Alkaline Water Electrolysis System Research Articles

Optimization of chemical engineering control for large-scale alkaline electrolysis systems based on renewable energy sources

In the context of renewable energy, dynamic control is crucial for large-scale alkaline water electrolysis systems. Under traditional Proportional-Integral-Derivative (PID) control, the system's temperature and impurity levels may exceed safe limits during sudden load changes, compromising system safety. Therefore, this study proposes a control strategy based on mathematical models of system temperature and impurities, including Model Predictive Control (MPC) for temperature and Optimal Curve Tracking (OCT) for impurities. The MPC controller offsets the disturbances in temperature caused by current fluctuations through state prediction, while the OCT controller ensures that impurity levels remain within safe limits. Real-time application of these control strategies is achieved through MATLAB-PLC communication, validating controller performance. Experimental results show that the MPC controller exhibits excellent dynamic response and stability in controlling the stack temperature, with a maximum temperature peak deviation of only 2.9 K and a temperature fluctuation range of 5.9 K. This represents a reduction of 1.6 K in peak deviation compared to traditional PID controllers and significantly decreases the temperature fluctuation range. The OCT controller also demonstrates good safety and stability in controlling hydrogen to oxygen (HTO) impurity levels, consistently maintaining the HTO content at the set upper limit of 1.5%, thereby expanding the safe operational range of the system and reducing the need for frequent adjustments to the system setpoints.

Efficient Oxygen Evolution Reaction on Catalyst‐Free Acid‐Functionalized Plastic Chip Electrodes

Innovative electrode design is critical for improving the oxygen evolution reaction (OER) and meeting rising global energy demands. Despite the development of numerous carbon materials for water splitting, their potential is hampered by sluggish kinetics, primarily due to high activation energy compounded by various smaller factors, including additives or binders used in electrode modification. To address these limitations, a catalyst‐free plastic chip electrode (PCE) for OER is developed. PCE is functionalized by oxidizing it in acidic media at 1.8 V versus Ag/AgCl and eliminates the need for additives, offering a more accurate industrial representation. The oxidation process enhances the electrode's surface area and introduces electrochemically active oxygen‐containing functional groups. Characterization of the modified PCE is conducted using scanning electron microscope, X‐ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, X‐ray diffraction, Raman, and thermogravimetric analysis, while electrolyte analysis utilizes UV–vis spectroscopy and NMR. The PCE oxidized for 6 h (PCE@6) demonstrates improved OER performance, with an onset overpotential of 260 mV, an overpotential of 1.06 V versus reversible hydrogen electrode at 10 mA cm−2, and a Tafel slope of 494 mV decade−1. The modified PCE reduces overpotential and minimizes bubble formation, enhancing efficiency and showcasing its potential as a cost‐effective solution for alkaline water electrolysis systems.

Green hydrogen production from thermoelectric condensation of ambient moist air

As the world transitions towards reducing carbon emissions, green hydrogen produced through solar-powered alkaline water electrolysis (AWE) presents a promising eco-friendly fuel option. In response to the challenges caused by global warming, including air moisture saturation leading to unbalanced rainfall, flooding, concern for freshwater depletion and the limited availability of water and energy sources in arid regions. The present study introduces a novel method of integrating thermoelectric water condenser (TEWC) and AWE for green hydrogen production in remote and arid regions where both the water and the conventional energy sources are scarce. Numerical simulations of the present study show that the impact of relative humidity, temperature, and air flow rate significantly affect water condensation, energy requirement, and hydrogen production. The TEWC and AWE models showed excellent agreement with the experimental data. TEWC model reveled that the highest water production rate of 1.50 kg/(m2h) is achieved at ambient air temperature of 308 K and relative humidity of 80%. Furthermore, increasing the moist air flow from 1 m/s to 2 m/s results in a 47.5% increase in water production rate. The AWE model showed that cell's performance improved with higher temperatures, lower electrode-separator gap, and overpotentials. The hydrogen evolution rate reached a maximum of 5.2 kg/(m2h) at current density of 1.4 A/cm2 and potential of 3.96 V. By optimizing the TEWC and AWE systems the integrated method proved to be an efficient way of converting moist air into green hydrogen using solar energy, making it a viable and sustainable setup in remote arid regions.

