Advanced Functional Materials for Energy Storage

由于许多可再生能源是间歇性的（例如，太阳、风），有必要开发可靠和高密度的储能方法。锂离子电池（LIB）具有较大的能量密度和容量，在改变能量存储和使用方式方面发挥着关键作用，但由于缺乏可用的电极材料，其应用受到阻碍。本研究通过使用网络基础设施来设计能够承受电池充电/放电循环期间发生的大体积膨胀/收缩的材料，从而追求新颖的LIB电极。（石墨、锂钴氧化物）;然而，基于转化反应的电极或基于合金化反应的电极对于改善LIB中的能量容量和密度具有更大的希望。该项目涉及使用遗传算法，分子动力学和密度泛函理论（DFT）计算优化锂插入和移除过程中电极的组成和形态。在DFT水平上，能斯特电位由电极相的相对稳定性计算。轻推的弹性带和非平衡绿色的功能方法将提供深入了解离子扩散途径和导电性，分别。基于反应力场相互作用模型的分子动力学模拟将阐明锂插入和移除的微观结构效应，特别关注变形和断裂行为。当与先进的遗传算法的微观结构和成分优化能力相结合时，这些工具允许快速检查广泛的成分和配置空间，并可以提供新的见解，设计高能量密度电极，当受到重复的充电/放电循环时不会显着降低。

Since many renewable energy sources are intermittent (e.g., sun, wind) it is necessary to develop reliable and high-density methods for storing energy. Lithium ion batteries (LIBs), with their large energy density and capacity, play a pivotal role in transforming the way energy is stored and used, but their application is hindered by the lack of available electrode materials. This research pursues novel LIB electrodes by using cyberinfrastructure to design materials able to withstand the large volume expansion/contraction that occurs during the battery charge/discharge cycle.Commercially available LIBs are based on the intercalation of lithium within layered electrode materials (graphite, lithium cobalt oxide); however, electrodes based on conversion reactions, or those based on alloying reactions, hold greater promise for improving the energy capacity and density in LIBs. This project involves optimizing the composition and morphology of electrodes during lithium insertion and removal using genetic algorithms, molecular dynamics, and density functional theory (DFT) calculations. At the DFT level, the Nernst potential is calculated from the relative stability of electrode phases. The nudged elastic band and non-equilibrium Green's function methods will provide insight into ionic diffusion pathways and into electrical conductivity, respectively. Molecular dynamics simulations based on reactive force fields interaction models will elucidate the microstructural effects of lithium insertion and removal, with particular focus on deformation and fracture behavior. When combined with the microstructural and compositional optimization capacity of advanced genetic algorithms, these tools allow for a rapid examination of broad compositional and configuration spaces and could provide novel insights into the design of high energy density electrodes that do not significantly degrade when subjected to repeated charge/discharge cycles.