-tier SE venues continue to show sustained or emerging focus on areas like automated testing and program repair, with researchers worldwide reporting continuous performance gains, the alignment of these academic advances with real industrial needs remains unclear. To bridge this gap, we first conduct a systematic analysis of 1,367 papers published in FSE, ASE, and ICSE between 2022 and 2025, identifying key research topics, commonly used benchmarks, industrial relevance, and open-source availability. We then carry out an empirical survey across 17 organizations, collecting 282 responses on six prominent topics, i.e., program analysis, automated testing, code generation/completion, issue resolution, pre-trained code models, and dependency management, through structured questionnaires. By contrasting academic capabilities with industrial feedback, we derive seven critical implications, highlighting under-addressed challenges in software requirements and architecture, the reliability and explainability of intelligent SE approaches, input assumptions in academic research, practical evaluation tensions, and ethical considerations. This study aims to refocus academic attention on these important yet under-explored problems and to guide future SE research toward greater industrial impact.

Lu Xia, Kaiqi Zhao, Sunil Kadam et al.

Paired electrolysis at industrial current densities offers an energy-efficient and sustainable alternative to thermocatalytic chemical synthesis by leveraging anodic and cathodic valorization. However, its industrial feasibility remains constrained by system integration, including reactor assembly, asymmetric electron transfer kinetics, membrane selection, mass transport limitations, and techno-economic bottlenecks. Addressing these challenges requires an engineering-driven approach that integrates reactor architecture, electrode-electrolyte interactions, reaction pairing, and process optimization. Here, we discuss scale-specific electrochemical reactor assembly strategies, transitioning from half-cell research to full-scale stack validation. We develop reaction pairing frameworks that align electrocatalyst design with electrochemical kinetics, enhancing efficiency and selectivity under industrial operating conditions. We also establish application-dependent key performance indicators (KPIs) and benchmark propylene oxidation coupled with hydrogen evolution reaction (HER) or oxygen reduction reaction (ORR) against existing industrial routes to evaluate process viability. Finally, we propose hybrid integration models that embed paired electrolysis into existing industrial workflows, overcoming adoption barriers.

Sotiris Michaelides, Daniel Eguiguren Chavez, Martin Henze

With the ongoing adoption of 5G for communication in industrial systems and critical infrastructure, the security of industrial UEs such as 5G-enabled industrial robots becomes an increasingly important topic. Most notably, to meet the stringent security requirements of industrial deployments, industrial UEs not only have to fully comply with the 5G specifications but also implement and use correctly secure communication protocols such as TLS. To ensure the security of industrial UEs, operators of industrial 5G networks rely on security testing before deploying new devices to their production networks. However, currently only isolated tests for individual security aspects of industrial UEs exist, severely hindering comprehensive testing. In this paper, we report on our ongoing efforts to alleviate this situation by creating an automated security testing framework for industrial UEs to comprehensively evaluate their security posture before deployment. With this framework, we aim to provide stakeholders with a fully automated-method to verify that higher-layer security protocols are correctly implemented, while simultaneously ensuring that the UE's protocol stack adheres to 3GPP specifications.

Deepak-A Jadhav, A. K. Mungray, Ambika Arkatkar et al.

Abstract In the current scenario, application of microbial fuel cell (MFC) is limited at laboratory scale for wastewater treatment and energy recovery. Scaling-up applications of MFC are constrained with microbes-electrode interactions, design aspects, electrochemical limitations and multidisciplinary approach of environmental electrochemistry and biotechnology. For transformation of bench-top MFC models towards the field applications, scaling-up can be achieved by enlarging the size of electrodes and stacking of modular units. However, the issues of maintaining the proportionate energy harvesting rate and voltage reversal need to be addressed. Present review focused on scaling-up barriers and realistic status of MFC technology towards practical use as well as techno-economic assessment of the system. Field demonstration of Pee-Power MFC, Bioelectric toilet and other onsite applications for industrial use are key indicators of successful implementation of MFC technology for field applications. With advancement towards practical use, MFC can be sustainable competent technology against conventional technologies for wastewater treatment and energy recovery.

