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In alkaline water electrolysis, gas bubble coverage of the electrode surface is directly linked with an increase in cell potential. Ultrasonic field presence in water electrolysis has been proven effective in removing gas bubbles from the electrode and enhancing mass transfer and bubble removal. Most studies regarding water electrolysis under sonification focused on low-concentration NaOH electrolyte solutions so there is a lack of information regarding operating conditions similar to commercial solutions. This work focused on an experimental evaluation of the effect of an ultrasonic field with a 40 kHz frequency on water electrolysis using a lab-scale electrolyser with three different KOH solutions varying in concentration (15, 25, 35% (w/w)) at 30, 40, 50, 60 °C. A reduction in cell potential was registered across all test conditions and it was maximum for 15 and 25% KOH solutions at 30 °C with 52 and 34 mV, respectively, and decreased with an increase in temperature. For a 35% KOH solution, the cell potential reduction stayed constant across all temperatures (16–19 mV). This difference was thought to be caused by the ultrasonic frequency and power and therefore required further testing. To further investigate the effect of gas bubble accumulation on the electrode surface, measurements of hydrogen bubbles' critical diameter were taken. It was found that a higher electrolyte concentration results in a lower critical diameter (0.404, 0.356, and 0.293 mm with a 15, 25, and 35% KOH, respectively) assumed to be a consequence of higher viscosity and gas formation rate at higher concentrations. • Effect of ultrasonic field is studied in water alkaline electrolysis. • Three KOH solutions varying in concentration (15, 25, 35% (w/w)) at 30, 40, 50, 60 °C were tested. • A reduction in overpotential was registered across all test conditions. • Overpotential was observed to decrease with increasing temperatures. • Ultrasonic field is effective removing gas bubbles from the electrode and enhancing mass transfer and bubble removal. [ABSTRACT FROM AUTHOR]

This article explores the novel application of a trained artificial neural network (ANN) in the prediction of vanadium redox flow battery behaviour and compares its performance with that of a two-dimensional numerical model. The aim is to evaluate the capability of two ANNs, one for predicting the cell potential and one for the overpotential under various operating conditions. The two-dimensional model, previously validated with experimental data, was used to generate data to train and test the ANNs. The results show that the first ANN precisely predicts the cell voltage under different states of charge and current density conditions in both the charge and discharge modes. The second ANN, which is responsible for the overpotential calculation, can accurately predict the overpotential across the cell domains, with the lowest confidence near high-gradient areas such as the electrode membrane and domain boundaries. Furthermore, the computational time is substantially reduced, making ANNs a suitable option for the fast understanding and optimisation of VRFBs. [ABSTRACT FROM AUTHOR]

Formation of gas hydrates is an important feature of water systems. It occurs undesirably in natural gas pipelines, but also in deep‐sea deposits and unfreezing permafrost. However, the natural occurrence is of particular interest because methane hydrates have one of the highest energy densities of all naturally occurring forms of methane. Therefore, an accurate description of its thermodynamic properties is required. In this work, we demonstrate how the material properties of methane hydrate can be more easily calculated compared to ab initio methods. Furthermore, it is shown how the material properties depend on the cage occupancy by using the comparably fast self‐consistent‐charge density‐functional tight‐binding (SCC‐DFTB) method. The cell potential is calculated and compared to a numerical as well as an ab initio model, and is in good agreement with the literature. [ABSTRACT FROM AUTHOR]

This article explores the novel application of a trained artificial neural network (ANN) in the prediction of vanadium redox flow battery behaviour and compares its performance with that of a two-dimensional numerical model. The aim is to evaluate the capability of two ANNs, one for predicting the cell potential and one for the overpotential under various operating conditions. The two-dimensional model, previously validated with experimental data, was used to generate data to train and test the ANNs. The results show that the first ANN precisely predicts the cell voltage under different states of charge and current density conditions in both the charge and discharge modes. The second ANN, which is responsible for the overpotential calculation, can accurately predict the overpotential across the cell domains, with the lowest confidence near high-gradient areas such as the electrode membrane and domain boundaries. Furthermore, the computational time is substantially reduced, making ANNs a suitable option for the fast understanding and optimisation of VRFBs.

Advanced zero-gap alkaline electrolyzers can be operated at a significantly higher current density than traditional alkaline electrolyzers. We have investigated how their performance is influenced by diaphragm thickness, temperature and pressure. For this a semi-empirical current-voltage model has been developed based on experimental data of a 20 Nm3/h electrolyzer. The model was extrapolated to thinner diaphragm thicknesses and higher temperatures showing that a nominal current density of 1.8 A cm−2 is possible with a 0.1 mm diaphragm at 100 °C. However, these operating parameters also lead to increased gas crossover, which limits the ability to operate at low loads. A gas crossover model has been developed, which shows that crossover is mainly driven by diffusive transport of hydrogen, caused by a high local supersaturation at the diaphragm surface. To enable a low minimum load of 10% the operating pressure should be kept below 8 bara. [Display omitted] • A nominal current density of 1.8 A cm−2 seems achievable for alkaline electrolysis. • To enable a minimum load of 10%, the pressure is preferably kept below 8 bara. • Gas crossover is mainly driven by diffusive hydrogen transport. • Supersaturation at the diaphragm interface plays an important role. [ABSTRACT FROM AUTHOR]

