Rational Synthesis of Alloy Nanocrystals with Controlled Compositions and Facets for Electrocatalysis

由纳米级金属颗粒沉积在高表面积载体上组成的催化剂长期以来被用于提高化学反应的速率、产物选择性和能量效率。然而，在这种多相催化中，一个长期存在的挑战是设计和合成具有最佳颗粒组成和结构的催化剂。该项目通过开发一种精确而可靠的方法来制造具有良好控制表面的合金基电催化剂，解决了这一挑战。新的合成方法将被证明应用于氢（H2）和氧（O2）直接电催化转化为过氧化氢（H2O2），从而为能源密集型和复杂的现有技术提供了一种替代方案。项目成果将进一步加以调整，以加强课堂教学，包括发展与科学和工程关键概念有关的示范（例如动画和实验）。该项目的多学科和合作性质将为参与的学生提供丰富的教育和培训经验，同时扩大代表性不足的群体参与研究的机会。虽然由合金制成的纳米晶体已经被广泛地用于各种各样的电催化过程，但文献中报道的大多数研究都是基于一种试错方法，这种方法涉及到在元素组成和原子比方面对许多合金进行劳动密集型筛选。从组成、元素分布和原子排列等方面定量控制合金基纳米晶体的表面也是一个巨大的挑战。过氧化氢是一种对各种工业应用至关重要的化合物，随着电催化生产的重点，第一性原理计算和数据科学将用于确定候选合金的成分和表面结构，然后通过开发合成方法将其忠实地转化为纳米晶体催化剂。与传统方法不同，不同前驱体的溶液将被逐滴共滴定到反应溶液中，以便在整个合成过程中每种前驱体的瞬时浓度保持在预定的稳定状态。因此，原子将以稳定的、预先指定的速率从不同的前驱体中产生，以生成具有均匀组成的合金纳米晶体，原子比由其前驱体在稳定状态下的还原速率决定。当共形沉积在不同形状的纳米晶体上时（如厚度为几个原子层的覆盖层），将获得具有明确表面和增强抗元素偏析能力的合金基电催化剂。将实验测量和理论预测的催化数据进行比较，以改进计算方法，同时建立一个反馈回路，用于催化剂的迭代优化，而不涉及试错。这项变革性研究的直接成果将是为合理开发具有活性、选择性和耐用性的电催化剂的知识基础的创建，以实现过氧化氢的电催化生产。待开发的方法和技术也可以扩展，以加速发现和开发许多其他类型的纳米材料，这些纳米材料在各种应用中具有增强的性能，包括与化学生产、石油精炼、国家安全和公共卫生有关的应用。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Catalysts consisting of nanoscale metal particles deposited on high-surface-area supports have long been used to promote the rates, product selectivity, and energy efficiency of chemical reactions. However, a long-standing challenge in such heterogeneous catalysis has been the design and synthesis of catalysts that are optimally tuned with respect to particle composition and structure. The project addresses that challenge by developing a precise and robust method for the fabrication of alloy-based electrocatalysts with well-controlled surfaces. The novel synthesis approach will be demonstrated as applied to the direct electrocatalytic conversion of hydrogen (H2) and oxygen (O2) to hydrogen peroxide (H2O2) – thus offering an alternative to energy-intensive and complex current technology. Project results will be further adapted to enhance classroom teaching, including the development of demonstrations (e.g., animations and experiments) related to key concepts in science and engineering. The multi-disciplinary and collaborative nature of the project will offer a vehicle to enrich the education and training experiences of participating students while broadening participation of underrepresented groups in research. Although nanocrystals made of alloys have been extensively explored for a wide variety of electrocatalytic processes, most of the studies reported in the literature are based on a trial-and-error approach that involves labor-intensive screening of numerous alloys in terms of elemental composition and atomic ratio. It is also a grand challenge to quantitatively control the surface of an alloy-based nanocrystal in terms of composition, elemental distribution, and atomic arrangement. With a focus on the electrocatalytic production of hydrogen peroxide, a compound pivotal to a variety of industrial applications, first-principles calculations and data science will be used to identify candidate alloys in terms of composition and surface structure, followed by their faithful translation into nanocrystal-based catalysts through the development of a synthetic method. Different from conventional approaches, solutions of different precursors will be co-titrated dropwise into the reaction solution so that the instantaneous concentration of each precursor is maintained in a predefined steady state throughout the synthesis. As a result, atoms will be produced from the different precursors at stable, pre-specified rates for the generation of alloy nanocrystals with a uniform composition, with the atomic ratio being determined by the reduction rates of their precursors in the steady state. When conformally deposited on nanocrystals with different shapes - as overlayers of a few atomic layers in thickness - alloy-based electrocatalysts with well-defined surfaces and enhanced resistance against elemental segregation will be obtained. The catalytic data from experimental measurements and theoretical predictions will be compared to refine the computational methods while establishing a feedback loop for iterative optimization of the catalysts without involving trial and error. The immediate outcome of this transformative research will be the creation of a knowledge base for the rational development of electrocatalysts featuring an optimal combination of activity, selectivity, and durability toward the electrocatalytic production of hydrogen peroxide. The methods and techniques to be developed can also be extended to accelerate the discovery and development of many other types of nanomaterials with enhanced performance in various applications, including those related to chemical production, petroleum refining, national security, and public health.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.