CAS: Developing Data-Driven, Automated Methodology to Understand and Control Light-Driven Catalytic Processes
CAS: Developing Data-Driven, Automated Methodology to Understand and Control Light-Driven Catalytic Processes
批准号:
2350257
负责人:
Stefan Bernhard
金额:
$57.5万
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
项目状态:
未结题
起止时间:
2024-09-01 至 2027-08-31
中文摘要
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,这将为太阳能、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源于扩展现有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。这项工作的重点之一将是利用甘油、糖或纤维素等生物可利用的前体光能制氢。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研究协议将创建重要的数据集,这些数据集将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、光催化和数据科学领域对他们进行强烈的训练。伯恩哈德实验室涉及并训练了一组不同的研究人员来完成这些研究任务。伯恩哈德教授和他的团队将继续为非科学家开展外展活动,向公众宣传能源问题,并灌输对科学的热情。根据该奖项,伯恩哈德研究小组将在开发和使用氢敏感膜的基础上,开发互补的氧敏感膜。这些薄膜将允许在96孔板上快速筛选氢和氧演化光反应的过程。这项技术将使该团队能够详细阐述早期的结果,即从甘油作为电子和质子的来源光产生氢,现在过渡到越来越困难,但更理想的底物,如单糖或多糖。多井光反应器将产生大量数据集,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启发机器学习方法进行探索。这些实验将成为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的能力是开发一种能同时产生氢和氧的功能性水分解系统的必要步骤。通过结合和应用从每个半反应的工作中获得的知识,将上述高通量技术应用于这种水光解系统。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。
英文摘要
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.
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会议论文
D3SC: Developing Data-Driven, Automated Methodology to Understand and Control Light-Driven Catalytic Processes
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批准号:2102460
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项目类别:Continuing Grant
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资助金额:$55.0万
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依托单位:
CAREER: Synthetically Tuned Luminophoric Materials: 3D Displays, Solar Energy Conversion and Beyond
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批准号:0949238
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项目类别:Continuing Grant
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资助金额:$28.8万
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财政年份:2009
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负责人:Stefan Bernhard
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依托单位:
CAREER: Synthetically Tuned Luminophoric Materials: 3D Displays, Solar Energy Conversion and Beyond
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批准号:0449755
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资助金额:$56.6万
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财政年份:2005
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负责人:Stefan Bernhard
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依托单位:
海外基金