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

题目：等离子体金属纳米颗粒对太阳能水分解中助催化剂/半导体光催化剂影响的研究在这个项目中，密歇根大学（安娜堡）的Suljo Linic教授正在开发用于光催化水分解的新材料。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。在追求高效的水分解光催化剂方面缺乏成功清楚地表明需要新的方向。在他们的概念验证研究中，Linic教授和同事展示了一种全新的复合光催化剂，将等离子体金属纳米颗粒（其特点是与太阳光强相互作用）与半导体结合在一起，显示出很大的前景。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极限的复合光催化剂的几何形状。所提出的工作将开发这些预测模型，为优化复合光催化剂的设计提供关键的知识基础。最近有研究表明，一种新型的复合材料，将半导体与金属的等离子体纳米粒子结合在一起，与传统的半导体光催化剂相比，在利用太阳光进行水的光催化分解方面表现出更好的性能。等离子体纳米结构的作用是选择性地在半导体中发生水分裂过程的区域（即水/半导体界面）捕获光，从而选择性地提高该区域e-/h+的形成速率，并改善材料的性能。概念验证工作的重点是在氮掺杂TiO2和Ag纳米颗粒的复合材料上光化学分解水。虽然这些初步的研究导致了复合材料光化学领域的一个非常活跃的领域，但仍有许多悬而未决的关键问题。该奖项将使Linic能够专注于其中一些问题，包括：(i)确定基本机制和关键概念可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的更高效的多功能光催化剂是人们感兴趣的。（ii）确定控制等离子体金属/共催化剂/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特性与其在光催化分解水中的性能联系起来的预测的、物理透明的模型将是可交付的成果。这些预测结构/性能关系是设计复合光催化剂以达到最佳性能所必需的。（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。Linic教授为地区高中开发的外展计划使当地高中学生有机会参与这项研究并了解可持续能源转型。此外，将作出重大努力，使公众了解利用万维网可持续能源生产的各个领域。这项工作更广泛的影响包括发现新一代光催化剂带来的潜在社会效益，以及为学生和教师提供培训机会。

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.