Machine-Learning-Guided Insights into Solid-Electrolyte Interphase Conductivity: Are Amorphous Lithium Fluorophosphates the Key?
Peichen Zhong, Kristin A. Persson

TL;DR
This study uses machine learning and structure prediction to show that amorphous lithium difluorophosphate phases can significantly enhance ionic conductivity in battery interfaces, challenging the focus on crystalline phases.
Contribution
It identifies amorphous LiPO2F2 as a highly conductive phase with potential to improve solid-electrolyte interphase performance in lithium-ion batteries.
Findings
Amorphous LiPO2F2 exhibits projected room-temperature conductivity of 0.18 mS/cm.
Structural disorder in amorphous phases reduces the Li site-energy landscape.
Low formation energy for Li-interstitials supplies additional mobile carriers.
Abstract
Despite decades of study, the identity of the dominant \ce{Li+}-conducting phase within the inorganic SEI of Li-ion batteries remains unresolved. While the mosaic model describes LiF/\ce{Li2O}/\ce{Li2CO3} nanocrystallites within a disordered matrix, these crystalline phases inherently offer limited ionic conductivity. Growing evidence suggests that interfaces, grain boundaries, and amorphous phases may instead host the primary fast-ion pathways. Using diffusion-based generative structure prediction and machine-learning interatomic potentials (MLIPs), we investigate lithium difluorophosphate (\ce{LiPO2F2}), a key mixed-anion decomposition product of phosphorus- and fluorine-containing electrolytes. We identify a stable crystalline polymorph and demonstrate that the amorphous counterpart is conductive, with projected room-temperature mS cm and $E_\mathrm{a}…
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