DMREF/Collaborative Research: Design and Testing of Nanoalloy Catalysts in 3D Atomic Resolution

DMREF/合作研究：3D 原子分辨率纳米合金催化剂的设计和测试

• 批准号: 1437355
• 负责人: Hendrik Heinz
• 金额: $ 40万
• 依托单位: University of Akron
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-10-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1437355&HistoricalAwards=false
• 关键词: DMREF; Collaborative; Research; Design; Testing

DMREF: Collaborative Research: Design and Testing of Nanoalloy Catalysts in 3D Atomic ResolutionNon-Technical Description: The project aims at the discovery of ultra-small, nanometer-sized alloy catalysts to improve the efficiency of fuel cells, mobile power generation, and automotive catalytic converters. State-of-the-art laboratory and computer simulation techniques will be engaged to explore the uncharted design space of bimetallic nanostructures for such applications and implement reductions in cost through partial replacement of precious metals such as platinum by cheaper alternatives. The team of three PIs will synthesize new nanocatalysts using biomimetic approaches, image the positions of all atoms in 3D resolution using the world's most powerful electron microscope, and carry out performance tests in fuel cells in a close feedback loop with predictions by multi-scale modeling and simulation. Fundamental understanding of synthesis controls, atomic-scale order, and associated reactivity of the nanoalloys will lead to rational design rules to optimize catalyst performance and enable targeted improvements of promising materials. The development and validation of predictive multi-scale simulation tools will also benefit the broader computational user community. New fundamental insight into alloy synthesis and reactivity controls has further potential benefits to improve catalysts for commodity chemicals, magnetic information storage, batteries, sensors, and nanoelectronic devices. Undergraduate students, high school students, and teachers will be engaged in summer research activities at UCLA and in annual Engineering Career Days at the University of Akron to encourage careers in science and engineering.Technical Description: The project focuses on the computationally driven, rational optimization of nanoalloy atomic composition and shape for catalytic performance in the Oxygen Reduction Reaction (ORR) in fuel cells. Specific aims include the deterministic synthesis of Pt-M Nanocrystals (M = Fe, Co, Ni, Cu, Cr, Mn), the three-dimensional characterization of nanoalloy catalysts in atomic resolution and model refinements, as well as the prediction, tests, and optimization of the reactivity in the ORR. Methods comprise biomimetic synthesis protocols coupled with molecular dynamics and kinetic Monte Carlo simulations, ORR performance testing by voltammetry and density functional theory calculations, and in-situ monitoring of all reactions. The coordinates of the atoms in the synthesized nanostructures will be monitored by electron tomography to identify atomic ordering, to validate and improve interatomic potentials, and to predict reaction rates in ORR. Detailed understanding of alloy growth mechanism, shape control, and catalytic performance through new polarizable and reactive force fields for alloys and their aqueous interfaces from first principles will close a wide gap between experimental capabilities and missing theoretical understanding. Aided by thorough experimental characterization, predictions with unprecedented accuracy at length scales of 1 to 100 nm appear feasible, far beyond the limits of quantum-mechanical methods and building on previous successful models for interfaces of pure metals (CHARMM-METAL).

DMREF：协作研究：3D Atomic ResolutionNon-Technical描述中的纳米合物催化剂的设计和测试：该项目旨在发现超小，纳米大小的合金催化剂以提高燃料电池，移动电源，移动电源和汽车催化转化器的效率。最先进的实验室和计算机仿真技术将聘请以探索用于此类应用的双金属纳米结构的未知设计空间，并通过部分替换贵金属（例如廉价替代品）来实施降低成本的成本。三个PI的团队将使用仿生方法合成新的纳米催化剂，并使用世界上最强大的电子显微镜在3D分辨率中对所有原子的位置进行图像，并在燃料电池中在燃料电池中进行性能测试，并通过多规模建模和仿真进行预测，并通过预测。对合成控制，原子尺度顺序以及纳米合金相关的反应性的基本理解将导致合理的设计规则，以优化催化剂性能并实现有前途的材料的有针对性改进。预测性多尺度仿真工具的开发和验证也将使更广泛的计算用户社区受益。对合金合成和反应性控制的新基本洞察力具有进一步的潜在优势，可以改善商品化学品，磁性信息存储，电池，传感器和纳米电子设备的催化剂。本科生，高中生和老师将在UCLA参加夏季研究活动，并在阿克伦大学的年度工程职业生涯中，以鼓励科学和工程学的职业。技术描述：该项目着重于计算驱动的，合理的，合理的优化纳米合金原子原子组成和形状的催化性能，以催化性能在氧化反应中的催化性能（ORG）中的反应（ORR）。具体目的包括PT-M纳米晶体的确定性合成（M = Fe，Co，Ni，Cu，Cr，Mn），原子分辨率和模型改进中纳米合物催化剂的三维表征，以及ORR中反应性的预测和优化。方法包含仿生合成方案，结合了分子动力学和动力学蒙特卡洛模拟，通过伏安法和密度功能理论计算进行ORR性能测试，以及对所有反应的原位监测。合成纳米结构中原子的坐标将通过电子断层扫描监测，以鉴定原子订购，验证和改善原子间潜能以及预测ORR中的反应速率。详细了解合金的合金生长机制，形状控制和催化性能，通过合金的新两极分化和反应性力场及其第一原理中的水性接口将弥补实验能力和缺失理论理解之间的巨大差距。在彻底的实验表征的帮助下，在1至100 nm的长度尺度上具有前所未有的准确性的预测显得可行，远远超出了量子力学方法的限制，并且在先前成功的纯属金属接口（charmm-metal）接口的模型上构建了限制。