Suppr超能文献

利用铑羰基片段探究钳形配体的给体性质:一个实验与计算的案例研究

Probing the Donor Properties of Pincer Ligands Using Rhodium Carbonyl Fragments: An Experimental and Computational Case Study.

作者信息

Parker Gemma L, Lau Samantha, Leforestier Baptiste, Chaplin Adrian B

机构信息

Department of Chemistry University of Warwick Gibbet Hill Road CV4 7AL Coventry UK.

出版信息

Eur J Inorg Chem. 2019 Sep 8;2019(33):3791-3798. doi: 10.1002/ejic.201900727. Epub 2019 Aug 23.

Abstract

Metal carbonyls are commonly employed probes for quantifying the donor properties of monodentate ligands. With a view to extending this methodology to -tridentate "pincer" ligands, the spectroscopic properties [ν(CO), , ] of rhodium(I) and rhodium(III) carbonyl complexes of the form [Rh(pincer)(CO)][BAr ] and [Rh(pincer)Cl(CO)][BAr ] have been critically analysed for four pyridyl-based pincer ligands, with two flanking oxazoline (NNN), phosphine (PNP), or N-heterocyclic carbene (CNC) donors. Our investigations indicate that the carbonyl bands of the rhodium(I) complexes are the most diagnostic, with frequencies discernibly decreasing in the order NNN > PNP > CNC. To gain deeper insight, a DFT-based energy decomposition analysis was performed and identified important bonding differences associated with the conformation of the pincer backbone, which clouds straightforward interpretation of the experimental IR data. A correlation between the difference in carbonyl stretching frequencies Δν(CO) and calculated thermodynamics of the Rh/Rh redox pairs was identified and could prove to be a useful mechanistic tool.

摘要

金属羰基化合物通常用作定量单齿配体给体性质的探针。为了将这种方法扩展到三齿“钳形”配体,对四种基于吡啶的钳形配体(带有两个侧翼恶唑啉(NNN)、膦(PNP)或N-杂环卡宾(CNC)给体)的[Rh(钳形)(CO)][BAr]和[Rh(钳形)Cl(CO)][BAr]形式的铑(I)和铑(III)羰基配合物的光谱性质[ν(CO)、 、 ]进行了严格分析。我们的研究表明,铑(I)配合物的羰基谱带最具诊断性,频率按NNN > PNP > CNC的顺序明显降低。为了获得更深入的见解,进行了基于密度泛函理论(DFT)的能量分解分析,并确定了与钳形主链构象相关的重要键合差异,这使得对实验红外数据的直接解释变得模糊。羰基伸缩频率差Δν(CO)与铑/铑氧化还原对的计算热力学之间的相关性被确定,这可能被证明是一种有用的机理工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1578/6774296/eb9a04670108/EJIC-2019-3791-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验