Abstract

Monoelemental two-dimensional materials (borophene, silicene, etc.) are exciting candidates for electrodes in lithium-ion batteries because of their ultralight molar mass. However, these materials' lithium-ion binding mechanism can be complex as the inherited polymorphism may induce phase changes during the charge-discharge cycles. Here, we combine genetic-algorithm-based bottom-up and stochastic top-down structure searching techniques to conduct thermodynamic scrutiny of the lithiated compounds of 2D allotropes of four elements: B, Al, Si, and P. Our first-principles-based high-throughput computations unveil polymorphism-driven lithium-ion binding process and other nonidealities (e.g., bond cleavage, adsorbent phase change, and electroplating), which lacks mention in earlier works. While monolayer B (2479 mAh/g), Al (993 mAh/g), and Si (954 mAh/g) have been demonstrated here as excellent candidates for Li-ion storage, P falls short of the expectation. Our well-designed computational framework, which always searches for lithiated structures at global minima, provides convincing thermodynamical insights and realistic reversible specific-capacity values. This will expectedly open up future experimental efforts to design monoelemental two-dimensional material-based anodes with specific polymorphic structures.

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