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Forced Disorder in the Solid Solution Li₃P-Li₂S: A New Class of Fully Reduced Solid Electrolytes for Lithium Metal Anodes.

ABSTRACT: All-solid-state batteries based on non-combustible solid electrolytes are promising candidates for safe energy storage systems. In addition, they offer the opportunity to utilize metallic lithium as an anode. However, it has proven to be a challenge to design an electrolyte that combines high ionic conductivity and processability with thermodynamic stability toward lithium. Herein, we report a new highly conducting solid solution that offers a route to overcome these challenges. The Li-P-S ternary was first explored via a combination of high-throughput crystal structure predictions and solid-state synthesis (via ball milling) of the most promising compositions, specifically, phases within the Li₃P-Li₂S tie line. We systematically characterized the structural properties and Li-ion mobility of the resulting materials by X-ray and neutron diffraction, solid-state nuclear magnetic resonance spectroscopy (relaxometry), and electrochemical impedance spectroscopy. A Li₃P-Li₂S metastable solid solution was identified, with the phases adopting the fluorite (Li₂S) structure with P substituting for S and the extra Li⁺ ions occupying the octahedral voids and contributing to the ionic transport. The analysis of the experimental data is supported by extensive quantum-chemical calculations of both structural stability, diffusivity, and activation barriers for Li⁺ transport. The new solid electrolytes show Li-ion conductivities in the range of established materials, while their composition guarantees thermodynamic stability toward lithium metal anodes.

SUBMITTER: Szczuka C

PROVIDER: S-EPMC9479069 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Forced Disorder in the Solid Solution Li<sub>3</sub>P-Li<sub>2</sub>S: A New Class of Fully Reduced Solid Electrolytes for Lithium Metal Anodes.

Szczuka Conrad C Karasulu Bora B Groh Matthias F MF Sayed Farheen N FN Sherman Timothy J TJ Bocarsly Joshua D JD Vema Sundeep S Menkin Svetlana S Emge Steffen P SP Morris Andrew J AJ Grey Clare P CP

Journal of the American Chemical Society 20220830 36

All-solid-state batteries based on non-combustible solid electrolytes are promising candidates for safe energy storage systems. In addition, they offer the opportunity to utilize metallic lithium as an anode. However, it has proven to be a challenge to design an electrolyte that combines high ionic conductivity and processability with thermodynamic stability toward lithium. Herein, we report a new highly conducting solid solution that offers a route to overcome these challenges. The Li-P-S terna ...[more]

PMID: 36040461

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Project description:Next generation batteries based on lithium (Li) metal anodes have been plagued by the dendritic electrodeposition of Li metal on the anode during cycling, resulting in short circuit and capacity loss. Suppression of dendritic growth through the use of solid electrolytes has emerged as one of the most promising strategies for enabling the use of Li metal anodes. We perform a computational screening of over 12 000 inorganic solids based on their ability to suppress dendrite initiation in contact with Li metal anode. Properties for mechanically isotropic and anisotropic interfaces that can be used in stability criteria for determining the propensity of dendrite initiation are usually obtained from computationally expensive first-principles methods. In order to obtain a large data set for screening, we use machine-learning models to predict the mechanical properties of several new solid electrolytes. The machine-learning models are trained on purely structural features of the material, which do not require any first-principles calculations. We train a graph convolutional neural network on the shear and bulk moduli because of the availability of a large training data set with low noise due to low uncertainty in their first-principles-calculated values. We use gradient boosting regressor and kernel ridge regression to train the elastic constants, where the choice of the model depends on the size of the training data and the noise that it can handle. The material stiffness is found to increase with an increase in mass density and ratio of Li and sublattice bond ionicity, and decrease with increase in volume per atom and sublattice electronegativity. Cross-validation/test performance suggests our models generalize well. We predict over 20 mechanically anisotropic interfaces between Li metal and four solid electrolytes which can be used to suppress dendrite growth. Our screened candidates are generally soft and highly anisotropic, and present opportunities for simultaneously obtaining dendrite suppression and high ionic conductivity in solid electrolytes.

Dataset Information

Forced Disorder in the Solid Solution Li₃P-Li₂S: A New Class of Fully Reduced Solid Electrolytes for Lithium Metal Anodes.

Publications

Forced Disorder in the Solid Solution Li<sub>3</sub>P-Li<sub>2</sub>S: A New Class of Fully Reduced Solid Electrolytes for Lithium Metal Anodes.

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Forced Disorder in the Solid Solution Li3P-Li2S: A New Class of Fully Reduced Solid Electrolytes for Lithium Metal Anodes.

Publications

Forced Disorder in the Solid Solution Li<sub>3</sub>P-Li<sub>2</sub>S: A New Class of Fully Reduced Solid Electrolytes for Lithium Metal Anodes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Forced Disorder in the Solid Solution Li₃P-Li₂S: A New Class of Fully Reduced Solid Electrolytes for Lithium Metal Anodes.