Decoupling Electrolytic Water Splitting by an Oxygen-Mediating Process.

Decoupled water electrolysis systems, incorporating a reversible redox mediator that allows for the construction of membrane-free electrolyzers, have emerged as a promising approach to produce high-purity hydrogen with remarkable flexibility. The key factor crucial for practical applications lies in the development of mediator electrodes that possess suitable redox potential, high redox capacity, excellent cycling reversibility and stability. Herein, we introduce a novel concept of oxygen-mediating redox mediators (ORMs) employing Bi2O3 as an example material, which are capable of sequestering oxygen during the hydrogen evolution reaction and subsequently releasing it to generate oxygen gas under alkaline conditions. Thanks to its remarkable reversible redox activity and specific capacity, the Bi2O3 electrode boasts an impressive reversible specific capacity of 300.8 mA h g-1 and delivers outstanding cycling performance for >1000 cycles at a current density of 2.0 A g-1. Furthermore, the implementation of such a decoupled alkaline water electrolysis system can be integrated with a Bi2O3-Zn battery, enabling both power-to-fuel (hydrogen production) and chemical-to-power (rechargeable Bi2O3-Zn battery) conversion. With many oxygen-carrier materials readily available and the potential integration with rechargeable alkaline batteries, this study provides an alternative competitive route for membrane-free decoupled water splitting through the oxygen-mediating mechanism with combined energy transformation and storage.

A Coherent Workflow for Elevating Transition Metal Oxide Anode Materials in Alkaline Electrolysis to Connect Insights from Micro Powder Analysis with Electrochemical Performance

Increasing environmental concerns have redirected research efforts toward sustainable energy, prominently highlighting hydrogen as a promising solution [1]. Despite considerable advancements in water electrolysis, providing efficient energy conversion and storage, there exists a gap in our comprehensive understanding of the production chain. This includes insights from commercial powder materials to electrode fabrication and their electrocatalytic behavior, representing an underexplored domain that demands closer examination.This study systematically examines transition metal oxide electrocatalysts, aiming to parameterize the process chain within the context of a coherent workflow for advancing transition metal oxide anode materials in alkaline electrolysis. This approach seeks to reveal the interdependencies and comprehend the correlations between material properties, fabrication processes, electrode structure, and the final performance of the cell. Our methodology integrates a range of complementary techniques to ensure a consistent analysis of the physical and chemical properties of the materials. Following the initial characterization of commercial micropowder through transmission electron microscopy and energy-dispersive X-ray spectroscopy, we optimized ink formulations derived from the powder using analytical centrifugation and Hansen parameter calculations [2]. Subsequently, selected inks were transferred to electrodes by coating these inks on Ni plates via ultrasonic spray deposition. We further investigated the impact of post-treatments, including vacuum annealing and surface plasma treatment, on the stability of the electrodes, particularly in terms of delamination prevention.To quantify the underlying micro features of this wide range of electrode surfaces and analyze their characteristics, we developed a framework called multistage data quantification (MSDQ). MSDQ ulitizes microscopical charcterizations such as laser microscopy and atomic force microscopy [3]. The assessed electrodes were finally tested as anodes for alkaline water electrolysis, revealing correlations between electrode properties and electrochemical activity and stability. In line with the recognized structural characteristics, our initial findings indicate that electrodes treated with plasma demonstrate reduced overpotentials and enhanced stability when compared to pristine and plasma treated electrodes, due to increased adhesion and surface properties (e.g., roughness).Our study makes a substantial contribution to the comprehensive evaluation of the alkaline water electrolysis system across its development stages, incorporating valuable insights from earlier steps to continually enhance electrode performance. Our approach is particularly advantageous in enabling the transition from laboratory-scale research to scalable processing, effectively bridging the crucial gap for practical industrial applications [4]. Ehlers, J.C., et al., "Affordable Green Hydrogen from Alkaline Water Electrolysis: Key Research Needs from an Industrial Perspective. " ACS Energy Letters, 2023. 8(3): p. 1502-1509.Bapat, S., et al., "On the state and stability of fuel cell catalyst inks. " Advanced Powder Technology, 2021. 32(10): p. 3845-3859.Jain, A., et al., "Small-Area Observations to Insight: Surface-Feature-Extrapolation of Anodes via Multistage Data Quantification. " Under review, ChemCatChemSegets, D., et al., "Accelerating CO2 electrochemical conversion towards industrial implementation." Nature communications 14.1 (2023): 7950.