The influence of low‐cost anode materials, aluminum, and graphite on the sediment microbial fuel cell (SMFC) performance is investigated. The cathode in both cells is a high‐conductive pencil electrode. The open‐circuit potentials of the graphite sediment microbial fuel cell (CSMFC) and the aluminum sediment microbial fuel cell (ASMFC) are 600 mV and 1103 mV, respectively. The microbial metabolic activity in polluted marine sediment creates a large potential difference at the marine sediment/seawater interface. The sustainable electrical power from CSMFC and ASMFC are 680 mW.m−2 and 930 mW.m−2 respectively. The high cell potentials of both cells are achieved at ambient temperature. The designed SMFCs could power oceanographic instruments and biosensors in the coastal ocean. The total viable bacterial count (TVBC) and biological parameters of pore water are related to the high cell potential. The higher open‐circuit potential of ASMFC than CSMFC is mainly attributed to the lower charge transfer resistance of aluminum than graphite. This high performance is confirmed by using electrochemical impedance spectroscopy (EIS). The charge transfer resistance (Rct) of aluminum and graphite are 1600 and 2050 Ohm.cm2, respectively. The electrical conductivity of a thin film of aluminum and graphite are 40.1× 104 and 9.99× 103 Siemens/cm, respectively. The electrical resistivity of the ASMFC and CSMFC are 1.506×10−5 and 2.25661×10−5 Ω.m, respectively. These results strongly suggest that ASMFC has a higher electrical power density than CSMFC due to the lower charge transfer resistance, the good electrical conductivity of aluminum, and the lower electrical resistivity of ASMFC. [ABSTRACT FROM AUTHOR]

Similar to an IC (Internal combustion) engine which requires cooling to operate at optimum temperature for better efficiency; electric vehicles do require a similar system. There are various methods used in the current market for thermal management of batteries, of these our paper focuses on phase change materials (PCM). This cooling strategy can store an enormous amount of heat produced inside a battery because of its high latent heat capability. A 3D model of the battery using the multi-scale multi-dimension model (MSMD) for battery simulation and Solidification/melting models were used to showcase the melting of PCM due to the heat generated from a cell. ANSYS fluent was used to carry out the simulations. These computations are carried out at different C-rate to find the time taken for a battery to discharge and to find the impact of C-rate on PCM performance. Besides, temperature data for the cell was recorded before and after PCM was involved to compare the temperature difference between various PCM's. [ABSTRACT FROM AUTHOR]

Integrating anodic biomass valorization with carbon dioxide electroreduction (CO 2 RR) can produce value-added chemicals on both the cathode and anode; however, anodic oxidation still suffers from high overpotential. Herein, a photothermal-assisted method was developed to reduce the potential of 5-hydroxymethyl furfural (HMF) electrooxidation. Capitalizing on the copious oxygen vacancies, defective Co 3 O 4 (D-Co 3 O 4 ) exhibited a stronger photothermal effect, delivering a local temperature of 175.47 °C under near infrared light illumination. The photothermal assistance decreased the oxidation potential of HMF from 1.7 V over pristine Co 3 O 4 to 1.37 V over D-Co 3 O 4 to achieve a target current density of 30 mA cm -2 , with 2,5-furandicarboxylic acid as the primary product. Mechanistic analysis disclosed that the photothermal effect did not change the HMF oxidation route but greatly enhanced the adsorption capacity of HMF. Meanwhile, faster electron transfer for direct HMF oxidation and the surface conversion to cobalt (oxy)hydroxide, which contributed to indirect HMF oxidation, was observed. Thus, rapid HMF conversion was realized, as evidenced by in situ surface-enhanced infrared spectroscopy. Upon coupling cathodic CO 2 RR with an atomically dispersed Ni-N/C catalyst, the Faradaic efficiencies of CO (cathode) and 2,5-furandicarboxylic acid (FDCA, anode) exceeded 90.0 % under a low cell potential of 1.77 V., (© 2024 Wiley-VCH GmbH.)