Pankaj Kumar, Amit Kumar Jain, J. Srivastava et al.

ABSTRACT The electrochemical machining process involves electrical and chemical processes while removing materials from the workpiece. Electrochemical machining (ECM) lacks accurate models for predicting the shape and material removal rate during the ECM process. This limits the ability to optimise the process and predict the final product geometry, which is crucial for industrial applications. This research mainly focused on the modelling and simulation of material removal from the workpiece using COMSOL Multiphysics software. This research involves developing a mathematical model that describes ECM’s electrical, chemical, and mechanical interactions. The model is based on electrochemistry, fluid dynamics, and solid mechanics principles and will be solved using numerical simulation techniques. Various workpiece materials considered in this investigation include Aluminium, Nickel, Stainless Steel, and Tungsten, whereas copper is electrode material. The effects of the various parameters, such as workpiece materials, the voltage applied during machining, and electrolyte conductivity on the material removal rate are being investigated. In addition, the shape of the machined workpiece is also predicted. The results of this research provide a deeper understanding of the underlying physics of the ECM process and lead to the development of more accurate models for predicting the shape and material removal rate during ECM.

M. Elsherbini, T. Wirth

Despite the long history of electroorganic synthesis, it did not participate in the mainstream of chemical research for a long time. This is probably due to the lack of equipment and standardized protocols. However, nowadays organic electrochemistry is witnessing a renaissance, and a wide range of interesting electrochemical transformations and methodologies have been developed, not only for academic purposes but also for large scale industrial production. Depending on the source of electricity, electrochemical methods can be inherently green and environmentally benign and can be easily controlled to achieve high levels of selectivity. In addition, the generation and consumption of reactive or unstable intermediates and hazardous reagents can be achieved in a safe way. Limitations of traditional batch-type electrochemical methods such as the restricted electrode surface, the necessity of supporting electrolytes, and the difficulties in scaling up can be alleviated using electrochemical flow cells. Microreactors offer high surface-to-volume ratios and enable precise control over temperature, residence time, flow rate, and pressure. In addition, efficient mixing, enhanced mass and heat transfer, and handling of small volumes lead to simpler scaling-up protocols and minimize safety concerns. Electrolysis under flow conditions reduces the possibility of overoxidation as the reaction mixture is flown continuously out of the reactor in contrast to traditional batch-type electrolysis cells. In this Account, we highlight our contributions in the area of electroorganic synthesis under flow conditions over the past decade. We have designed and manufactured different generations of electrochemical flow cells. The first-generation reactor was effectively used in developing a simple one-step synthesis of diaryliodonium salts and used in proof-of-concept reactions such as the trifluoromethylation of electron-deficient alkenes via Kolbe electrolysis of trifluoroacetic acid in addition to the selective deprotection of the isonicotinyloxycarbonyl (iNoc) group from carbonates and thiocarbonates. The improved second-generation flow cell enabled the development of efficient synthesis of isoindolinones, benzothiazoles, and thiazolopyridines, achieving gram-scale for some of the products easily without changing the reactor design or reoptimizing the reaction parameters. In addition, the same reactor was used in the development of an efficient continuous flow electrochemical synthesis of hypervalent iodine reagents. The generated unstable hypervalent iodine reagents were easily used without isolation in various oxidative transformations in a coupled flow/flow manner and could be easily transformed into bench-stable reagents via quantitative ligand exchange with the appropriate acids. Our second-generation reactor was further improved and commercialized by Vapourtec Ltd. We have demonstrated the power of online analysis in accelerating optimizations and methodology development. Online mass spectrometry enabled fast screening of the charge needed for the cyclization of amides to isoindolinones. The power of online 2D-HPLC combined with a Design of Experiments approach empowered the rapid optimization of stereoselective electrochemical alkoxylations of amino acid derivatives.

