离子关联对锂-O2 电池氧化还原媒介物电化学的影响:建立理论框架

IF 2.9 3区 化学 Q3 CHEMISTRY, PHYSICAL Physical Chemistry Chemical Physics Pub Date : 2024-07-01 DOI:10.1039/D4CP01488J
Gabriela Horwitz, Vera Kunz, Samuel P. Niblett and Clare P. Grey
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摘要

本文提出了一个理论框架来解释氧化还原介质(RM)和电解质成分之间的相互作用如何影响电子转移动力学、热力学和催化效率。我们以 2,5-二叔丁基-1,4-苯醌(DBBQ)的离子关联为例,具体说明了这些影响。我们的分析方程揭示了所观察到的氧化还原耦合电位和电子转移速率常数是如何随着 Li+ 浓度的变化而变化的,这源于不同的氧化还原活动机制。循环伏安法测量的实验验证表明,DBBQ 在还原状态下与三个 Li+ 离子结合,在中性状态下与一个 Li+ 离子结合,导致电子转移动力学常数在 0.25M 左右达到最大值。对这一框架进行了扩展,以解释可能在 RM 氧化还原机制中发挥重要作用的其他现象:考虑了 Li+ 离子溶解及其与支撑盐反离子的结合对氧化还原过程的影响,并强调了 "游离 Li+"浓度在决定电化学行为中的作用。然后,我们再次使用 DBBQ 和模拟 Li+ 浓度对电子转移和催化动力学的影响,探讨了 Li+ 浓度对氧还原反应催化的影响。我们发现,尽管观察到的催化速率常数会随着 Li+ 浓度的增加而增加,但根据电子传递途径的不同,整个催化过程会变得更加缓慢。我们以循环伏安图为例进行了说明。所提出的理论框架的优势在于它能适应更广泛的氧化还原介质及其相互作用。通过了解这些效应,我们开辟了调整电子传递和催化动力学的新途径,从而提高了锂-O2 电池的能量效率和速率能力。虽然精确的结果可能无法应用于不同的溶剂,但我们模型的预测将为未来类似系统的研究提供一个起点,而且模型本身也很容易扩展到新的化学物质。
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The effect of ionic association on the electrochemistry of redox mediators for Li–O2 batteries: developing a theoretical framework†

A theoretical framework to explain how interactions between redox mediators (RMs) and electrolyte components impact electron transfer kinetics, thermodynamics, and catalytic efficiency is presented. Specifically focusing on ionic association, 2,5-di-tert-butyl-1,4-benzoquinone (DBBQ) is used as a case study to demonstrate these effects. Our analytical equations reveal how the observed redox couple's potential and electron transfer rate constants evolve with Li+ concentration, resulting from different redox activity mechanisms. Experimental validation by cyclic voltammetry measurements shows that DBBQ binds to three Li+ ions in its reduced state and one Li+ ion in its neutral form, leading to a maximum in the electron transfer kinetic constant at around 0.25 M. The framework is extended to account for other phenomena that can play an important role in the redox reaction mechanisms of RMs. The effect of Li+ ion solvation and its association with the supporting salt counteranion on the redox processes is considered, and the role of “free Li+” concentration in determining the electrochemical behaviour is emphasized. The impact of Li+ concentration on oxygen reduction reaction (ORR) catalysis was then explored, again using DBBQ and modelling the effects of the Li+ concentration on electron transfer and catalytic kinetics. We show that even though the observed catalytic rate constant increases with Li+ concentration, the overall catalysis can become more sluggish depending on the electron transfer pathway. Cyclic voltammograms are presented as illustrative examples. The strength of the proposed theoretical framework lies in its adaptability to a wider range of redox mediators and their interactions with the various electrolyte components and redox active molecules such as oxygen. By understanding these effects, we open up new avenues to tune electron transfer and catalytic kinetics and thus improve the energy efficiency and rate capability of Li–O2 batteries. Although exact results may not transfer to different solvents, the predictions of our model will provide a starting point for future studies of similar systems, and the model itself is easily extensible to new chemistries.

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来源期刊
Physical Chemistry Chemical Physics
Physical Chemistry Chemical Physics 化学-物理:原子、分子和化学物理
CiteScore
5.50
自引率
9.10%
发文量
2675
审稿时长
2.0 months
期刊介绍: Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.
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