Astrocytes represent a diverse and morphologically complex group of glial cells critical for shaping and maintaining nervous system homeostasis, as well as responding to injuries. Understanding the origins of astroglial heterogeneity, originated from a limited number of progenitors, has been the focus of many studies. Most of these investigations have centered on protoplasmic and pial astrocytes, while the clonal relationship of fibrous astrocytes or juxtavascular astrocytes has remained relatively unexplored. In this study, we sought to elucidate the morphological diversity and clonal distribution of astrocytes across adult cortical layers, with particular emphasis on their ontogenetic origins. Using the StarTrack lineage tracing tool, we explored the characteristics of adult astroglial clones derived from single and specific progenitors at various embryonic stages. Our results revealed a heterogeneous spatial distribution of astroglial clones, characterized by variations in location, clonal size, and rostro-caudal dispersion. While a considerable proportion of clones were confined within specific cortical layers, others displayed sibling cells crossing layer boundaries. Notably, we observed a correlation between clone location and developmental stage at earlier embryonic stages, although this relationship diminished in later stages. Fibrous astrocyte clones were exclusively confined to the corpus callosum. In contrast, protoplasmic or juxtavascular clones were located in either the upper or lower cortical layers, with certain clones displayed sibling cells distributed across both regions. Our findings underscore the developmental origins and spatial distribution of astroglial clones within cortical layers, providing new insights into the interplay between their morphology, clonal sizes, and progenitor heterogeneity., (© 2024 The Authors. GLIA published by Wiley Periodicals LLC.)

Similar to an IC (Internal combustion) engine which requires cooling to operate at optimum temperature for better efficiency; electric vehicles do require a similar system. There are various methods used in the current market for thermal management of batteries, of these our paper focuses on phase change materials (PCM). This cooling strategy can store an enormous amount of heat produced inside a battery because of its high latent heat capability. A 3D model of the battery using the multi-scale multi-dimension model (MSMD) for battery simulation and Solidification/melting models were used to showcase the melting of PCM due to the heat generated from a cell. ANSYS fluent was used to carry out the simulations. These computations are carried out at different C-rate to find the time taken for a battery to discharge and to find the impact of C-rate on PCM performance. Besides, temperature data for the cell was recorded before and after PCM was involved to compare the temperature difference between various PCM's.

• The activity coefficients of the KCl in the KCl-SrCl 2 -H 2 O solutions at 278.15 K were determined by cell potential method. • The mixed ion interaction parameters of Pitzer model in KCl-SrCl 2 -H 2 O solutions at 278.15 K were fitted by multiple linear regression. • The mean activity coefficients of SrCl 2 , water activities a w , osmotic coefficients Φ, excess Gibbs free energies G E of the KCl-SrCl 2 -H 2 O solutions at 278.15 K were calculated by Pitzer model. • The experimental and predicted solubilities in KCl-SrCl 2 -H 2 O system at 278.15 K were compared and the comparison results were good agreement. The cell potentials were determined by the cell without liquid junction K-ISE |KCl (m 0) |Cl-ISE firstly. Using Nernst equation and the measured cell potentials, the response slope κ of the single-salt electrode and the standard cell potential E 0 were fitted well. The total ionic strengths range from 0.0100 to 1.0000 mol·kg−1, the cell without liquid junction K-ISE |KCl (m 1), SrCl 2 (m 2) |Cl-ISE is used to determine the mean activity coefficients of KCl in the KCl + SrCl 2 + H 2 O solutions, the ionic strength fractions y b of SrCl 2 are 0.8, 0.6, 0.4, 0.2 and 0. According to the measured cell potentials, the mean activity coefficients of KCl in the KCl + SrCl 2 + H 2 O solutions were calculated by Nernst equation, and the relationship diagrams between the mean activity coefficients and total ionic strengths of the mixed solutions are drawn at 278.15 K. The mixed interaction parameters θ K,Sr , and ψ K,Sr,Cl in the Pitzer model were also obtained by regression of the mean activity coefficients of KCl in the mixed solutions. The mean activity coefficients of SrCl 2 , the osmotic coefficients, the water activities, and the excess Gibbs free energies of the mixed solutions were also calculated by Pitzer equations. Additionally, in order to verify the mixed ion parameters of Pitzer model fitted in this work, the isothermal dissolution equilibrium method is used to measure experimentally the phase equilibria of the mixed solutions at 278.15 K, and then the Pitzer equations and the mixed ion parameters are used to predict the solubilities of the salts in the mixed solutions at 278.15 K. The experimental and predicted phase diagrams are good agreement. [ABSTRACT FROM AUTHOR]

• Synthetic current density profiles with renewable power characteristics. • Pressurized alkaline water electrolyzer. • Experimental evaluation of dynamic operating concepts. • Enhancing the part-load operating range by lowering the gas contamination. [Display omitted] Synthetic current density profiles with wind and photovoltaic power characteristics were calculated by autoregressive-moving-average (ARMA) models for the experimental evaluation of dynamic operating concepts for alkaline water electrolyzers powered by renewable energy. The selected operating concepts included switching between mixed and split electrolyte cycles and adapting the liquid electrolyte volume flow rate depending on the current density. All experiments were carried out at a pressure of 7 bar, a temperature of 60 °C and with an aqueous potassium hydroxide solution with 32 wt.% KOH as the electrolyte. The dynamic operating concepts were compared to stationary experiments with mixed electrolyte cycles, and the experimental evaluation showed that the selected operating concepts were able to reduce the gas impurity compared to the reference operating conditions without a noticeable increase of the cell potential. Therefore, the overall system efficiency and process safety could be enhanced by this approach. [ABSTRACT FROM AUTHOR]