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Association between cations and anions plays an important role in the interfacial structure of room-temperature ionic liquids (ILs) and their electrochemical performance. Whereas great efforts have been devoted to investigating the association effect on the equilibrium properties of ILs, a molecular-level understanding of the charging dynamics is yet to be established. Here, we propose a theoretical procedure combining reaction kinetics and the modified Poisson-Nernst-Planck (MPNP) equations to study the influences of ionic association on the dynamics of electrical double layer (EDL) in response to an applied voltage. The ionic association introduces a new decay length λS and relaxation time scale τRC=λSL/D, where L is the system size and D is ion diffusivity, that are distinctively different those corresponding to non-associative systems. Analytical expressions have been obtained to reveal the quantitative relations between the dynamic timescales and the association strength.

The human perception system's information processing is intricately linked to the nonlinear response and gating effect of neurons. While piezoionics holds potential in emulating the pressure sensing capability of biological skin, the incorporation of information processing functions seems neglected. Here, ionic gating behavior in piezoionic hydrogels is uncovered as a notable extension beyond the previously observed linear responses. The hydrogel can generate remarkably high voltages (700 mV) and currents (7 mA) when indentation forces surpass the threshold. Through a comprehensive analysis involving simulations and experimental investigations, it is proposed that the gating behavior emerges due to significant diffusion differences between cations and anions. To showcase the practical implications of this breakthrough, the piezoionic hydrogels are successfully integrated with prostheses and robot hands, demonstrating that the gating effect enables accurate discrimination between gentle and harsh touch. The advancement in neuromimetic tactile sensing has significant potential for emerging applications such as humanoid robotics and biomedical engineering, offering valuable opportunities for further development of embodied neuromorphic intelligence., (© 2024 Wiley‐VCH GmbH.)

Electrically resistive CaF 2 -based slags are extensively used in many metallurgical processes such as electroslag remelting (ESR). Chemical and electrochemical reactions as well as transport of ions in the molten slag (electrolyte) are critical phenomena for those processes. In this paper, an electrochemical system including two parallel, planar electrodes and a completely dissociated electrolyte operating under a DC voltage is modeled. The transport of ions by electro-migration and diffusion is modeled by solving the Poisson–Nernst–Planck (PNP) equations using the Finite Volume Method (FVM). The non-linear Butler–Volmer equations are implemented to describe the boundary condition for the reacting ions at the electrode–electrolyte interface. Firstly, we study a binary symmetrical electrolyte, which was previously addressed by Bazant et al. (2005), to verify the numerical model. Secondly, we employed the model to investigate our target CaF 2 –FeO system. The electrolyte is consisted of reacting (Fe2+) and non-reacting (Ca+2, O2−, F−) ions. Spatial distributions of concentrations of ions, charge density, and electric potential across the electrolyte at steady state are analyzed. It is found that the Faradaic reaction of the ferrous ion (Fe2+) has negligible impact on the electric potential field at very low current density (<1 A m−2). The strong impact of electric double layer (EDL) capacitance on the system behavior is addressed throughout our analysis. Furthermore, a linear relationship among activation (surface) overpotential and current density (<1600 A m−2) is observed. The simulation results helps to explain some phenomena observed in the ESR process. The higher melt rate for an anodic ESR electrode than a cathodic one is linked to the interfacial potential drop. It is found that the anodic potential drop near the anode is larger than the cathodic voltage drop near the cathode. The results are tested against an experiment. [ABSTRACT FROM AUTHOR]

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Two mathematical approaches have been compared for modeling the electrical behavior (e.g., electric/current density field) of an electrolyte. The first approach uses the traditional Ohmic method (Laplace equation) based on the assumption of a uniform concentration of ions in the electrolyte. The second approach utilizes the ionic transport method that takes into account the effect of electrochemical transport/reaction of ions assuming a quasi-electro neutral bulk for the electrolyte. For the latter, the Poisson-Nernst-Planck (PNP) equations are employed to include impacts of the non-uniformity of the concentration of ions on the electrical pattern of the electrolyte. Demonstratively, a 2D case was studied. It comprises two unequally sized electrodes, which are separated by the electrolyte. Findings show that the electrical behavior of the electrolyte remains unchanged using an Ohmic approach, regardless of variations in operational parameters such as applied voltage and electrode polarity. In contrast, the electrical behavior in response to the operational parameters is found to be significantly influenced using the ionic transport approach. Therefore, Ohm’s law is invalid in the bulk of an electrolyte, when a non-uniform concentration field of ions exists. Ultimately, the obtained results helped to propose an explanation on a commonly observed phenomenon (melt rate-polarity relationship) during the DC operation of the electroslag remelting (ESR) process. [ABSTRACT FROM AUTHOR]

Smart modulation of bioelectric signals is of great significance for the development of brain-computer interfaces, bio-computers, and other technologies. The regulation and transmission of bioelectrical signals are realized through the synergistic action of various ion channels in organisms. The bionic nanochannels, which have similar physiological working environment and ion rectification as their biological counterparts, can be used to construct ion rectifier bridges to modulate the bioelectric signals. Here, the artificial smart ionic rectifier bridge with light response is constructed by anodic aluminum oxide (AAO)/poly (spiropyran acrylate) (PSP) nanochannels. The output ion current of the rectifier bridge can be switched between "ON" and "OFF" states by irradiation with UV and visible (Vis) light, and the conversion efficiency (η) of the system in "ON" state is ≈70.5%. The controllable modulation of brain wave-like signal can be realized by ionic rectifier bridge. The ion transport properties and processes of ion rectifier bridges are explained using theoretical calculations based on Poisson-Nernst-Planck (PNP) equations. These findings have significant implications for the understanding of the intelligent ionic circuit and combination of artificial smart ionic channels to organisms, which provide new avenues for development of intelligent ion devices., (© 2022 Wiley-VCH GmbH.)