Collaborative Research: Controlling Metal-Oxide Interface Chemistry for New C-H Activation Catalysts

在向可再生和可持续的净零碳燃料和化学品的清洁能源转型过程中，世界将继续依赖碳氢化合物资源。因此，通过有效的化学加工，生产易于运输的液体燃料和化学品，有很大的机会减少我国巨大的天然气储量的碳足迹。该项目解决了天然气化学加工中的一个关键挑战——根据需要打破碳氢键，以制造更高价值的燃料和化学品。催化技术是天然气高效节能升级的关键技术。为此，该项目研究了一种新型碳氢化合物转化催化剂，这种催化剂有可能使天然气在现场转化为液体燃料和化学品，从而极大地提高能源效率，并显著减少温室气体排放。该项目还将投资于针对经济上处于不利地位的本科生的研究经验，这些本科生中有不成比例的女性和代表性不足的少数民族。本科生将参与到同侪辅导网络中，这对促进本科生的成功尤其有效，特别是当团队中的学生具有不同的文化和社会经济背景时。该项目将结合研究人员的实验和计算专业知识，基于Au/氧化物界面的独特性质，开发新的异裂解C-H活化催化剂，通过改变氧化物的组成来最大化活性。将密度泛函理论和新的原位红外技术相结合，在精心挑选的一系列Au/MOx催化剂上量化H2活化参数。H-H和C-H键活化是密切相关的过程，因此广泛的方法是首先研究氧化物成分如何调节H2活化的热力学和动力学，然后扩展这些知识来设计C-H活化的有效界面。机器学习技术将利用这些结果来调查数千种氧化物成分的H2活化化学，这将为在金属-氧化物界面上控制复杂相互作用的潜在物理化学过程提供直接的见解。再加上有意设计的实验，以告知和完善计算模型，研究将超越影响碳氢活化的因素（如支持还原性，支持碱性，M-OH键柔韧性）的识别，以评估每个系统变量的相对影响。所得到的C-H键激活化学反应将用一组根据其吸附特性选择的碳氢化合物和催化苯甲醇氧化来测试。理想情况下，该项目将产生一种研究方案，该方案将结合高效的计算筛选和金属支撑催化剂组合的实验验证，为广泛的碳氢化合物和有机分子提供高效的C-H键激活。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。

The world will continue to rely on hydrocarbon resources during the Clean Energy Transition to renewable and sustainable net-zero carbon fuels and chemicals. Thus, there is a substantial opportunity to reduce the carbon footprint of our Nation’s tremendous natural gas reserves through efficient chemical processing to manufacture readily transportable liquid fuels and chemicals. The project addresses a key challenge in natural gas chemical processing – breaking the carbon-hydrogen bonds as needed to manufacture higher-value fuels and chemicals. Catalytic technology is critical to energy efficient natural gas upgrading. To that end, the project investigates a new class of hydrocarbon conversion catalysts that can potentially enable natural gas to be converted to liquid fuels and chemicals in the field, thereby generating enormous boosts in energy efficiency and a significant reduction in greenhouse gas emissions. The project also will invest in research experiences targeted to economically disadvantaged undergraduate students, who are disproportionately women and under-represented minorities. The undergraduates will be engaged in a peer-mentoring network, which can be particularly effective in promoting undergraduate success, especially when the students in the team have diverse cultural and socio-economic backgrounds. The project will combine the investigators’ experimental and computational expertise to develop new heterolytic C-H activation catalysts based on the unique properties of Au/oxide interfaces, which will be tuned to maximize activity by varying the composition of the oxide. A combination of density functional theory and new in-situ IR techniques will be employed to quantify H2 activation parameters over a carefully chosen series of Au/MOx catalysts. H-H and C-H bond activation are closely related processes, so the broad approach is to first study how oxide composition tunes the thermodynamics and kinetics of H2 activation, and then extend this knowledge to design effective interfaces for C-H activation. Machine learning techniques will use these results to survey H2 activation chemistry for thousands of oxide compositions, which will provide direct insight into underlying physio-chemical processes that govern complex interactions at the metal-oxide interface. Coupled with experiments intentionally designed to inform and refine the computational models, the research will go beyond identification of factors that impact C-H activation (such as support reducibility, support basicity, M-OH bond flexibility) to assess the relative impact of each system variable. The resulting C-H bond activation chemistry will be tested with a suite of hydrocarbons chosen for their adsorption properties and with catalytic benzyl alcohol oxidation. Ideally, the project will generate a research protocol that will combine efficient computational screening and experimental validation of metal-support catalyst combinations tailored for efficient C-H bond activation across a broad range of hydrocarbon and organic molecules.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.