Solar Thermal Integrated Alkaline Water Electrolyser for Fast Ramping Up

There is significant recent interest in clean hydrogen production from renewable water electrolysis. In general, alkaline water electrolysis (AWE) operates with a voltage of ca. 2 V due to ohmic and overpotential-derived loss (0.7~0.8 V) [1]. In addition, it requires 0.5~1 hours for the ramping-up, which hinders its wider implementation. Our intended solution is to introduce a heat-tolerant electrolyser integrated with a chemically resistant solar thermal collector, providing a heated electrolyte to increase the reactivity [2] and reduce the ramp-up time. In this work, we discuss key dimensional design aspects of the thermal collector for alkaline electrolyser, considering the control feasibility of operating temperature and fluidic parameters. Furthermore, we also demonstrate our proof-of-concept experimental results using our alkaline electrolyser integrated with the solar-thermal collector at an elevated temperature. The time-dependent current output of the solar-thermal integrated AWE over the first 1 h yielded ca. 70% higher compared to the conventional AWE system. E. Amores, J. Rodríguez, J. Oviedo, A. De Lucas-Consuegra, Open Eng 2017, 7,141–152.B. Zhang, Q. Daniel, M. Cheng, L. Fan, L. Sun, Faraday Discuss 2017, 198, 169–179 Figure 1

Development and characterization of engineering plastic diaphragm for alkaline water electrolysis

Research on carbon dioxide free energy sources is increasing due to climate change, with green hydrogen gaining significant attention for its eco-friendly production process. This study focused on creating a diaphragm for alkaline water electrolysis using the TIPS method, utilizing the engineering thermoplastics PEEK and PPS for their excellent mechanical properties and heat resistance. DPK was employed as a diluent, and the phase diagram was established by measuring the crystallization temperature and cloud point based on polymer content. The morphology of the diaphragm, both surface and cross-section, was observed using an SEM, while tensile strength, alkaline stability, and permeability tests assessed its suitability for alkaline electrolysis conditions. The diaphragm with a polymer content of 20 wt% demonstrated a mechanical strength of 31.9 MPa, making it viable for operational use in alkaline electrolysis. All the diaphragms exhibited exceptional alkali resistance, with weight changes of less than 1 % in a 25 to 30 wt% KOH solution. Additionally, permeability tests indicated that permeability decreased as polymer content increased. Electrochemical evaluations revealed that the 20 wt% polymer content diaphragm achieved the best performance, delivering 188.7 mA/cm². This study confirms the potential of using these diaphragms in efficient and sustainable alkaline water electrolysis systems.

Direct operational data-driven workflow for dynamic voltage prediction of commercial alkaline water electrolyzers based on artificial neural network (ANN)

