D3SC: Developing Data-Driven, Automated Methodology to Understand and Control Light-Driven Catalytic Processes

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来自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相互作用的固有困难。拟议的工作利用了一种研究方法，旨在通过开发集成高通量实验、量子化学和数据科学的新工具来加速化学发现并加强对化学反应的控制。 伯恩哈德实验室涉及一组不同的研究人员来完成这些研究任务。Stefan Bernhard教授和他的研究团队将参与非科学家的外展活动，教育公众了解能源问题，并为科学注入活力。在化学系化学催化项目的支持下，卡内基梅隆大学的Stefan Bernhard教授将研究光驱动化学过程中试剂和催化剂的复杂相互作用。资助的研究将通过使用集成高通量实验，量子化学和数据科学的新工具来加深理解。 由化学理论和化学数据合并而成的人工智能将允许捕获复杂的多体电子相互作用的影响，而这些影响是当前算法所无法捕获的。为了收集推动这一努力所需的数据，伯恩哈德团队将开发大规模并行的自动化化学反应器，能够并行和真实的时间感测和记录各种反应类型的进展。越来越复杂的光化学过程，从简单的能量转移到光驱动的聚合反应将被调查，他们观察到的反应模式将被建模，比较和分析。工作的初始阶段将集中在铱配合物催化的光催化反应。由于能够容易地合成跨越巨大化学空间的结构，这些有望提供优异的试验系统，但其中结构-活性关系难以建模和预测。后来的努力将增加光催化剂的化学和结构多样性，包括更广泛的各种配体框架和涉及具有一系列电子结构的中心离子。光催化剂的量子化学计算将是一种基于特征学习的方法的基础，用于发现和预测所研究的光化学系统中的结构性质/（反应）活性关系。该奖项反映了NSF的法定使命，并被认为值得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来支持。

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 interplay of matter and energy in light-driven chemical transformations. The proposed work utilizes an investigative approach that seeks to accelerate chemical discovery and enhance control of chemical reactions by developing new tools integrating high-throughput experiments, quantum chemistry, and data science. The Bernhard lab involves a diverse group of researchers to accomplish these research tasks. Stefan Bernhard and his research team will be involved in outreach activities for non-scientists to educate the public on energy issues and instill excitement for science, in general.With the support of the Chemical Catalysis program in the Division of Chemistry, Professor Stefan Bernhard of Carnegie Mellon University will study the complex interplay of reagents and catalysts in light-driven chemical processes. The funded research will create a deeper understanding by using new tools integrating high-throughput experiments, quantum chemistry, and data science. The created artificial intelligence resulting from a merger of chemical theory and chemical data will allow the capture of the effects of complex many-body electronic interactions that elude current algorithms. To gather the data needed to drive this effort, the Bernhard team will develop massively parallel, automated chemical reactors capable of sensing and recording the progress on a variety of reaction types in parallel and in real time. Increasingly complex photochemical processes ranging from simple energy transfers to light-driven polymerizations will be investigated and their observed reactivity patterns will be modeled, compared and analyzed. The initial phase of the work will focus on photocatalytic reactions catalyzed by iridium complexes. These are expected to provide an excellent trial system due to the ability to easily synthesize structures that span a vast chemical space, but where the structure-activity relationships have been difficult to model and predict. Later efforts will increase the chemical and structural diversity of the photocatalyst by inclusion of a much wider variety of ligand frameworks and involving central ions with a range of electronic structures. Quantum chemical calculations on the photocatalysts will be the basis of a feature learning-based approach to find and predict structure property/(re)activity relationships in the studied photochemical systems.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.