十二烷基苯磺酸双齿配体衍生同感铁配合物的NBO、NLO和TD-DFT研究

IF 2.7 Q2 Chemistry Chemical Data Collections Pub Date : 2025-03-06 DOI:10.1016/j.cdc.2025.101186
Houari Brahim , Djebar Hadji , Zahia Zizi , Abdelkrim Guendouzi , Mostefa Boumediene
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引用次数: 0

摘要

本研究采用DFT和TD-DFT方法研究了十二烷基苯磺酸盐(DBS)与三种双齿配体配位的铁离子的结构、光学、非线性光学和光谱性质。用NBO分析研究了铁离子与三种双齿配体的配位性质。根据NBO Fock矩阵的二阶微扰分析,确定了络合过程中所涉及的相互作用。利用NTO分析方法对其紫外-可见吸收光谱进行了模拟和研究。发现在苯基轨道和金属轨道之间发生强烈的吸收。结果表明,该配合物具有高效的超瑞利散射和超极化特性。结果表明,该配合物具有作为非线性光学候选物的潜力。
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NBO, NLO and TD-DFT study of homoleptic iron complex derived from dodecyl benzene sulfonate bidentate ligand
In this study, we investigated structural, optical, nonlinear optical and spectroscopic properties of iron ion coordinated with three bidentate ligands based on dodecyl benzene sulfonate (DBS) using DFT and TD-DFT methods. Coordination properties between iron ion and the three bidentate ligands were studied using NBO analysis. The interactions involved in the complexation were identified according to second order perturbation analysis of the NBO Fock matrix. UV–vis absorption spectra were simulated and investigated in term of NTO analyzes. It was found that the intense absorptions occur between phenyl and metal orbitals. The results show the complex exhibits efficient hyper-Rayleigh scattering hyperpolarizability. This investigation showed the potential of this complex based on DBS as nonlinear optical candidate.
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来源期刊
Chemical Data Collections
Chemical Data Collections Chemistry-Chemistry (all)
CiteScore
6.10
自引率
0.00%
发文量
169
审稿时长
24 days
期刊介绍: Chemical Data Collections (CDC) provides a publication outlet for the increasing need to make research material and data easy to share and re-use. Publication of research data with CDC will allow scientists to: -Make their data easy to find and access -Benefit from the fast publication process -Contribute to proper data citation and attribution -Publish their intermediate and null/negative results -Receive recognition for the work that does not fit traditional article format. The research data will be published as ''data articles'' that support fast and easy submission and quick peer-review processes. Data articles introduced by CDC are short self-contained publications about research materials and data. They must provide the scientific context of the described work and contain the following elements: a title, list of authors (plus affiliations), abstract, keywords, graphical abstract, metadata table, main text and at least three references. The journal welcomes submissions focusing on (but not limited to) the following categories of research output: spectral data, syntheses, crystallographic data, computational simulations, molecular dynamics and models, physicochemical data, etc.
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