Xie Xiaowei, Clark Spotte-Smith Evan Walter, Wen Mingjian, Patel Hetal D, Blau Samuel M, Persson Kristin A
Department of Chemistry, University of California, Berkeley, California 94720, United States.
Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
J Am Chem Soc. 2021 Aug 25;143(33):13245-13258. doi: 10.1021/jacs.1c05807. Epub 2021 Aug 11.
Interfacial reactions are notoriously difficult to characterize, and robust prediction of the chemical evolution and associated functionality of the resulting surface film is one of the grand challenges of materials chemistry. The solid-electrolyte interphase (SEI), critical to Li-ion batteries (LIBs), exemplifies such a surface film, and despite decades of work, considerable controversy remains regarding the major components of the SEI as well as their formation mechanisms. Here we use a reaction network to investigate whether lithium ethylene monocarbonate (LEMC) or lithium ethylene dicarbonate (LEDC) is the major organic component of the LIB SEI. Our data-driven, automated methodology is based on a systematic generation of relevant species using a general fragmentation/recombination procedure which provides the basis for a vast thermodynamic reaction landscape, calculated with density functional theory. The shortest pathfinding algorithms are employed to explore the reaction landscape and obtain previously proposed formation mechanisms of LEMC as well as several new reaction pathways and intermediates. For example, we identify two novel LEMC formation mechanisms: one which involves LiH generation and another that involves breaking the (CH)O-C(═O)OLi bond in LEDC. Most importantly, we find that all identified paths, which are also kinetically favorable under the explored conditions, require water as a reactant. This condition severely limits the amount of LEMC that can form, as compared with LEDC, a conclusion that has direct impact on the SEI formation in Li-ion energy storage systems. Finally, the data-driven framework presented here is generally applicable to any electrochemical system and expected to improve our understanding of surface passivation.
界面反应极难表征，对所得表面膜的化学演化及相关功能进行可靠预测是材料化学的重大挑战之一。对锂离子电池（LIB）至关重要的固体电解质界面（SEI）就是这样一种表面膜，尽管经过数十年研究，但关于SEI的主要成分及其形成机制仍存在相当大的争议。在此，我们使用反应网络来研究碳酸亚乙烯酯锂（LEMC）还是碳酸亚乙烯酯二锂（LEDC）是LIB SEI的主要有机成分。我们基于数据驱动的自动化方法，通过通用的碎片化/重组程序系统地生成相关物种，这为利用密度泛函理论计算的广阔热力学反应图景提供了基础。采用最短路径寻找算法来探索反应图景，并获得先前提出的LEMC形成机制以及几种新的反应途径和中间体。例如，我们确定了两种新的LEMC形成机制：一种涉及氢化锂的生成，另一种涉及在LEDC中打破（CH）O - C（═O）OLi键。最重要的是，我们发现所有确定的路径在探索的条件下在动力学上也是有利的，都需要水作为反应物。与LEDC相比，这种条件严重限制了可形成的LEMC的量，这一结论对锂离子储能系统中的SEI形成有直接影响。最后，这里提出的数据驱动框架普遍适用于任何电化学系统，并有望增进我们对表面钝化的理解。
