2024-09-24 アルゴンヌ国立研究所(ANL)
＜関連情報＞
- https://www.anl.gov/article/innovative-electrolytes-could-transform-steelmaking-and-beyond
- https://www.sciencedirect.com/science/article/abs/pii/S2451929424003747?via%3Dihub
電解質設計の統一原理としての陰イオン由来の接触イオン対形成 Anion-derived contact ion pairing as a unifying principle for electrolyte design
Stefan Ilic, Sydney N. Lavan, Justin G. Connell
Chem Available online: 26 August 2024
DOI:https://doi.org/10.1016/j.chempr.2024.07.031
Graphical abstract
The bigger picture
Electrochemistry-enabled decarbonization requires an improved understanding of ion coordination and transport to develop electrolytes compatible with extreme operating conditions. Many strategies focus on reducing free solvent to improve performance; however, less attention is given to the anion-derived contact ion pair (CIP) formation that takes place as a result. It is remarkable that, despite stark differences in system properties, similar benefits can be realized in CIP-forming electrolytes spanning aqueous/non-aqueous and mono-/multivalent systems across orders of magnitude of concentration. The determination of new descriptors, built upon the ion-pairing concepts summarized in this review, is key to developing universal design rules. An integrated approach combining multiscale computations and targeted experiments is essential to continually refine computational insights with experimental validation to accelerate the discovery of new, high-performance electrolytes.
Summary
Enabling new electrochemical technologies requires systems that can operate under ever-more demanding conditions, and progress in energy storage applications reveals tantalizing opportunities to reimagine electrolyte design for performance at extreme potentials. A common thread among these innovations is the formation of significant populations of contact ion pairs (CIPs) in the electrolyte, regardless of the specific cation chemistry or solvent system. The examples summarized in this review suggest that a set of general electrolyte design rules likely exists, where the purposeful selection of anion chemistry can yield CIP structures with tunable control over reaction thermodynamics, kinetics, and interphase chemistry. Identifying the relevant descriptors for high-performance, anion-derived CIP structures can be achieved utilizing a combined experimental and computational approach, aided by machine learning and artificial intelligence, to more rapidly survey the vast combinatorial space available and to enable a new generation of electrolytes for decarbonized electrochemical processes at scale.