The thermal inertia of alkaline water electrolysis (AWE) system under dynamic operation reduces efficiency and poses security risks. To mitigate this, predictive model control (MPC) emerges as a potential solution, aiming to precisely regulate temperature through temperature trend prediction, which relies on accurate voltage predictions. However, the current MPC implementation for AWE system utilizes empirical model for voltage prediction, requiring extensive experimental data for calibration, making it time-consuming and costly for large-scale water electrolysis projects. Data-driven models are a promising alternative for voltage prediction, but research is limited by the lack of long-term commercial AWE operational data and the ambiguity in developing effective data-driven models. In this study, a 10-kW level AWE test system underwent 300 h of simulated solar-driven dynamic operation to assess the resilience of AWE system to dynamic conditions. Subsequently, a robust data-driven workflow using artificial neural networks (ANNs) was developed for precise dynamic voltage prediction based on obtained operational data. The data-driven workflow incorporates automated processes for voltage prediction, including data importing, data cleaning, ANN architecture optimization, model training, and ultimately voltage prediction, avoiding the need for manual parameters fitting. The model’s performance was evaluated and compared with empirical model across four dynamic operation types (cold-start, ramp, stepwise, and random response), achieving an impressive accuracy over 98 %. Furthermore, the ANN model also exhibits application potential in U-I curves prediction (accuracy > 98 %), influential features assessment, operational optimization and MPCs. This ANN-based workflow serves as a versatile framework for precise voltage prediction under dynamic operations and provides an analytical platform for operational data analysis, system optimization, and advanced control system development.

Effect of electrolyte circulation on hydrogen-in-oxygen in alkaline water electrolysis

The concentration of hydrogen in oxygen (HTO) is a crucial factor in determining the load limit of alkaline water electrolysis (AWE) due to the risk of explosion with high HTO levels. In this study, we analysed the impact of circulating electrolytes, carrying dissolved gas, on HTO in a home-designed zero-gap alkaline water electrolysis system, operating at atmospheric pressure and constant temperature. By comparing the experimental results from mixed and separated cycles, we found that the amount of dissolved hydrogen in the electrolyte significantly contributes to HTO. We then developed a theoretical model to predict HTO values and experimentally confirmed a linear relationship between the HTO and the ratio of electrolyte circulation to gas production (QL/ QO2). Based on this evidence, we proposed a new electrolyte circulation control strategy that reduces the HTO value by as much as 63.56%. These findings could help overcome the load limit of alkaline water electrolysis systems, which is crucial for their large-scale application.

Reverse‐Current Tolerance for Hydrogen Evolution Reaction Activity of Lead‐Decorated Nickel Catalysts in Zero‐Gap Alkaline Water Electrolysis Systems (Adv. Funct. Mater. 27/2024)

Reverse‐Current Tolerance for Hydrogen Evolution Reaction Activity of Lead‐Decorated Nickel Catalysts in Zero‐Gap Alkaline Water Electrolysis Systems (Adv. Funct. Mater. 27/2024)

Supercapacitor-isolated water electrolysis for renewable energy storage

This study addresses a significant technological challenge in hydrogen production through electrolysis: the issue of gas crossover across the diaphragm between the cathode and anode, particularly under variable power conditions associated with renewable energy sources. We introduce a novel supercapacitor-isolated alkaline water electrolysis system utilizing a carbon-based supercapacitor sheet approximately 1 mm thick as an alternative to traditional diaphragms, effectively reducing gas crossover. At 25 °C and in 2.0 M KOH, our electrolysis system achieved a high current density of 0.736 A cm−2 for hydrogen evolution at 2.0 V, which was maintained at 0.023 A cm−2 even when the voltage was reduced to 0.9 V. Notably, the concentration of hydrogen to oxygen (HTO) remained low at 0.42 vol% with a current density of 0.01 A cm−2, surpassing the 28.5 vol% observed with a traditional diaphragm under similar conditions. At 70 °C, the electrolysis system exhibited an average hydrogen evolution rate of 0.952 A cm−2, with a specific energy consumption of 4.786 kWh Nm−3 (H₂) and a Faradaic efficiency of 99.5 %. Following a 55-day test under near-industrial conditions, the capacitive electrode demonstrated exceptional durability. These results represent a significant advancement in decoupled water electrolysis, indicating that the direct utilization of renewable energy for hydrogen production is feasible.

