First-principles calculations for the adsorption of lithium sulfide by zinc oxide

IF 2.9 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Jin-Ke Wei, Zhi-Xin Bai,  Wei-Zeng, Zheng-Tang Liu, Cheng-Lu Jiang
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Abstract

Context

Lithium‒sulfur batteries (LSBs) are regarded as next-generation energy storage technologies owing to their high energy density; however, their practical application is constrained by the shuttle effect of lithium polysulfides (LiPSs), which leads to capacity degradation and safety concerns. This work focuses on the adsorption mechanism of Li₂S on ZnO and investigates the microscopic mechanism by which ZnO suppresses the shuttle effect through first-principles calculations. The results demonstrate that the adsorption energy of a Li₂S molecule on the ZnO (100) facet is negative (−1.67 eV), which is thermodynamically more favorable than that on the (111) facet (1.73 eV). The Li–O ionic bonds and S–Zn covalent bonds formed between the (111) facet and the Li₂S molecule exhibit stronger coupling than those on the (100) facet, resulting in stronger overall interfacial electronic interactions. Nevertheless, the deformation magnitude of the Li–S bond on the (111) facet (9%–14%) exceeds that on the (100) facet (less than 5%). The (100) facet achieves energetically superior stable adsorption through weak bonding and low deformation, whereas the (111) facet, despite stronger bonding, has a deformation energy that surpasses the energy released by bond formation, rendering it a thermodynamically metastable configuration. Evidently, ZnO strongly adsorbs Li₂S—the final product of the shuttle effect—thereby suppressing the shuttle effect to a certain extent.

Methods

In this study, first-principles calculations were performed via the Materials Studio software via density functional theory (DFT) via the generalized gradient approximation (GGA) with the PBE functional and the GGA-PBE + U approach. Ultrasoft pseudopotentials were employed to balance computational efficiency and accuracy. Crystal models of zinc oxide (ZnO) and Li₂S were constructed via the CASTEP code. The nonpolar (100) facet and polar (111) facet of ZnO were selected for Li₂S molecule adsorption, followed by structural optimization. The adsorption energy, electronic band structure, partial density of states (PDOS), charge density, Mulliken charge population, and chemical bond lengths were subsequently calculated.

氧化锌吸附硫化锂的第一性原理计算。
背景:锂硫电池因其高能量密度被认为是下一代储能技术;然而,它们的实际应用受到多硫化锂(LiPSs)的穿梭效应的限制,这会导致容量下降和安全性问题。本文重点研究了Li₂S在ZnO上的吸附机理,并通过第一性原理计算探讨了ZnO抑制穿梭效应的微观机理。结果表明,Li₂S分子在ZnO(100)表面的吸附能为负(-1.67 eV),比在ZnO(111)表面的吸附能(1.73 eV)更有利。(111)面与Li₂S分子之间形成的Li- o离子键和S- zn共价键比(100)面的耦合更强,导致整体界面电子相互作用更强。然而,(111)面Li-S键的变形幅度(9% ~ 14%)大于(100)面(小于5%)。(100)面通过弱键合和低变形实现了能量上优越的稳定吸附,而(111)面尽管键合更强,但其变形能超过键形成释放的能量,使其成为热力学亚稳态构型。显然,ZnO对穿梭效应的最终产物Li₂有很强的吸附作用,从而在一定程度上抑制了穿梭效应。方法:在本研究中,通过Materials Studio软件通过密度泛函理论(DFT),通过PBE泛函和GGA-PBE + U方法的广义梯度近似(GGA)进行第一性原理计算。采用超软赝势来平衡计算效率和准确性。通过CASTEP程序建立了氧化锌(ZnO)和Li₂S的晶体模型。选择ZnO的非极性(100)面和极性(111)面吸附Li₂S分子,并进行结构优化。随后计算了吸附能、电子能带结构、偏态密度(PDOS)、电荷密度、Mulliken电荷居数和化学键长度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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