DMREF: Collaborative Research: A Blueprint for Photocatalytic Water Splitting: Mapping Multidimensional Compositional Space to Simultaneously Optimize Thermodynamics and Kinetics

非技术描述：阳光是一种巨大的可再生能源，但其间歇性意味着其利用需要一种储存这种能量的方法。太阳能存储的一种有吸引力的方法是利用太阳光的能量将水分解成氢和氧，即太阳能产生的燃料。太阳能产生的燃料可以燃烧以有效地释放能量，水作为唯一的副产品。因此，这种方法避免了伴随传统化石燃料燃烧的温室气体排放的有害后果。收集阳光并将水分解为氢和氧所需的复杂级联反应是一项艰巨的科学挑战。该项目旨在开发混合材料作为水分解的催化剂，使单个组件组装并协同发挥作用。该项目进一步致力于采用能量水平高度可调的组件，从而提供一个多功能平台，可以优化将阳光和水转化为燃料。 采用超级计算机计算和选择性实验的明智组合，加速了材料的合理设计，以在化学键内实现高效的太阳能存储。该项目团队指导来自弱势群体的年轻科学家，并让K-12学生和教师参与强调大数据和太阳能带来的机会的活动。技术描述：该项目探索基于三元氧化钒青铜与半导体量子点接口的光催化水分解可编程异质结构平台的设计。在前一种化合物中，金属阳离子插入各种开放的钒氧化物框架内，从而实现多种组成可能性和相当大的能级调节。此外，量子点的能级也可以作为组成以及尺寸和核的存在的函数来调节。光催化水分解不仅需要适当的能级排列，还需要精确控制电荷转移动力学。连接两个通用的和可调的组件产生了丰富的多维空间，用于识别水氧化的有效的光催化架构，其产生的空穴的电位仅最低限度地积极的水氧化电位，从而允许有效的转换太阳光的太阳能燃料。多维参数空间通过第一原理结构预测、电子结构计算、多样化材料合成、详细光谱学、高通量筛选和大数据分析的紧密集成和迭代组合来映射。该活动涉及开发一个用于统计分析和光谱数据挖掘的开源平台。暑期研究活动吸引了来自不同背景的本科生。

NON-TECHNICAL DESCRIPTION: Sunlight is a vast source of renewable energy but its intermittent nature means that its utilization requires a means of storing this energy. One attractive approach for solar energy storage is to harness the energy of sunlight to split water into hydrogen and oxygen i.e. solar generated fuels. The solar generated fuels can be combusted to release energy efficiently with water as the only by-product. As a result, this approach avoids the deleterious consequences of greenhouse emissions that accompany the combustion of conventional fossil fuels. The complex cascade of reactions required to harvest sunlight and split water into hydrogen and oxygen present a formidable scientific challenge. The project seeks to develop hybrid materials as the catalyst for water splitting, such that individual components are assembled and function synergistically. The project further works towards employing components that are highly tunable in terms of their energy levels, thereby providing a versatile platform that can be optimized for converting sunlight and water into fuel. Employing a judicious mix of calculations from supercomputers and selective experiments accelerates the rationally design of materials for efficient solar energy storage within chemical bonds. The project team mentors young scientists from underrepresented groups and engages K-12 students and teachers in activities that emphasize the opportunities made available by big data and solar energy.TECHNICAL DESCRIPTION: The project explores the design of programmable heterostructured platforms for photocatalytic water splitting based on interfacing ternary vanadium oxide bronzes with semiconductor quantum dots. In the former compounds, metal cations are intercalated within a variety of open vanadium oxide frameworks, enabling a multitude of compositional possibilities and considerable energy level tuning. Moreover, the energy levels of quantum dots can also be tuned as a function of composition as well as size and the presence of cores. Photocatalytic water splitting requires not just the appropriate alignment of energy levels but also precise control of charge transfer dynamics. Interfacing two versatile and tunable components yields a rich multidimensional space for identification of effective photocatalytic architectures for water oxidation that yield holes at potentials only minimally positive to the water oxidation potential, thereby allowing for efficient conversion of sunlight to solar fuels. The multidimensional parameter space is mapped through a closely integrated and iterative combination of first-principles structure prediction, electronic structure calculations, diversified materials synthesis, detailed spectroscopy, high-throughput screening, and big data analytics. The activity involves development of an open-source platform for statistical analysis and mining of spectroscopic data. A summer research activity engages undergraduates from diverse backgrounds.