Mohamed Kilani, Guangzhao Mao

Despite their restrictions under international treaties, many chemical warfare agents (CWAs) and their toxic analogues are still used in various industrial sectors such as agriculture and chemical manufacturing. Thus, the need for sensitive and selective CWA detection remains critical. Commercially available detection methods, while accurate, are often bulky, expensive, and require specialized personnel. Sensors incorporating nanomaterials present a promising alternative, offering rapid, portable, and cost-effective detection due to their unique properties, such as high surface area and tunable reactivity. This review covers the four main CWA categories: nerve agents, blister agents, blood agents, and choking agents, highlighting recent progress in nanosensor development for each category. It discusses various sensing mechanisms employed, including fluorescence, colorimetry, chemiresistivity, electrochemistry, and Raman spectroscopy. Despite these advancements, challenges remain, particularly regarding the scalability, stability, and selectivity of nanomaterials-based sensors in complex environments. The review concludes by emphasizing the need to address these challenges and explore novel nanomaterials, the development of scalable nanomanufacturing techniques, and the integration of artificial intelligence to fully unlock the potential of nanomaterials in CWA sensing for homeland security and personal safety.

Soumi Mondal, S. C. Peter

Electrochemical CO2 reduction reaction (eCO2RR) has been explored extensively for mitigation of noxious CO2 gas generating C1 and C2+ hydrocarbons and oxygenates as value‐added fuels and chemicals with remarkable selectivity. The source of CO2 being a pure CO2 feed, it does not fully satisfy the real‐time digestion of industrial exhausts. Besides the detrimental effect of noxious gas mixture leading to global warming, there is a huge capital investment in purifying the flue gas mixtures from industries. The presence of other impurity gases affects the eCO2RR mechanism and its activity and selectivity toward C2+ products dwindle drastically. Impurities like NOx, SOx, O2, N2, and halide ions present in flue gas mixture reduce the conversion and selectivity of eCO2RR significantly. Instead of wiping out these impurities via separation processes, new strategies from material chemistry and electrochemistry can open new avenues for turning foes to friends! In this perspective, the co‐electroreduction will vividly discussed and supporting role of different heteroatom‐containing impurity gases with CO2, generating highly stable C─N, C─S, C─X bonds, and highlight the existing limitations and providing probable solutions for attaining further success in this field and translating this to industrial exhaust streams.

Hui Zhao

Rechargeable Zn-air batteries are considered to be an effective energy storage device due to their high energy density, environmental friendliness, and long operating life. Further progress on rechargeable Zn-air batteries with high energy density/power density is greatly needed to satisfy the increasing energy conversion and storage demands. This review summarizes the strategies proposed so far to pursue high-efficiency Zn-air batteries, including the aspects of the electrocatalysts (from noble metals to non-noble metals), the electrode chemistry (from the oxygen evolution reaction to the organic oxidation reaction), electrode engineering (from powdery to free-standing), aqueous electrolytes (from alkaline to non-alkaline) and the battery configuration (from liquid to flexible). An essential evaluation of electrochemistry is highlighted to solve the challenges in boosting the efficiency of rechargeable metal-air batteries. In the end, the perspective on current challenges and future research directions to promote the industrial application of rechargeable Zn-air batteries is provided.

Muhammad Mujahid, Muhammad Umar Farooq, Chao Wang et al.

Industry, agriculture, and a growing population all have a major impact on the scarcity of clean‐water. Desalinating or purifying contaminated water for human use is crucial. The combination of thermal membrane systems can outperform conventional desalination with the help of synergistic management of the water‐energy nexus. High energy requirement for desalination is a key challenge for desalination cost and its commercial feasibility. The solution to these problems requires the intermarriage of multidisciplinary approaches such as electrochemistry, chemical, environmental, polymer, and materials science and engineering. The most feasible method for producing high‐quality freshwater with a reduced carbon footprint is demanding incorporation of industrial low‐grade heat with membrane distillation (MD). More precisely, by using a reverse electrodialysis (RED) setup that is integrated with MD, salinity gradient energy (SGE) may be extracted from highly salinized MD retentate. Integrating MD‐RED can significantly increase energy productivity without raising costs. This review provides a comprehensive summary of the prospects, unresolved issues, and developments in this cutting‐edge field. In addition, we summarize the distinct physicochemical characteristics of the membranes employed in MD and RED, together with the approaches for integrating them to facilitate effective water recovery and energy conversion from salt gradients and freshwater.