Differentiable OPLS Force-Field Parameterization for Ionic Electrolytes and High-Throughput Application to Lithium-Ion Batteries

IF 5.8 1区 化学 Q2 CHEMISTRY, PHYSICAL
Haichao Huang,Zilin Chen,Qi Liu,Tianqi Zhao,Yunpei Liu,Guotao Qiu,Jianhui Chen,Zhen Li,Wenshuo Liang,Minsung Cho,Manxue Zhang,Feiyu Kang,Xiaolong Zou,Yidan Cao,Xushan Zhao,Ziqi Cheng,Ye Mei
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Abstract

The rational design of lithium-ion battery (LIB) electrolytes is severely impeded by the vast chemical space of solvent–salt combinations and the inefficiency of empirical trial-and-error approaches. Molecular dynamics (MD) bridges microscopic solvation structures and macroscopic physicochemical properties, but classical force fields (FFs) often lack accuracy for multicomponent electrolytes. To address this, we develop an automated differentiable OPLS-AA FF parametrization workflow tailored for ionic electrolytes. It employs topology-guided atom typing to reduce parameter redundancy and optimizes Lennard-Jones parameters via the DMFF framework. A uniform charge-scaling scheme approximates condensed-phase charge transfer and polarization. Density serves as the structural/thermodynamic fitting target, while ionic conductivity provides the independent transport benchmark, ensuring balanced accuracy. Rigorous convergence tests establish a standardized protocol with ∼100,000-atom systems and 35–40 ns NVT trajectories for reliable transport property calculations. Furthermore, high-throughput simulations of over 10,000 formulations─encompassing 67 solvents and 15 lithium salts─are performed on Tianqiong, a special-purpose supercomputer for molecular dynamics simulations that has been validated to deliver numerically equivalent results to GPUs with superior efficiency. A comprehensive data set is generated covering five key electrolyte properties. The t-SNE visualization reveals partial clustering of distinct salt chemistries, continuous property gradients as functions of salt concentration and temperature, and internal physical self-consistency across the measured electrolyte parameters while simultaneously identifying solvent components as another critical performance determinant. The accurate, transferable FF and the rich data resource establish a robust foundation for future data-driven design of ionic electrolytes.

Abstract Image

离子电解质的可微ops力场参数化及其在锂离子电池中的高通量应用
锂离子电池(LIB)电解质的合理设计受到溶剂-盐组合的巨大化学空间和经验试错方法效率低下的严重阻碍。分子动力学(MD)连接了微观溶剂化结构和宏观物理化学性质,但经典力场(FFs)对于多组分电解质往往缺乏准确性。为了解决这个问题,我们开发了一个为离子电解质量身定制的自动化可微分OPLS-AA FF参数化工作流程。它采用拓扑引导的原子类型来减少参数冗余,并通过DMFF框架优化Lennard-Jones参数。均匀电荷标度方案近似于凝聚相电荷转移和极化。密度作为结构/热力学拟合目标,而离子电导率提供独立的输运基准,确保平衡的准确性。严格的收敛测试为可靠的输运性质计算建立了标准化协议,该协议具有~ 100,000原子系统和35-40 ns NVT轨迹。此外,还在用于分子动力学模拟的专用超级计算机“天琼”上进行了超过10,000种配方(包括67种溶剂和15种锂盐)的高通量模拟,该计算机已被验证能够以卓越的效率为gpu提供数值等效的结果。生成了涵盖五种关键电解质性质的综合数据集。t-SNE可视化显示了不同盐化学的部分聚类,连续的性能梯度作为盐浓度和温度的函数,以及测量电解质参数之间的内部物理自一致性,同时确定溶剂成分是另一个关键的性能决定因素。准确、可转移的FF和丰富的数据资源为未来离子电解质的数据驱动设计奠定了坚实的基础。
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来源期刊
Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation 化学-物理:原子、分子和化学物理
CiteScore
9.90
自引率
16.40%
发文量
568
审稿时长
1 months
期刊介绍: The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.
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