Density Functional Tight-Binding Model for Lithium-Silicon Alloys

被引:5
|
作者
Oviedo, Maria Belen [1 ,2 ]
Fernandez, Francisco [3 ]
Otero, Manuel [3 ]
Leiva, Ezequiel P. M. [1 ,2 ]
Paz, Sergio Alexis [1 ,2 ]
机构
[1] Univ Nacl Cordoba, Fac Ciencias Quim, Dept Quim Teor & Computac, X5000HUA, Cordoba, Argentina
[2] Consejo Nacl Invest Cient & Tecn, INFIQC, X5000HUA, Cordoba, Argentina
[3] Consejo Nacl Invest Cient & Tecn, IFEG, X5000HUA, Cordoba, Argentina
来源
JOURNAL OF PHYSICAL CHEMISTRY A | 2023年 / 127卷 / 11期
关键词
1ST PRINCIPLES; ANODES; SIMULATIONS; CHALLENGES;
D O I
10.1021/acs.jpca.3c00075
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The predictive power of molecular dynamic simulations is mainly restricted by the time scale and model accuracy. Many systems of current relevance are of such complexity that they require addressing both issues simultaneously. This is the case of silicon electrodes in Li-ion batteries, where different LixSi alloys are formed during charge/discharge cycles. While first-principles treatments for this system are seriously limited by the computational cost of exploring its large conformational space, classical force fields are not transferable enough to represent it accurately. Density Functional Tight Binding (DFTB) is an intermediate complexity approach capable of capturing the electronic nature of different environments with a relatively low computational cost. In this work, we present a new set of DFTB parameters suited to model amorphous LixSi alloys. LixSi is the usual finding upon cycling the Si electrodes in the presence of Li ions. The model parameters are constructed with a particular emphasis on their transferability for the entire LixSi composition range. This is achieved by introducing a new optimization procedure that weights stoichiometries differently to improve the prediction of their formation energies. The resulting model is shown to be robust for predicting crystal and amorphous structures for the different compositions, giving excellent agreement with DFT calculations and outperforming state-of-the-art ReaxFF potentials.
引用
收藏
页码:2637 / 2645
页数:9
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