Techno-economic analysis of green hydrogen production, storage, and waste heat recovery plant in the context of Nepal

Alkaline water electrolysis (AWE) operated by surplus electricity is suitable for producing green hydrogen in Nepal. Simulation models are built using DWSIM software for AWE, multistage compression, and the Organic Rankine Cycle (ORC). The AWE system's Capital Expenditure (CAPEX) is determined to be $47 million and Operational Expenditure (OPEX) of $7.65 million/year. The storage system, including the multistage compression system and Type IV cylinders, has a CAPEX of $52 million and an OPEX of $17 million/year. The ORC has a CAPEX of $500,000 and an OPEX of $200,000/year. The thermal power generated from AWE and multistage compression can be converted to electricity by the ORC and supplied to the AWE system. This process decreases the Levelized Cost of Hydrogen (LCOH) from $3.5141/kg over 5 years to $3.4725/kg over 25 years. The techno-economic analysis performed confirms the feasibility of implementing these plants in Nepal.

Dynamic fault detection and diagnosis of industrial alkaline water electrolyzer process with variational Bayesian dictionary learning

Alkaline Water Electrolysis (AWE) is one of the simplest green hydrogen production method using renewable energy. AWE system typically yields process variables that are serially correlated and contaminated by measurement uncertainty. A novel robust dynamic variational Bayesian dictionary learning (RDVDL) monitoring approach is proposed to improve the reliability and safety of AWE operation. RDVDL employs a sparse Bayesian dictionary learning to preserve the dynamic mechanism information of AWE process which allows the easy interpretation of fault detection results. To improve the robustness to measurement uncertainty, a low-rank vector autoregressive (VAR) method is derived to reliably extract the serial correlation from process variables. The effectiveness of the proposed approach is demonstrated with an industrial hydrogen production process, and RDVDL can efficiently detect and diagnose critical AWE faults.

Reverse‐Current Tolerance for Hydrogen Evolution Reaction Activity of Lead‐Decorated Nickel Catalysts in Zero‐Gap Alkaline Water Electrolysis Systems

AbstractAlkaline water electrolysis (AWE) systems offer a cost‐effective and scalable approach for large‐scale hydrogen production using renewable energy sources. However, their susceptibility to load fluctuations, particularly the reverse‐current (RC) phenomenon during shutdown events, poses a significant challenge to the long‐term stability and scalability of these systems. Herein, a catalytic approach for enhancing the RC tolerance in AWE systems by using Pb‐decorated Ni cathode catalysts (Pb/Ni) is introduced. The oxidation of Pb/Ni by repeated RC lowers the electromotive force for the reverse current operation, and consequently, imparts RC tolerance. Intriguingly, contrary to the expectation that the decoration with lead, an inert material for the hydrogen evolution reaction (HER), will interfere with the hydrogen generation of the Ni catalyst, the presence of Pb on the Ni cathode after the RC flow promotes both the proton desorption and water‐dissociation steps, improving the HER activity. Furthermore, the AWE stack testing with Pb/Ni catalysts is perfectly operated, demonstrating remarkably enhanced RC tolerance during startup/shut‐down (SU/SD) testing protocol. This paper presents a new strategy for mitigating the AWE performance degradation induced by RC flow and for achieving Pb/Ni catalysts with improved operational durability against RC flow in AWE systems.

Considerations of Reference Electrodes and Liquid Junction Potentials for Accurate Electrocatalysis Studies

