Highly Efficient Numerical Method for Modeling Mofs Containing Transition Metal Ions

IF 2.9 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY Journal of Computational Chemistry Pub Date : 2025-02-12 DOI:10.1002/jcc.27546
D. D. Raenko, A. L. Tchougreeff
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Abstract

Employing a group-function based semiempirical approach, a new program package ΣHΘΩ $$ \varSigma H\varTheta \varOmega $$ (seethoo), targeted to modeling of metal-organic frameworks (MOFs) containing transition metal ions (TMIs) with open d-shells is developed. In this proof of concept study it is shown that the ΣHΘΩ $$ \varSigma H\varTheta \varOmega $$ package has potential to accurately compute d-shell low-spin (LS) —high-spin (HS) gaps and charge distributions in MOFs in O N 1 . 33 $$ O\left({N}^{1.33}\right) $$ time with reasonable accuracy. The calculations were carried out for a variety of MOFs and MOF-like systems containing doubly and triply charged Mn, Fe, Co and Ni ions. For Fe-containing systems, parameters of 57 Fe $$ {}^{57}\mathrm{Fe} $$ Mössbauer spectra were also computed. For the test runs, the results reasonably agree with available experimental data up to errors introduced by use of the CNDO parametrization in the test manner.

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含过渡金属离子Mofs的高效数值模拟方法
采用基于群函数的半经验方法,开发了一个新的程序包ΣHΘΩ $$ \varSigma H\varTheta \varOmega $$ (seethoo),用于模拟含开放d壳层过渡金属离子(tmi)的金属有机骨架(mfs)。在这一概念验证研究中,表明ΣHΘΩ $$ \varSigma H\varTheta \varOmega $$包具有精确计算O N中mof中d壳层低自旋(LS) -高自旋(HS)间隙和电荷分布的潜力1。33 $$ O\left({N}^{1.33}\right) $$时间与合理的准确性。这些计算是针对多种mof和类mof体系进行的,这些体系含有双重和三重电荷的Mn、Fe、Co和Ni离子。对于含铁体系,还计算了57 Fe $$ {}^{57}\mathrm{Fe} $$ Mössbauer光谱参数。对于试验运行,结果与现有的实验数据基本一致,但不包括使用CNDO参数化在试验方式中引入的误差。
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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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