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.

在化学系化学催化计划的支持下，卡内基梅隆大学的Stefan Bernhard教授将研究由光驱动的催化过程。可持续社会的持续发展需要分子科学的进步，这将为新功能分子，材料和燃料的太阳能，高效，安全和精确的分子工程铺平道路。这条道路上的主要障碍之一源于扩展当前化学理论以准确描述光驱动化学转化中物质和能量的复杂相互作用的固有困难。拟议工作的重点之一将是从生物可利用的前体如甘油、糖或纤维素中光生氢。这项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燃料。基于新开发的比色氢和氧检测方法的新的自动化和并行化研究协议将创建重要的数据集，这些数据集将使用现代人工智能方法进行分析。这种数据驱动的方法将大大加快研究进展。新开发的工具将使用现代制造技术，如3D打印和激光切割，以显着降低这些设置和实验的成本。这种方法有可能大大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各级学生在当今研究中常见的多学科环境中脱颖而出，同时也在过渡金属络合物合成，催化剂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来完成这些研究任务。Bernhard教授和他的团队将继续参与非科学家的外展活动，教育公众对能源问题的认识，并为科学注入活力。在这个奖项下，Bernhard研究小组将在他们开发和使用氢敏感薄膜的基础上，开发互补的氧敏感薄膜。这些薄膜将允许在96孔板上快速筛选氢和氧释放光反应的进展。这项技术将使研究小组能够详细阐述早期关于甘油作为电子和质子来源的光生氢的结果，现在过渡到越来越困难，但更理想的底物，如单糖或多糖。多孔光反应器将产生大型数据集，不仅可以更有效地优化反应条件，还可以建立结构/活性数据库，这些数据库可以通过基于量子力学计算的物理学启发的机器学习方法进行探索。这些实验将为利用水作为质子和电子源的光化学研究奠定基础。获得充分的理解和控制这种水氧化过程的能力是朝着开发用于同时生产氢气和氧气的功能性水裂解系统的必要步骤。建议的工作将最终在上述高通量技术的应用，这样的水光解系统相结合，并应用从工作中获得的知识对每个half-reaction.This奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。