First Principles Simulations of Battery Materials

技术概述：该奖项支持计算和理论研究及教育，以解决电池设计中使用固体(而不是液体或聚合物)电解液的可能性。固体电解质被认为是液体和聚合物电解质的有效替代品，液体和聚合物电解质可能有更大的过热倾向。这项研究最初集中在与实验开发的立邦电解质相关的、表征良好的结晶体系上。从这些研究中获得的知识对于解决计算上更具挑战性的任务至关重要，即对玻璃形状进行建模，这些玻璃形状对电池和一些相关技术具有直接的商业利益。第二个研究轨道侧重于进一步开发现有的计算工具，以更好地模拟依赖多价过渡金属的阴极材料。为了满足对100 meV精度的内在需求，优化的有效势法将得到改进，以便所得到的波函数的空间范围不存在与密度泛函理论的标准近似所固有的自相互作用误差相关的不确定性。在更高级别的理论中使用这些波函数改进了对与电池功率直接相关的能量差异的预测。这一倡议是在一个框架内执行的，该框架有效地与目前的努力相联系，以便将精确交换和依赖轨道的方法纳入在算法上类似于密度函数代码的计算理论中。开发被实施到至少一个标准的共享通用电子结构代码中，该代码被广泛使用，并且是计算材料研究社区的网络基础设施的一部分。这项研究可能导致更安全的电池，具有更长的寿命和更高的效率，并根据功率-重量比进行优化。这项研究还将全面改善计算材料科学的状况，并通过教育倡议帮助培训下一代科学家。非技术概述：该奖项支持计算和理论研究以及教育，这些研究和教育将应用计算机和先进的材料理论和模型，以帮助详细了解电池技术的材料以及发现和设计新材料。在各种应用中，对便携式充电电池的需求迅速增长，相应地，开发具有成本效益和可靠的电池技术的动机也越来越大。虽然经济、实验和营销继续对成功的电池设计做出贡献，但这种技术方法可以通过从基础研究中收集的新见解进一步发展，这些基础研究产生于以前不可用的计算方法。这项计划采用了两个研究轨道，目的是通过详细的计算机模拟来加强对与现代可充电电池相关的材料的基本了解。第一个研究轨道使用各种计算技术来研究固体电解质材料的结构、离子导电性和稳定性。第二个研究方向是进一步开发现有的计算工具，以便更好地模拟依赖多价过渡金属的阴极材料

TECHNICAL SUMMARY:This award supports computational and theoretical research and education that addresses the potential use of solid, rather than liquid or polymer, electrolytes for battery design. Solid electrolytes are thought to be an efficacious alternative to the liquid and polymer electrolytes which may have a greater propensity toward over-heating. The research initially focuses upon well-characterized crystalline systems related to the LiPON electrolytes that have been experimentally developed. Knowledge garnered from these studies is essential for tackling the computationally more challenging task of modeling the glassy forms which have immediate commercial interest in batteries as well as in a number of related technologies. The second research track focuses on the further development of existing computational tools to better model the cathode materials which rely on multivalent transition metals. To address the intrinsic need for 100meV accuracy, the optimized effective potential method will be improved so that the spatial extent of the resulting wavefunctions are devoid of uncertainties associated with the self-interaction error that is intrinsic to standard approximations to the density-functional theory. Use of these wavefunctions in higher level theories improves prediction of energy differences which are directly related to battery power. This initiative is being carried out within a framework that efficiently connects to current efforts to include exact exchange and orbital-dependent approaches to correlation into computational theories that are algorithmically similar to that of density-functional codes. Developments are implemented into at least one standard shared general purpose electronic structure code that is widely used and is part of the cyberinfrastructure of the computational materials research community.This research may lead to safer batteries with longer life and higher efficiency that are optimized with respect to power-weight ratios. The research will also provide general improvements to the state of computational materials science and aid in training the next generation of scientists through the educational initiatives.NON-TECHNICAL SUMMARY:This award supports computational and theoretical research and education that will apply computers and advanced theories and models of materials to aid in the detailed understanding of materials for battery technologies and in the discovery and design of new materials.The need for portable rechargeable batteries is rapidly growing in a wide variety of applications and correspondingly, there is growing incentive to develop cost-effective and reliable battery technology. While economics, experiment and marketing continue to contribute to successful battery designs, such technological approaches can grow further from new insights gleaned from basic research resulting from previously unavailable computational methods. This initiative employs two research tracks with a goal toward enhancing basic understanding of materials related to modern rechargeable batteries through detailed computer simulation. The first research track uses a variety of computational techniques to study the structures, ionic conductivity, and stability of solid electrolyte materials. The second research track focuses on the further development of existing computational tools to better model the cathode materials which rely on multivalent transition metals