A new universal force-field for the Li2S-P2S5 system

Insights into Lithium Sulfide Glass Electrolyte Structures and Ionic Conductivity via Machine Learning Force Field Simulations

Sulfide-based solid electrolytes (SEs) are important for advancing all-solid-state batteries (ASSBs), primarily due to their high ionic conductivities and robust mechanical stability. Glassy SEs (GSEs) comprising mixed Si and P glass formers are particularly promising for their synthesis process and their ability to prevent lithium dendrite growth. However, to date, the complexity of their glassy structures hinders a complete understanding of the relationships between their structures and properties. This study introduces a new machine learning force field (ML-FF) tailored for lithium sulfide-based GSEs, enabling the exploration of their structural characteristics, mechanical properties, and lithium ionic conductivities. Using molecular dynamic (MD) simulations with this ML-FF, we explore the glass structures in varying compositions, including binary Li2S-SiS2 and Li2S-P2S5 as well as ternary Li2S-SiS2-P2S5. Our simulations yielded consistent results in terms of density, elastic modulus, radial distribution functions, and neutron structure factors compared to DFT and experimental work. Our findings reveal distinct local environments for Si and P within these glasses, with most Si atoms in edge-sharing configurations in Li2S-SiS2 and a mix of corner- and edge-sharing tetrahedra in the ternary Li2S-SiS2-P2S5 composition. For lithium ionic conductivity at 300 K, the 50Li2S-50SiS2 glass displayed the lowest conductivity at 2.1 mS/cm, while the 75Li2S-25P2S5 composition exhibited the highest conductivity at 3.6 mS/cm. The ternary glass showed a conductivity of 2.6 mS/cm, sitting between the two. Moreover, an in-depth analysis of lithium ion diffusion over the MD trajectory in the ternary glass demonstrated a significant correlation between diffusion pathways and the rotational dynamics of nearby SiS4 or PS4 tetrahedra. The ML-FF developed in this study provides an important tool for exploring a broad spectrum of solid-state and mixed former sulfide-based electrolytes.

Mechanism of Charge Transport in Lithium Thiophosphate

Lithium ortho-thiophosphate (Li3PS4) has emerged as a promising candidate for solid-state electrolyte batteries, thanks to its highly conductive phases, cheap components, and large electrochemical stability range. Nonetheless, the microscopic mechanisms of Li-ion transport in Li3PS4 are far from being fully understood, the role of PS4 dynamics in charge transport still being controversial. In this work, we build machine learning potentials targeting state-of-the-art DFT references (PBEsol, r2SCAN, and PBE0) to tackle this problem in all known phases of Li3PS4 (α, β, and γ), for large system sizes and time scales. We discuss the physical origin of the observed superionic behavior of Li3PS4: the activation of PS4 flipping drives a structural transition to a highly conductive phase, characterized by an increase in Li-site availability and by a drastic reduction in the activation energy of Li-ion diffusion. We also rule out any paddle-wheel effects of PS4 tetrahedra in the superionic phases-previously claimed to enhance Li-ion diffusion-due to the orders-of-magnitude difference between the rate of PS4 flips and Li-ion hops at all temperatures below melting. We finally elucidate the role of interionic dynamical correlations in charge transport, by highlighting the failure of the Nernst-Einstein approximation to estimate the electrical conductivity. Our results show a strong dependence on the target DFT reference, with PBE0 yielding the best quantitative agreement with experimental measurements not only for the electronic band gap but also for the electrical conductivity of β- and α-Li3PS4.

Molecular Dynamics Studies of the Ho(III) Aqua-tris(dibenzoylmethane) Complex: Role of Water Dynamics

The seven-coordinate Ho(III) aqua-tris(dibenzoylmethane)(DBM) complex, referred to as Ho-(DBM)₃·H₂O, was first reported in the late 1960s. It has a threefold symmetric structure, with Ho at the center of three dibenzoylmethane ligands and hydrogen-bonded water to ligands. It is considered that the hydrogen bonds between the water molecule and the ligands surrounding Ho play an important role in the formation of its symmetrical structure. In this work, we developed new force-field parameters for classical molecular dynamics (CMD) simulations to theoretically elucidate the structure and dynamics of Ho-(DBM)₃·H₂O. To develop the force field, structural optimization and molecular dynamics were performed on the basis of ab initio calculations using the plane-wave pseudopotential method. The force-field parameters for CMD were then optimized to reproduce the data obtained from ab initio calculations. Validation of the developed force field showed good agreement with the experimental crystalline structure and ab initio data. The vibrational properties of water in Ho-(DBM)₃·H₂O were investigated by comparison with bulk liquid water. The vibrational motion of water was found to have a characteristic mode originating from stationary rotational motion along the c-axis of Ho(III) aqua-tris(dibenzoylmethane). Contrary to expectations, the hydrogen-bond dynamics of water in Ho-(DBM)₃·H₂O were found to be almost equivalent to those of bulk liquid water except for librational motion. This development route for force-field parameters for CMD and the establishment of water dynamics can advance the understanding of water-coordinated metal complexes with high coordination numbers such as Ho-(DBM)₃·H₂O.

Disentangling Cation and Anion Dynamics in Li3PS4 Solid Electrolytes

A prerequisite for the realization of solid-state batteries is the development of highly conductive solid electrolytes. Li₃PS₄ is the archetypal member of the highly promising thiophosphate family of Li-ion conductors. Despite a multitude of investigations into this material, the underlying atomic-scale features governing the roles of and the relationships between cation and anion dynamics, in its various temperature-dependent polymorphs, are yet to be fully resolved. On this basis, we provide a comprehensive molecular dynamics study to probe the fundamental mechanisms underpinning fast Li-ion diffusion in this important solid electrolyte material. We first determine the Li-ion diffusion coefficients and corresponding activation energies in the temperature-dependent γ, β, and α polymorphs of Li₃PS₄ and relate them to the structural and chemical characteristics of each polymorph. The roles that both cation correlation and anion libration play in enhancing the Li-ion dynamics in Li₃PS₄ are then isolated and revealed. For γ- and β-Li₃PS₄, our simulations confirm that the interatomic Li-Li interaction is pivotal in determining (and restricting) their Li-ion diffusion. For α-Li₃PS₄, we quantify the significant role of Li-Li correlation and anion dynamics in dominating Li-ion transport in this polymorph for the first time. The fundamental understanding and analysis presented herein is expected to be highly applicable to other solid electrolytes where the interplay between cation and anion dynamics is crucial to enhancing ion transport.

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

Lithium thiophosphates (LPSs) with the composition (Li₂S) _x (P₂S₅)_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, (Li₂S) _x (P₂S₅)_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.