用人工智能预测锂金属电解液中功能基团和盐类的电子结构影响。
A Density-Matrix Framework for Electronic-Structure Analysis of Functional-Group and Salt Effects in Lithium-Metal Electrolytes
- 基于密度矩阵构建AI平台，预测分子与离子间的电子分布。
- 发现不同功能基团对前线轨道和锂离子键合有差异化影响。
- 适合电池材料设计者快速评估电解液成分的电子特性。
锂金属电解液的反应性源于分子功能基团、Li⁺溶剂化与盐阴离子的协同作用，其本质是电子密度在供体、阴离子与阳离子中心间的重新分布，需通过空间分辨的电子结构来解析。量子化学计算虽能准确反映这一过程，但在多维设计空间中计算成本过高；而现有机器学习模型通常无法覆盖化学多样性或电解液相关读数。本文提出以密度矩阵为核心的AI平台EMolStudio，整合分子功能化、显式Li⁺第一溶剂层构建、密度矩阵预测及幂等投影，并输出前线轨道、静电势、Li⁺-供体键级与电子定域性等指标。该平台应用于163,655种功能化分子与22,500个显式Li⁺第一溶剂层簇，涵盖四种锂盐。结果表明：1）在分子尺度上，CO₂Me、CN、F/CF₃、磺酰基等功能基团通过π*受体、诱导与极化效应，显著改变前线能级、静电势与Li⁺-供体接触，且高功能化程度下累积呈亚线性；2）在显式溶剂壳中，阴离子身份重塑前线轨道局域化：LiTDI使HOMO锚定于阴离子，而LiDFOB则呈现阴离子主导的HOMO与功能基团依赖的强LUMO。EMolStudio将功能基团与盐的选择转化为与锂键形成、去溶剂化及界面反应相关的电子结构假说。
原文摘要 · Abstract (English)
The reactivity of lithium-metal electrolytes arises from the interplay of molecular functional groups, Li$^+$ solvation, and salt-anion participation. This interplay operates through the redistribution of electron density across donor, anion, and cation centers, which is most directly read out from the electronic structure resolved in space. Quantum-chemical calculations deliver such readouts faithfully, yet become computationally demanding across this multidimensional design space, and machine-learning electronic-structure models seldom cover chemically diverse solvation shells or electrolyte-relevant readouts. Here, we present a density-matrix-centered AI platform (EMolStudio) for electronic-structure prediction and analysis. Its workflow integrates molecular functionalization, explicit Li$^+$ first-shell assembly, density-matrix prediction with idempotency projection, and readouts of frontier orbitals, electrostatic potential, Li$^+$-donor bond order, and electron localization. We apply EMolStudio to 163,655 functionalized molecules and 22,500 explicit Li$^+$ first-shell clusters across four lithium salts. We find that 1) at the molecular scale, functionalization distinguishes CO$_2$Me, CN, F/CF$_3$, and sulfonyl groups by chemically distinct changes in frontier levels, electrostatic potential, and Li$^+$-donor contact, consistent with $π^*$-acceptor, inductive, and polarization contributions, with sublinear accumulation at higher degrees of functionalization; 2) in explicit solvation shells, anion identity reshapes frontier-orbital localization: LiTDI anchors the HOMO on the anion across the entire library, whereas LiDFOB pairs an anion-hosted HOMO with strongly functional-group-dependent LUMO hosting. EMolStudio thereby translates functional-group and salt choices into electronic-structure hypotheses relevant to lithium-bond formation, desolvation, and interphase reactions.
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