Data-Driven Insight into the Reductive Stability of Ion-Solvent Complexes in Lithium Battery Electrolytes.

Lithium (Li) metal batteries (LMBs) are regarded as one of the most promising energy storage systems due to their ultrahigh theoretical energy density. However, the high reactivity of the Li anodes leads to the decomposition of the electrolytes, presenting a huge impediment to the practical application of LMBs. The routine trial-and-error methods are inefficient in designing highly stable solvent molecules for the Li metal anode. Herein, a data-driven approach is proposed to probe the origin of the reductive stability of solvents and accelerate the molecular design for advanced electrolytes. A large database of potential solvent molecules is first constructed using a graph theory-based algorithm and then comprehensively investigated by both first-principles calculations and machine learning (ML) methods. The reductive stability of 99% of the electrolytes decreases under the dominance of ion-solvent complexes, according to the analysis of the lowest unoccupied molecular orbital (LUMO). The LUMO energy level is related to the binding energy, bond length, and orbital ratio factors. An interpretable ML method based on Shapley additive explanations identifies the dipole moment and molecular radius as the most critical descriptors affecting the reductive stability of coordinated solvents. This work not only affords fruitful data-driven insight into the ion-solvent chemistry but also unveils the critical molecular descriptors in regulating the solvent's reductive stability, which accelerates the rational design of advanced electrolyte molecules for next-generation Li batteries.

Diameter-dependent ultrafast lithium-ion transport in carbon nanotubes.

Ion transport in solids is a key topic in solid-state ionics. It is critical but challenging to understand the relationship between material structures and ion transport. Nanochannels in crystals provide ion transport pathways, which are responsible for the fast ion transport in fast lithium (Li)-ion conductors. The controlled synthesis of carbon nanotubes (CNTs) provides a promising approach to artificially regulating nanochannels. Herein, the CNTs with a diameter of 5.5 Å are predicted to exhibit an ultralow Li-ion diffusion barrier of about 10 meV, much lower than those in routine solid electrolyte materials. Such a characteristic is attributed to the similar chemical environment of a Li ion during its diffusion based on atomic and electronic structure analyses. The concerted diffusion of Li ions ensures high ionic conductivities of CNTs. These results not only reveal the immense potential of CNTs for fast Li-ion transport but also provide a new understanding for rationally designing solid materials with high ionic conductivities.

Probing the Origin of Viscosity of Liquid Electrolytes for Lithium Batteries.

Viscosity is an extremely important property for ion transport and wettability of electrolytes. Easy access to viscosity values and a deep understanding of this property remain challenging yet critical to evaluating the electrolyte performance and tailoring electrolyte recipes with targeted properties. We proposed a screened overlapping method to efficiently compute the viscosity of lithium battery electrolytes by molecular dynamics simulations. The origin of electrolyte viscosity was further comprehensively probed. The viscosity of solvents exhibits a positive correlation with the binding energy between molecules, indicating viscosity is directly correlated to intermolecular interactions. Salts in electrolytes enlarge the viscosity significantly with increasing concentrations while diluents serve as the viscosity reducer, which is attributed to the varied binding strength from cation-anion and cation-solvent associations. This work develops an accurate and efficient method for computing the electrolyte viscosity and affords deep insight into viscosity at the molecular level, which exhibits the huge potential to accelerate advanced electrolyte design for next-generation rechargeable batteries.

Working Zinc-Air Batteries at 80 °C.

Aqueous zinc-air batteries possess inherent safety and are especially commendable facing high-temperature working conditions. However, their working feasibility at high temperatures has seldom been investigated. Herein, the working feasibility of high-temperature zinc-air batteries is systemically investigated. The effects of temperature on air cathode, zinc anode, and aqueous electrolyte are decoupled to identify the favorable and unfavorable factors. Specifically, parasitic hydrogen evolution reaction strengthens at high temperatures and leads to declined anode Faraday efficiency, which is identified as the main bottleneck. Moreover, zinc-air batteries demonstrate cycling feasibility at 80 °C. This work reveals the potential of zinc-air batteries to satisfy energy storage at high temperatures and guides further development of advanced batteries towards harsh working conditions.

An Electrocatalytic Model of the Sulfur Reduction Reaction in Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) battery is strongly considered as one of the most promising energy storage systems due to its high theoretical energy density and low cost. However, the sluggish reduction kinetics from Li2 S4 to Li2 S during discharge hinders the practical application of Li-S batteries. Although various electrocatalysts have been proposed to improve the reaction kinetics, the electrocatalytic mechanism is unclear due to the complexity of sulfur reduction reactions (SRR). It is crucial to understand the electrocatalytic mechanism thoroughly for designing advanced electrocatalysts. Herein an electrocatalytic model is constructed to reveal the chemical mechanism of the SRR in Li-S batteries based on systematical density functional theory calculations, taking heteroatoms-doped carbon materials as an example. The adsorption energy of LiSy ⋅ (y=1, 2, or 3) radicals is used as a key descriptor to predict the reaction pathway, rate-determining step, and overpotential. A diagram for designing advanced electrocatalysts is accordingly constructed. This work establishes a theoretical model, which is an intelligent integration for probing the complicated SRR mechanisms and designing advanced electrocatalysts for high-performance Li-S batteries.