Acid-base flow batteries (ABFB) are a promising and environmentally benign class of flow batteries that utilize neutralization energy. Among the other flow batteries, ABFBs stand out with low cost and high solubility of the electrolytes and the possibility to harvest neutralization energy of acidic and alkaline wastewaters. However, the main ABFB issues, such as low power caused by discharge current limitation and low energy density, are limiting the possibility of their implementation. In this work, a novel two-membrane ABFB with two hydrogen electrodes was developed to overcome main ABFB issues. The proposed concept demonstrated high power density up to 6.1 mW cm at 13 mA cm . It was shown that battery performance was greatly limited by negative electrode overvoltage. Analysis of the voltage losses allowed to estimate main power losses and highlight the possible ways to its minimization.

Download full-text PDF

Source
http://dx.doi.org/10.1002/cssc.202101460DOI Listing

Publication Analysis

Top Keywords

flow batteries
12
acid-base flow
8
hydrogen electrodes
8
neutralization energy
8
main abfb
8
abfb issues
8
two-membrane acid-base
4
flow
4
flow battery
4
battery hydrogen
4

Similar Publications

Significance: Cerebral blood flow (CBF) and cerebral blood volume (CBV) are key metrics for regional cerebrovascular monitoring. Simultaneous, non-invasive measurement of CBF and CBV at different brain locations would advance cerebrovascular monitoring and pave the way for brain injury detection as current brain injury diagnostic methods are often constrained by high costs, limited sensitivity, and reliance on subjective symptom reporting.

Aim: We aim to develop a multi-channel non-invasive optical system for measuring CBF and CBV at different regions of the brain simultaneously with a cost-effective, reliable, and scalable system capable of detecting potential differences in CBF and CBV across different regions of the brain.

View Article and Find Full Text PDF

Remaining useful life (RUL) prediction is a crucial aspect of the prognostics health management of lithium-ion batteries (LIBs). Owing to the influence of resampling technology, particle degradation is often observed in the particle filter-based RUL prediction of LIBs, resulting in a low prediction accuracy and large uncertainty. In this paper, a novel particle flow filter with the grey model method (GM-PFF) is proposed to forecast the RUL and state of health of batteries.

View Article and Find Full Text PDF

The tightly connected structure of polybenzimidazole (PBI) membrane can be relaxed by solvent/nonsolvent solution to achieve a high proton conductivity for vanadium redox flow battery (VRFB). However, the nature behind the solvent/nonsolvent strategy is not unraveled. This work proposes a guideline to analyze the effect of PBI membrane relaxing formulas based on the interactions between different components in membranes.

View Article and Find Full Text PDF

Fluorine-free organic framework polyelectrolyte membranes showing near frictionless ionic conductivities are gaining cognitive insights. However, the co-precipitation of COFs in the membranes often brings trade-offs to commission long-life electrochemical energy storage solutions. Herein, a durable and ionically miscible dual-ion exchange membrane based on triazine organic framework (TOF) is designed for alkaline redox flow batteries (RFB).

View Article and Find Full Text PDF

Zinc (Zn)-based batteries have been persistently challenged by the critical issue of inhomogeneous zinc deposition/stripping process on substrate surface. Herein, we reveal that zinc electrodeposition behaviors dramatically improved through the introduction of highly zincophilic copper oxide nanoparticles (CuO NPs). Strong electronic redistribution between Zn and CuO explains the high Zn affinity on CuO, with negligible nucleation overpotential.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!