Jian Gao

Bio: Jian Gao is an academic researcher from Shanghai University. The author has contributed to research in topics: Ionic conductivity & Electrolyte. The author has an hindex of 10, co-authored 10 publications receiving 624 citations. Previous affiliations of Jian Gao include Chinese Academy of Sciences.

Brief overview of electrochemical potential in lithium ion batteries

Abstract: The physical fundamentals and influences upon electrode materials' open-circuit voltage (OCV) and the spatial distribution of electrochemical potential in the full cell are briefly reviewed. We hope to illustrate that a better understanding of these scientific problems can help to develop and design high voltage cathodes and interfaces with low Ohmic drop. OCV is one of the main indices to evaluate the performance of lithium ion batteries (LIBs), and the enhancement of OCV shows promise as a way to increase the energy density. Besides, the severe potential drop at the interfaces indicates high resistance there, which is one of the key factors limiting power density.

Lithium-ion transport in inorganic solid state electrolyte*

Abstract: An overview of ion transport in lithium-ion inorganic solid state electrolytes is presented, aimed at exploring and designing better electrolyte materials. Ionic conductivity is one of the most important indices of the performance of inorganic solid state electrolytes. The general definition of solid state electrolytes is presented in terms of their role in a working cell(to convey ions while isolate electrons), and the history of solid electrolyte development is briefly summarized. Ways of using the available theoretical models and experimental methods to characterize lithium-ion transport in solid state electrolytes are systematically introduced. Then the various factors that affect ionic conductivity are itemized, including mainly structural disorder, composite materials and interface effects between a solid electrolyte and an electrode. Finally, strategies for future material systems, for synthesis and characterization methods, and for theory and calculation are proposed, aiming to help accelerate the design and development of new solid electrolytes.

Screening possible solid electrolytes by calculating the conduction pathways using Bond Valence method

Abstract: Inorganic solid electrolytes have distinguished advantages in terms of safety and stability, and are promising to substitute for conventional organic liquid electrolytes. However, low ionic conductivity of typical candidates is the key problem. As connective diffusion path is the prerequisite for high performance, we screen for possible solid electrolytes from the 2004 International Centre for Diffraction Data (ICDD) database by calculating conduction pathways using Bond Valence (BV) method. There are 109846 inorganic crystals in the 2004 ICDD database, and 5295 of them contain lithium. Except for those with toxic, radioactive, rare, or variable valence elements, 1380 materials are candidates for solid electrolytes. The rationality of the BV method is approved by comparing the existing solid electrolytes’ conduction pathways we had calculated with those from experiments or first principle calculations. The implication for doping and substitution, two important ways to improve the conductivity, is also discussed. Among them Li2CO3 is selected for a detailed comparison, and the pathway is reproduced well with that based on the density functional studies. To reveal the correlation between connectivity of pathways and conductivity, α/γ-LiAlO2 and Li2CO3 are investigated by the impedance spectrum as an example, and many experimental and theoretical studies are in process to indicate the relationship between property and structure. The BV method can calculate one material within a few minutes, providing an efficient way to lock onto targets from abundant data, and to investigate the structure-property relationship systematically.

Toward Safe Lithium Metal Anode in Rechargeable Batteries: A Review.

Abstract: The lithium metal battery is strongly considered to be one of the most promising candidates for high-energy-density energy storage devices in our modern and technology-based society. However, uncontrollable lithium dendrite growth induces poor cycling efficiency and severe safety concerns, dragging lithium metal batteries out of practical applications. This review presents a comprehensive overview of the lithium metal anode and its dendritic lithium growth. First, the working principles and technical challenges of a lithium metal anode are underscored. Specific attention is paid to the mechanistic understandings and quantitative models for solid electrolyte interphase (SEI) formation, lithium dendrite nucleation, and growth. On the basis of previous theoretical understanding and analysis, recently proposed strategies to suppress dendrite growth of lithium metal anode and some other metal anodes are reviewed. A section dedicated to the potential of full-cell lithium metal batteries for practical applicatio...

