The influence of water channel geometry and proton mobility on the conductivity of Nafion®

Comparative Study on Proton Conductivity and Mechanism Analysis of Two Imidazole Modified Imine-Based Covalent Organic Frameworks

This work elucidates the potential impact of intramolecular H-bonds within the pore walls of covalent organic frameworks (COFs) on proton conductivity. Employing DaTta and TaTta as representative hosts, it was observed that their innate proton conductivities (σ) are both unsatisfactory and σ(DaTta)<σ(TaTta). Intriguingly, the performance of both imidazole-loaded products, Im@DaTta and Im@TaTta is greatly improved, and the σ of Im@DaTta (0.91×10-2  S cm-1 ) even surpasses that of Im@TaTta (3.73×10-3  S cm-1 ) under 100 °C and 98 % relative humidity. The structural analysis, gas adsorption tests, and activation energy calculations forecast the influence of imidazole on the H-bonded system within the framework, leading to observed changes in proton conductivity. It is hypothesized that intramolecular H-bonds within the COF framework impede efficient proton transmission. Nevertheless, the inclusion of an imidazole group disrupts these intramolecular bonds, leading to the formation of an abundance of intermolecular H-bonds within the pore channels, thus contributing to a dramatic increase in proton conductivity. The related calculation of Density Functional Theory (DFT) provides further evidence for this inference.

Metaplastic and energy-efficient biocompatible graphene artificial synaptic transistors for enhanced accuracy neuromorphic computing

CMOS-based computing systems that employ the von Neumann architecture are relatively limited when it comes to parallel data storage and processing. In contrast, the human brain is a living computational signal processing unit that operates with extreme parallelism and energy efficiency. Although numerous neuromorphic electronic devices have emerged in the last decade, most of them are rigid or contain materials that are toxic to biological systems. In this work, we report on biocompatible bilayer graphene-based artificial synaptic transistors (BLAST) capable of mimicking synaptic behavior. The BLAST devices leverage a dry ion-selective membrane, enabling long-term potentiation, with ~50 aJ/µm2 switching energy efficiency, at least an order of magnitude lower than previous reports on two-dimensional material-based artificial synapses. The devices show unique metaplasticity, a useful feature for generalizable deep neural networks, and we demonstrate that metaplastic BLASTs outperform ideal linear synapses in classic image classification tasks. With switching energy well below the 1 fJ energy estimated per biological synapse, the proposed devices are powerful candidates for bio-interfaced online learning, bridging the gap between artificial and biological neural networks.

Ion transport and limited currents in supporting electrolytes and ionic liquids

Supporting electrolytes contain inert dissolved salts to increase the conductivity, to change microenvironments near the electrodes and to assist in electrochemical reactions. This combined experimental and computational study examines the impact of supporting salts on the ion transport and related limited currents in electrochemical cells. A physical model that describes the multi-ion transport in liquid electrolytes and the resulting concentration gradients is presented. This model and its parameterization are evaluated by the measured limited current of the copper deposition in a CuSO₄ electrolyte under a gradually increasing amount of Na₂SO₄ that acts as a supporting salt. A computational sensibility analysis of the transport model reveals that the shared conductance between the ions lowers the limited currents with larger supporting salt concentrations. When the supporting salt supplies most of the conductance, the electric-field-driven transport of the electrochemically active ions becomes negligible so that the limited current drops to the diffusion-limited current that is described by Fick’s first law. The transition from diluted supporting electrolyte to the case of ionic liquids is elucidated with the transport model, highlighting the different physical transport mechanisms in a non-conducting (polar) and a conducting (ionic) solvent.

A high-performance capillary-fed electrolysis cell promises more cost-competitive renewable hydrogen

Renewable, or green, hydrogen will play a critical role in the decarbonisation of hard-to-abate sectors and will therefore be important in limiting global warming. However, renewable hydrogen is not cost-competitive with fossil fuels, due to the moderate energy efficiency and high capital costs of traditional water electrolysers. Here a unique concept of water electrolysis is introduced, wherein water is supplied to hydrogen- and oxygen-evolving electrodes via capillary-induced transport along a porous inter-electrode separator, leading to inherently bubble-free operation at the electrodes. An alkaline capillary-fed electrolysis cell of this type demonstrates water electrolysis performance exceeding commercial electrolysis cells, with a cell voltage at 0.5 A cm-2 and 85 °C of only 1.51 V, equating to 98% energy efficiency, with an energy consumption of 40.4 kWh/kg hydrogen (vs. ~47.5 kWh/kg in commercial electrolysis cells). High energy efficiency, combined with the promise of a simplified balance-of-plant, brings cost-competitive renewable hydrogen closer to reality.

A magnetic resonance and electrochemical study of the role of polymer mobility in supporting hydrogen transport in perfluorosulfonic acid membranes

Perfluorosulfonic acid (PFSA) materials have been used in polymer electrolyte membrane fuel cells (PEMFCs) as electrolyte materials due to their mechanical durability and high proton conductivity.