Studies of the impact of plasmonic metal nano-particles on co-catalysts/semiconductor photocatalysts in solar water splitting

标题：等离子体金属纳米粒子对辅助催化剂/半导体光催化剂在太阳能水分离中的影响研究在这个项目中，密歇根大学(Ann Arbor)的Suljo Linic教授正在开发光催化分解水的新材料。由太阳光驱动的水的分解是最重要的化学转化之一，目前还没有有效的材料来实现这一转化。在追求高效的水分解光催化剂方面没有取得成功，这清楚地表明需要新的方向。在他们的概念验证研究中，Linic教授和他的同事们展示了一种全新的复合光催化剂，将等离子金属纳米颗粒(其特征是与太阳光强相互作用)与半导体结合在一起，展示了巨大的前景。虽然它们揭示了影响这些复合光催化剂性能的多种因素，但需要开发能够量化这些因素之间的相互作用并指导优化材料设计的预测模型。如果没有这样全面的预测模型，就不可能讨论复合材料的性能上限，也不可能确定能够达到这些上限的复合光催化剂的几何结构。这项工作将开发这些预测模型，产生优化的复合光催化剂设计所需的关键知识库。最近的研究表明，一类新的复合材料，将半导体和硬币金属的等离子体纳米颗粒相结合，在利用太阳光分解水方面表现出比传统半导体光催化剂更好的性能。等离子体纳米结构的作用是选择性地将光捕获在半导体中发生水分解过程的区域，即水/半导体界面，从而选择性地提高该区域e-/h+的形成速度并改善材料的性能。概念验证工作主要集中在氮掺杂的二氧化钛和银纳米颗粒的复合材料上光化学分解水。虽然这些初步研究在复合材料的光化学领域带来了非常活跃的领域，但仍有许多关键问题没有得到解答。该奖项将使Linic能够专注于其中的一些问题，包括：(I)确定潜在的机制和关键概念可以转移到其他更先进的光催化剂系统。特别是，包括助催化剂和半导体在内的更高效的多功能光催化剂是人们感兴趣的。(2)确定支配等离子-金属/助催化剂/半导体光催化剂性能的关键物理性质。将光催化剂的光学和几何性质与其光催化分解水的性能联系起来的预测性的、物理上透明的模型将是可交付的。这些预测的结构/性能关系是设计能够达到最佳性能的复合光催化剂所必需的。(Iii)通过合成和测试具有最佳物理特性的等离子体-金属/助催化剂/半导体光催化剂来验证这些模型。林尼克教授为当地高中开发了一个外展项目，让当地高中生有机会参与这项研究，了解可持续能源转换。此外，还将作出重大努力，让普通公众了解利用万维网进行可持续能源生产的各个领域。这项工作的更广泛影响包括发现新一代光催化剂的潜在社会效益，以及为学生和教师开发培训机会。

Title: Studies of the impact of plasmonic metal nanoparticles on co-catalyst/semiconductor photocatalysts in solar water splittingIn this project, Professor Suljo Linic of The University of Michigan (Ann Arbor) is developing new materials for photocatalytic splitting of water. The splitting of water driven by solar light is one of the most important chemical transformations for which no efficient materials exist. The lack of success in the pursuit of efficient water splitting photocatalysts clearly indicates that new directions are needed. In their proof-of-concept studies Prof. Linic and coworkers showed that an entirely new class of composite photocatalysts, combining plasmonic metal nanoparticles (characterized by their strong interaction with solar light) with semiconductors, exhibits a great deal of promise. While they shed light on multiple factors that play a role in the performance of these composite photocatalysts, predictive models that can quantify the interplay between these factors and guide the design of optimized materials need to be developed. Without such comprehensive predictive models, it is impossible to discuss the upper performance limits for the composite materials, or to identify the geometries of composite photocatalysts that could achieve these limits. The proposed work will develop these predictive models yielding the critical knowledge base required for the design of optimized composite photocatalysts.It was demonstrated recently that a new class of composite materials, combining semiconductors with plasmonic nanoparticles of coinage metals, exhibit improved performance in photo-catalytic splitting of water using Sun light compared to conventional semiconductor photocatalysts. The plasmonic nanostructures act to selectively trap light in the regions of the semiconductor where the water splitting process is taking place, i.e. the water/semiconductor interface, thereby selectively enhancing the rates of e-/h+ formation in this region and improving the performance of the material. The proof-of-concept work focused on photochemical splitting of water on the composites of nitrogen-doped TiO2 and nanoparticles of Ag. While these initial studies led to a very vibrant field of photochemistry on the composite materials, there are many unanswered critical issues. This award will allow Linic to focus on a number of these issues, including: (i) Establishing that the underlying mechanisms and critical concepts are transferable to other more advanced photocatalyst systems. In particular, more efficient multifunctional photocatalysts that include a co-catalyst and a semiconductor are of interest. (ii) Identifying critical physical properties that govern the performance of plasmonic-metal/co-catalyst/semiconductor photocatalysts. Predictive, physically transparent models that relate optical and geometric properties of photocatalysts to their performance in photocatalytic splitting of water will be the deliverables. These predictive structure/performance relationships are required for the design of composite photocatalysts that can achieve optimal performance. (iii) Validate these models by synthesizing and testing the plasmonic-metal/co-catalyst/semiconductor photocatalysts with optimal physical characteristics. An outreach program developed by Professor Linic to area high schools is allowing local high school students the opportunity to participate in this research and to learn about sustainable energy transformations. Furthermore, significant efforts will be made to expose general public to various fields of sustainable energy generation using World Wide Web. The broader impacts of this work include potential societal benefits from the discovery of new generation of photocatalysts as well as the development of training opportunities for students and teachers.