CAS: Developing Data-Driven, Automated Methodology to Understand and Control Light-Driven Catalytic Processes

CAS：开发数据驱动的自动化方法来理解和控制光驱动的催化过程

• 批准号: 2350257
• 负责人: Stefan Bernhard
• 金额: $ 57.5万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2350257&HistoricalAwards=false
• 关键词: CAS; Developing; Data; Driven; Automated

With the support of the Chemical Catalysis program in the Division of Chemistry, Professor Stefan Bernhard of Carnegie Mellon University will study catalytic processes that are driven by light. Continued development of a sustainable society requires advances in molecular sciences that will pave the way to the solar-powered, efficient, safe and precise molecular engineering of new functional molecules, materials, and fuels. One of the major obstacles on this path stems from the inherent difficulty of extending current chemical theories to accurately describe the complex interplay of matter and energy in light-driven chemical transformations. One of the focal points of the proposed work will be the photogeneration of hydrogen from bio-available precursors like glycerol, sugars, or cellulose. The proposed work aims to discover new chemistries for transforming sunlight into a storable, carbon-neutral fuel. New automated and parallelized research protocols based on newly developed colorimetric hydrogen and oxygen detection methods will create significant sets of data that will be analyzed with modern artificial intelligence methodologies. Such a data-driven approach will allow a substantial acceleration of the research progress. The newly developed tools will use modern manufacturing techniques such as 3D-printing and laser-cutting to significantly lower the cost of these setups and experiments. This approach has the potential to greatly increase the openness for exploring light-driven chemical processes. Research in the Bernhard lab will prepare students at all levels to excel in the multidisciplinary environment common in today's research, while also training them intensely in the areas of transition metal complex synthesis, photocatalysis, and data science. The Bernhard lab involves and trains a diverse group of researchers to accomplish these research tasks. Professor Bernhard and his team will continue to be involved in outreach activities for non-scientists to educate the public on energy issues and instill excitement for science in general.Under this award, the Bernhard research group will build on their work on the development and use of hydrogen-sensitive film to develop complementary oxygen sensitive films. These films will allow the rapid screening of the progress of hydrogen and oxygen evolving photoreactions on 96-well plates. This technique will allow the team to elaborate on earlier results on the photogeneration of hydrogen from glycerol as a source of electrons and protons, and now transition to increasingly difficult, but more desirable substrates such as monosaccharides or polysaccharides for this purpose. The multi-well photoreactors will produce large datasets that will not only allow the optimization of reaction conditions more efficiently, but will also establish structure/activity databases that can be explored by physics-inspired machine learning approaches based on quantum mechanical calculations. These experiments will be the foundation for photochemical studies using water as the source of protons and electrons. Gaining a full understanding and an ability to control such water oxidation processes is a requisite step toward the development of a functional water splitting system for producing hydrogen and oxygen concomitantly. The proposed work will culminate in the application of the aforementioned high throughput technology to such water photolysis systems by combining and applying the knowledge gained from the work on each half-reaction.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.

在化学系化学催化项目的支持下，卡内基梅隆大学的斯特凡·伯恩哈德教授将研究光驱动的催化过程。可持续社会的持续发展需要分子科学的进步，这将为太阳能驱动、高效、安全和精确的新功能分子、材料和燃料的分子工程铺平道路。这条道路上的主要障碍之一来自于扩展现有化学理论以准确描述光驱动化学变化中物质和能量的复杂相互作用的内在困难。拟议工作的焦点之一将是从甘油、糖或纤维素等生物可用前体光生成氢。这项拟议的工作旨在发现新的化学物质，将阳光转化为可储存的、碳中性的燃料。基于新开发的比色测氢和测氧方法的新的自动化和并行研究协议将创建重要的数据集，这些数据将用现代人工智能方法进行分析。这种以数据为导向的方法将大大加快研究进展。新开发的工具将使用3D打印和激光切割等现代制造技术，以显著降低这些设置和实验的成本。这种方法有可能极大地增加探索光驱动化学过程的开放性。伯恩哈德实验室的研究将使所有级别的学生在当今研究中常见的多学科环境中脱颖而出，同时还将在过渡金属络合物合成、光催化和数据科学领域对他们进行密集培训。伯恩哈德实验室涉及并培训了一批不同的研究人员，以完成这些研究任务。伯恩哈德教授和他的团队将继续参与面向非科学家的外展活动，教育公众有关能源问题的知识，并向公众灌输对科学的兴趣。根据这一奖项，伯恩哈德研究小组将在开发和使用氢敏胶片的基础上，开发补充氧敏胶片。这些薄膜将允许在96孔板上快速放映放氢和放氧光反应的进展。这项技术将使该团队能够详细说明早期关于甘油作为电子和质子来源光生成氢的结果，现在过渡到越来越困难但更令人满意的底物，如单糖或多糖。多孔光反应堆将产生大数据集，不仅可以更有效地优化反应条件，还将建立结构/活性数据库，这些数据库可以通过基于量子力学计算的受物理启发的机器学习方法来探索。这些实验将是利用水作为质子和电子来源的光化学研究的基础。充分了解和控制这种水氧化过程是开发同时生产氢气和氧气的功能性水分离系统的必要步骤。这项拟议的工作将通过结合和应用从每一半反应中获得的知识，将上述高通量技术应用于此类水光解系统。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。