提高电化学C─N偶联反应尿素定量准确性和可靠性的改进方案。

IF 10.7 2区 材料科学 Q1 CHEMISTRY, PHYSICAL
Weidong Dai, Shiyong Mou, Siyuan Liu, Peng Xu, Chiyao Tang, Keying Wu, Xing'an Dong, Lei Xiao, Chang Long, Fan Dong
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引用次数: 0

摘要

在碳氮可持续循环需求的推动下,尿素合成中的电化学碳氮偶联引起了人们的广泛关注。尿素定量为深入了解结构-性能相关性和性能的迭代优化提供了基础。然而,目前的尿素定量方法存在不可忽视的缺陷,很大程度上带来了假阳性或假阴性的风险。在此,最容易获得和常用的定量技术,即二乙酰单肟-硫代氨基脲和基于脲酶的方法,全面重新评估。对亚硝酸盐、金属杂质和标准曲线方案所引起的不利影响进行了彻底的鉴定。最重要的是,提出了直接解决问题的策略,分别通过化学预还原、电替换和改进标准曲线方案来排除这些混杂因素。这种精细化的尿素定量方法可以巩固尿素电合成研究的再生产,从而促进这一新兴领域的健康发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Refined Protocol for Improving Accuracy and Reliability in Urea Quantification During Electrochemical C─N Coupling Reactions.

Promoted by the growing demand for sustainable carbon and nitrogen cycling, electrochemical C─N coupling in urea synthesis has attracted intensive interest. Urea quantification provides the basis for an in-depth understanding of structure-performance correlations and the iterative optimization of performance. However, current urea quantification methods have non-negligible drawbacks, largely bringing about false positive or negatives risks. Herein, the most accessible and commonly used quantification techniques, namely the diacetylmonoxime-thiosemicarbazide and Urease-based methods, are comprehensively re-assessed. The adverse impacts caused by nitrite, metallic impurities, and standard curve protocol are thoroughly identified. Most importantly, direct problem-solving strategies are proposed to rule out those confounding factors by chemical pre-reduction, galvanic replacement, and refinement of the standard curve protocol, respectively. This refined urea quantification method can solidify the reproduction of urea electrosynthesis studies and thus promote the sound development of this emerging field.

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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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