For lab-scale electrocatalysis studies, one typically uses a three-electrode system, which consists of working, counter (auxiliary), and reference electrodes, an electrolyte solution, and a reactor. In this system, it is important for accurate electrochemical studies to select an appropriate reference electrode for a particular electrolyte solution and recognize the presence/absence of liquid junction potential at the frit of a reference electrode. For instance, in alkaline water electrocatalysis experiments, Hg/HgO, Ag/AgCl, or saturated calomel electrode (SCE) is generally used as a reference electrode, and 1 M KOH/NaOH aqueous solution is utilized as an electrolyte solution.1 In this regard, the Ag/AgCl electrode and SCE are unsuitable for electrochemical studies with alkaline electrolytes, and among them, only the Hg/HgO electrode can be used instead.1 Furthermore, if the internal solution of a reference electrode and the external electrolyte solution are different in constituent and/or concentration, the liquid junction potential will be established at the frit of a reference electrode. In this case, to accurately know the potential applied to a working electrode, this liquid junction potential as well as the iR drop caused by solution resistance need to be considered and corrected appropriately. However, the liquid junction potential has so far been ignored in most of the electrocatalysis studies.In this work, we will discuss a method to experimentally estimate the liquid junction potential at the reference electrode frit using three-electrode systems with different combinations of electrolytes and reference electrodes. Herein, we will deal with alkaline water electrolysis systems as representatives. The as-estimated values of various liquid junction potentials will be compared with the theoretical values obtained using the Henderson equation2 and the stationary Nernst–Planck equation.3 Additionally, the guideline for selecting an appropriate reference electrode depending on the types of external electrolyte solutions will be discussed briefly. We believe that these findings can improve the accuracy of reporting potential-related parameters (e.g., overpotential, half-wave potential, onset potential, etc.) in three-electrode system-based electrocatalysis studies. References K. Kawashima et al., ACS Catal., 13, 1893–1898 (2023).R. G. Bates, Determination of pH, 2nd ed., p. 36–44, A Wiley-Interscience Publication, New York, New York, (1973).M. Marino, L. Misuri, and D. Brogioli, (2014) https://arxiv.org/abs/1403.3640v2.

Mitigating the Degradation of Electrodes in Alkaline Water Electrolysis during Shutdown Mode by Interrupting Reverse Current

Alkaline water electrolysis (AWE) is a promising technology for large-scale hydrogen production using renewable energy sources (RES). However, AWE integrated with RES experiences shutdown mode due to their intermittency, resulting in reverse current through open flow path of high ionic conductivity. This induces irreversible phase changes, which lead to electrode degradation and inevitably reduce the performance of the AWE. Therefore, it is important to examine the degradation mechanism and identify effective methods to reduce reverse current in AWE. In this work, we developed AWE system which impedes hydroxide ion transfer using deionized (DI) water circulation when it undergoes a shutdown mode. Cutting off the flow of ionic charges prevents the electrodes from forming irreversible phase change, making long-term operation possible while securing durability. We examined how reduced ionic conductivity mitigates the side effects of reverse current using phase characterization and electrochemical performance tests. Based on these results, we established an optimal way to impede hydroxide ion transfer in shutdown condition of an AWE system integrated with RES. Our findings will overcome fatal shortcomings and operate more efficiently in AWE industry.

Study on the synergistic regulation strategy of load range and electrolysis efficiency of 250 kW alkaline electrolysis system under high-dynamic operation conditions

Alkaline water electrolysis (AWE) has the highest technological maturity among all the water electrolysis technologies for hydrogen production, however, reducing the minimum load boundary and improving the electrolysis efficiency are the technical challenges of the AWE system that still exist and urgently require optimization. The minimum load is primarily limited by the hydrogen to oxygen (HTO) from cross-diaphragm transfer and lye mixing, with HTO above 2.0% being a significant safety risk. Reducing the lye flow rate and pressure are effective while two of the few ways by regulating the operating parameters to improve the HTO thus extend the minimum load boundary, but will worsen electrolysis efficiency. Therefore, this study proposes a synergistic regulation strategy of pressure and lye flow rate: maximizing pressure and lye flow rate during high load period to ensure high electrolysis efficiency; adjusting lye flow rate and pressure during medium load period to ensure HTO≤2.0% and maximize the electrolysis efficiency; and reducing lye flow rate and pressure to a low level during the low load period to broaden the minimum load so as to improve overall efficiency of AWE system when loading with fluctuant green electric. This work elaborates the HTO routes, influencing factors and parameter optimization mechanism by building a system-level steady-state and dynamic gas purity model. The optimal combination curve of pressure and lye flow rate is obtained and its control effect on performance parameters, in terms of minimum load, system energy consumption, energy utilization, electrolysis efficiency and so on, is compared and verified in high dynamic wind and photovoltaic (PV) power scenarios. Finally, the optimal wind & PV power ratios are explored based on the optimal operation curve, which will provide a reference for the future large-scale development of hydrogen production scenarios direct-coupled with wind and PV power. The minimum load is extended from 42.0% in the lye flow rate alone control to 21.2% in the pressure alone control and finally to 15.6% in the lye flow rate and pressure synergistic control method. In the absence of electrical replenishment, wind and PV energy utilization efficiency can reach up to 98.3% and 95.6%, respectively.

