Bridging the gap between simulated and experimental ionic conductivities in lithium superionic conductors

Qi, Ji; Banerjee, Somesh; Zuo, Yang; Chen, Chi; Zhu, Zhuoying; Chandrappa, Manas Likhit Holekevi; Li, X.; Ong, Shyue Ping

doi:10.1016/j.mtphys.2021.100463

Cited by 66 publications

(69 citation statements)

References 77 publications

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“…Previous computational studies mainly focused on the crystalline LPS phases, such as Li 2 PS 3 , 48 − 50 Li 7 P 3 S 11 , 21 , 51 − 56 Li 3 PS 4 , 41 , 43 , 44 , 57 and Li 7 PS 6 . 58 In some studies, glassy LPS phases were approximated with moderately sized defect structures or molecular dynamics simulations at high temperatures.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence-Aided Mapping of the Structure–Composition–Conductivity Relationships of Glass–Ceramic Lithium Thiophosphate Electrolytes

et al. 2022

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Lithium thiophosphates (LPSs) with the composition (Li 2 S) x (P 2 S 5 ) 1– x are among the most promising prospective electrolyte materials for solid-state batteries (SSBs), owing to their superionic conductivity at room temperature (>10 –3 S cm –1 ), soft mechanical properties, and low grain boundary resistance. Several glass–ceramic ( gc ) LPSs with different compositions and good Li conductivity have been previously reported, but the relationship among composition, atomic structure, stability, and Li conductivity remains unclear due to the challenges in characterizing noncrystalline phases in experiments or simulations. Here, we mapped the LPS phase diagram by combining first-principles and artificial intelligence (AI) methods, integrating density functional theory, artificial neural network potentials, genetic-algorithm sampling, and ab initio molecular dynamics simulations. By means of an unsupervised structure-similarity analysis, the glassy/ceramic phases were correlated with the local structural motifs in the known LPS crystal structures, showing that the energetically most favorable Li environment varies with the composition. Based on the discovered trends in the LPS phase diagram, we propose a candidate solid-state electrolyte composition, (Li 2 S) x (P 2 S 5 ) 1– x ( x ∼ 0.725), that exhibits high ionic conductivity (>10 –2 S cm –1 ) in our simulations, thereby demonstrating a general design strategy for amorphous or glassy/ceramic solid electrolytes with enhanced conductivity and stability.

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Section: Introductionmentioning

confidence: 99%

Artificial Intelligence-Aided Mapping of the Structure–Composition–Conductivity Relationships of Glass–Ceramic Lithium Thiophosphate Electrolytes

et al. 2022

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“…57,58 Therefore, here we have restricted our study to the crystalline structures (both decomposing products and interfaces), a situation where the MTP approach has been proven to be adequate to predict ionic transport properties. 52,59,60 However, one major limitation of the current implementation of MTP is its lack of transferability from training within the binary bulk systems to being directly used in heterogeneous interfaces, requiring signicant retraining of MTP with new training sets for each distinct interface. Therefore, a complete retraining of the MTP for each interface combination considered in this work is highly resource intensive, which pushes a comprehensive examination of Li (and Na) transport across all interfaces out of the scope of our work.…”

Section: Discussionmentioning

confidence: 99%

The resistive nature of decomposing interfaces of solid electrolytes with alkali metal electrodes

et al. 2022

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“…[55,56] There-fore, here we have restricted our study to the crystalline structures (both decomposing products and interfaces), a situation where the MTP approach has been proven to be adequate to predict ion transport properties. [52,57,58] However, one major limitation of the current implementation of MTP is its lack of transferability from training within the binary bulk systems to being directly used in heterogeneous interfaces, requiring significant retraining of MTP with new training sets for each distinct interface. Therefore, a complete retraining of the MTP for each interface combination considered in this work is highly resource intensive, which pushes a comprehensive examination of Li (and Na) transport across all interfaces out of the scope of our work.…”

Section: Discussionmentioning

confidence: 99%

The Resistive Nature of Decomposing Interfaces of Solid Electrolytes with Alkali Metal Electrodes

Wang¹,

Panchal²,

Gautam³

et al. 2022

Preprint

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A crucial ingredient in lithium (Li) and sodium (Na)-ion batteries (LIBs and NIBs) is the electrolytes. The use of Li-metal (Na-metal) as anode in liquid electrolyte LIBs (NIBs) is constrained by several issues including thermal runway and flammability, electrolyte leakage, and limited chemical stability. Considerable effort has been devoted toward the development of solid electrolytes (SEs) and all-solid-state batteries, which are presumed to mitigate some of the issues of Li-metal(Nametal) in contact with flammable liquid electrolytes. However, most SEs, such as Li 3 PS 4 , Li 6 PS 5 Cl and Na 3 PS 4 readily decompose against the highly reducing Li-metal and Na-metal anodes. Using first-principles calculations we elucidate the stability of more than 20 solid||solid interfaces formed between the decomposition products of Li 3 PS 4 , Li 6 PS 5 Cl (and Na 3 PS 4 ) against the Li-metal (Nametal) electrode. We suggest that the work of adhesion needed to form a hetereogenous interfaces is an important descriptor to quantify the stability of interfaces. Subsequently, we clarify the atomistic origins of the resistance to Li-ion transport at interfaces of the Li-metal anode and selected decomposition products (Li 3 P, Li 2 S and LiCl) of SEs, via a high-fidelity machine learned potential (MLP). Utilising an MLP enables nano-second-long molecular dynamics simulations on 'large' interface models (here with 8320 atoms), but with similar accuracy to first-principles approaches. Our simulations demonstrate that the interfaces formed between Li-metal and argyrodite (e.g., Li 6 PS 5 Cl) decomposition products are resistive to Li-ion transport. The implications of this study are important since binary compounds are commonly found in the vicinity of Li(Na)-metal upon chemical and/or electrochemical decomposition of ternary and quaternary SEs.

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Bridging the gap between simulated and experimental ionic conductivities in lithium superionic conductors

Cited by 66 publications

References 77 publications

Artificial Intelligence-Aided Mapping of the Structure–Composition–Conductivity Relationships of Glass–Ceramic Lithium Thiophosphate Electrolytes

Artificial Intelligence-Aided Mapping of the Structure–Composition–Conductivity Relationships of Glass–Ceramic Lithium Thiophosphate Electrolytes

The resistive nature of decomposing interfaces of solid electrolytes with alkali metal electrodes

The Resistive Nature of Decomposing Interfaces of Solid Electrolytes with Alkali Metal Electrodes

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