Lithium battery chemistries enabled by solid-state electrolytes

Abstract: Solid-state electrolytes are attracting increasing interest for electrochemical energy storage technologies. In this Review, we provide a background overview and discuss the state of the art, ion-transport mechanisms and fundamental properties of solid-state electrolyte materials of interest for energy storage applications. We focus on recent advances in various classes of battery chemistries and systems that are enabled by solid electrolytes, including all-solid-state lithium-ion batteries and emerging solid-electrolyte lithium batteries that feature cathodes with liquid or gaseous active materials (for example, lithium–air, lithium–sulfur and lithium–bromine systems). A low-cost, safe, aqueous electrochemical energy storage concept with a ‘mediator-ion’ solid electrolyte is also discussed. Advanced battery systems based on solid electrolytes would revitalize the rechargeable battery field because of their safety, excellent stability, long cycle lives and low cost. However, great effort will be needed to implement solid-electrolyte batteries as viable energy storage systems. In this context, we discuss the main issues that must be addressed, such as achieving acceptable ionic conductivity, electrochemical stability and mechanical properties of the solid electrolytes, as well as a compatible electrolyte/electrode interface. This Review details recent advances in battery chemistries and systems enabled by solid electrolytes, including all-solid-state lithium-ion, lithium–air, lithium–sulfur and lithium–bromine batteries, as well as an aqueous battery concept with a mediator-ion solid electrolyte.

Recent advances and applications of machine learning in solid-state materials science

Abstract: One of the most exciting tools that have entered the material science toolbox in recent years is machine learning. This collection of statistical methods has already proved to be capable of considerably speeding up both fundamental and applied research. At present, we are witnessing an explosion of works that develop and apply machine learning to solid-state systems. We provide a comprehensive overview and analysis of the most recent research in this topic. As a starting point, we introduce machine learning principles, algorithms, descriptors, and databases in materials science. We continue with the description of different machine learning approaches for the discovery of stable materials and the prediction of their crystal structure. Then we discuss research in numerous quantitative structure–property relationships and various approaches for the replacement of first-principle methods by machine learning. We review how active learning and surrogate-based optimization can be applied to improve the rational design process and related examples of applications. Two major questions are always the interpretability of and the physical understanding gained from machine learning models. We consider therefore the different facets of interpretability and their importance in materials science. Finally, we propose solutions and future research paths for various challenges in computational materials science.

High electronic conductivity as the origin of lithium dendrite formation within solid electrolytes

Abstract: Solid electrolytes (SEs) are widely considered as an ‘enabler’ of lithium anodes for high-energy batteries. However, recent reports demonstrate that the Li dendrite formation in Li7La3Zr2O12 (LLZO) and Li2S–P2S5 is actually much easier than that in liquid electrolytes of lithium batteries, by mechanisms that remain elusive. Here we illustrate the origin of the dendrite formation by monitoring the dynamic evolution of Li concentration profiles in three popular but representative SEs (LiPON, LLZO and amorphous Li3PS4) during lithium plating using time-resolved operando neutron depth profiling. Although no apparent changes in the lithium concentration in LiPON can be observed, we visualize the direct deposition of Li inside the bulk LLZO and Li3PS4. Our findings suggest the high electronic conductivity of LLZO and Li3PS4 is mostly responsible for dendrite formation in these SEs. Lowering the electronic conductivity, rather than further increasing the ionic conductivity of SEs, is therefore critical for the success of all-solid-state Li batteries. Despite its importance in lithium batteries, the mechanism of Li dendrite growth is not well understood. Here the authors study three representative solid electrolytes with neutron depth profiling and identify high electronic conductivity as the root cause for the dendrite issue.

Review on modeling of the anode solid electrolyte interphase (SEI) for lithium-ion batteries

Abstract: A passivation layer called the solid electrolyte interphase (SEI) is formed on electrode surfaces from decomposition products of electrolytes. The SEI allows Li+ transport and blocks electrons in order to prevent further electrolyte decomposition and ensure continued electrochemical reactions. The formation and growth mechanism of the nanometer thick SEI films are yet to be completely understood owing to their complex structure and lack of reliable in situ experimental techniques. Significant advances in computational methods have made it possible to predictively model the fundamentals of SEI. This review aims to give an overview of state-of-the-art modeling progress in the investigation of SEI films on the anodes, ranging from electronic structure calculations to mesoscale modeling, covering the thermodynamics and kinetics of electrolyte reduction reactions, SEI formation, modification through electrolyte design, correlation of SEI properties with battery performance, and the artificial SEI design. Multi-scale simulations have been summarized and compared with each other as well as with experiments. Computational details of the fundamental properties of SEI, such as electron tunneling, Li-ion transport, chemical/mechanical stability of the bulk SEI and electrode/(SEI/) electrolyte interfaces have been discussed. This review shows the potential of computational approaches in the deconvolution of SEI properties and design of artificial SEI. We believe that computational modeling can be integrated with experiments to complement each other and lead to a better understanding of the complex SEI for the development of a highly efficient battery in the future.