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在酸衍生催化剂上的CO2电还原中,基于NMR的液体产品的量化

Phil Preikschas¹, Antonio J Martín¹, Boon Siang Yeo²

¹Institute of Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zurich, Vladimir-Prelog-Weg 1, 8093, Zurich, Switzerland.

Communications chemistry

|July 10, 2023

概括

新的分析方法改善了使用催化剂的二氧化碳电还原过程中的多碳产品的检测. 这项研究提高了产品量化的准确性,有助于促进可持续化学生产的催化剂开发.

科学领域:

电化学电化学电化学
催化剂是一种催化剂.
分析化学分析化学

背景情况:

酸盐衍生的Ni催化剂显示出通过二氧化碳电还原产生多碳产品的前景.
优化C3+产品形成需要了解电极电位,pH和缓冲容量的影响.
准确量化产品,特别是长链化合物,具有挑战性,限制了催化剂评估.

研究的目的:

开发敏感的分析协议,以准确评估二氧化碳电还原中的液体产品.
改进多碳产品的量化,并识别以前未报告的化合物.
为增强催化剂评估和理解性能趋势提供工具.

主要方法:

开发敏感的1H NMR光谱学协议,以优化水抑制和减少实验时间.
实现一个自动化的NMR数据处理程序,用于快速样本分析.
应用这些方法来评估二氧化碳电还原的酸盐衍生Ni催化剂.

主要成果:

在15分钟内量化最多12种产品,量化极限较低 (0.1%法拉第效率).
识别了四种以前没有报告的化合物:乙酸盐,乙烯基醇,酸和i-propanol.
披露与催化剂参数相关的碳产品形成的性能趋势.

结论:

开发的NMR协议显著提高了二氧化碳电还原液体产品分析的准确性和效率.
这些进步有助于发现新产品和优化用于多碳合成的Ni催化剂.
这些发现有助于开发更有效的途径,从二氧化碳中生产可持续化学品.

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