Experimental studies on dynamic performance of 250-kW alkaline electrolytic system

Alkaline water electrolysis is a mature hydrogen production technology and an important means for future large-scale green hydrogen production and electrical energy storage, while enhancing and optimizing its dynamic characteristic speed is the urgent problem to achieve this goal. In this study, the dynamic response characteristics of the system current, voltage, temperature, hydrogen to oxygen (HTO) and pressure parameters are experimentally investigated at two levels (start-stop and variable load processes) and three-time scales (hours, minutes and seconds) based on the 250-kW industrial alkaline water electrolysis system. The experimental study of cold start (25 °C)→full load (90 °C)→hot shutdown (75 °C)→hot start (70 °C)→full load (90 °C)→cold shutdown (30 °C) revealed that the response time of start-stop process is hourly and temperature is the main limiting factor. The response time of HTO is on the order of minutes based on the variable load test: full load (3500 A, 1.7 MPa)→minimum load (1400 A, 1.7 MPa)→full load (3500 A, 1.7 MPa)→minimum load (800 A, 0.6 MPa). The response of HTO to parameter changes has severe time delay and inertia links, and the latter with significantly longer response time. The response time for different current step is in the order of seconds. This experimental study points out the dynamic performance level of industrial-scale alkaline water electrolysis system at the present stage and provides directions for the optimization of dynamic performance indexes, which is an important guideline for designing control strategies that integrate with renewable energy sources.

Synergistically enhanced electrocatalytic performance of NiO infused crystalline graphitic carbon towards overall water splitting

Developing high-performance electrocatalysts to achieve catalytically active and kinetically feasible reaction sites with structural strength is challenging. Herein, a facile hydrothermal method is reported for compositing the NiO nanoparticles with high crystalline graphitic carbon (GC). With superior electronic conductivity, GC is functionalized with active NiO (NiO/GC) to improve electrocatalytic activity both intrinsically and extrinsically. The NiO/GC electrocatalyst exhibits a minimal overpotential of 260 mV and 177 mV at 10 mA cm−2 with a Tafel slope value of 63 mV dec−1 and 119 mV dec−1 during the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER), respectively. The alkaline water electrolysis system designed with NiO/GC as a bifunctional electrocatalyst performs overall water splitting at a low cell voltage of 1.7 V to deliver 10 mA cm−2.

Hierarchical consistency tracking (HCT) model: A rapid and efficient approach for dynamic thermal analysis of alkaline water electrolysis

The intermittent power output of renewable energy sources necessitates alkaline water electrolysis (AWE) systems to operate under fluctuating conditions, emphasizing the need for a comprehensive understanding of their dynamic thermal behavior. However, current methods for dynamic thermal detection in AWE systems suffer from limitations such as limited temperature signals, insufficient temperature distribution analysis, and a lack of dynamic thermal analysis methods. To address these challenges, a hierarchical consistency tracking (HCT) model is proposed, which incorporates three hierarchical procedures: segmental characteristic temperatures (CT) extraction, surface consistency extraction, and dynamic consistency tracking. By analyzing infrared images captured from the electrolyzer, the HCT model extracts CT, quantifies temperature distribution patterns, and enables the assessment of thermal consistency during dynamic processes. This model offers a rapid and efficient approach with several advantages, including a more comprehensive understanding of temperature distribution, quantification of dynamic thermal consistency, and optimization of operating parameters and internal structures to improve temperature uniformity. Moreover, the HCT model provides a cost-effective and efficient solution for thermal characterization by eliminating the need for additional temperature sensors during dynamic operation.