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通过几何互补对杂配体顺式-PdLL'配位笼进行的实验与计算联合探索

A Combined Experimental and Computational Exploration of Heteroleptic cis-PdLL' Coordination Cages through Geometric Complementarity.

作者信息

Tarzia Andrew, Shan Wentao, Posligua Victor, Cox Cameron J T, Male Louise, Egleston Benjamin D, Greenaway Rebecca L, Jelfs Kim E, Lewis James E M

机构信息

Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Torino, Italy.

Department of Chemistry, Imperial College London, Molecular Sciences Research Hub, White City Campus, Wood Lane, London, W12 0BZ, UK.

出版信息

Chemistry. 2025 Jan 2;31(1):e202403336. doi: 10.1002/chem.202403336. Epub 2024 Nov 16.

Abstract

Heteroleptic (mixed-ligand) coordination cages are of interest as host systems with more structurally and functionally complex cavities than homoleptic architectures. The design of heteroleptic cages, however, is far from trivial. In this work, we experimentally probed the self-assembly of Pd(II) ions with binary ligand combinations in a combinatorial fashion to search for new cis-PdLL' heteroleptic cages. A hierarchy of computational analyses was then applied to these systems with the aim of elucidating key factors for rationalising self-assembly outcomes. Simple and inexpensive geometric analyses were shown to be effective in identifying complementary ligand pairs. Preliminary results demonstrated the viability of relatively rapid semi-empirical calculations for predicting the topology of thermodynamically favoured assemblies with rigid ligands, whilst more flexible systems proved challenging. Stemming from this, key challenges were identified for future work developing effective computational forecasting tools for self-assembled metallo-supramolecular systems.

摘要

杂配体(混合配体)配位笼作为主体系统备受关注,因为其具有比均配体结构更具结构和功能复杂性的空腔。然而,杂配体笼的设计绝非易事。在这项工作中,我们以组合方式实验性地探究了钯(II)离子与二元配体组合的自组装,以寻找新的顺式 - PdLL' 杂配体笼。然后对这些系统应用了一系列计算分析,目的是阐明合理化自组装结果的关键因素。结果表明,简单且廉价的几何分析在识别互补配体对方面是有效的。初步结果证明,对于预测具有刚性配体的热力学有利组装体的拓扑结构,相对快速的半经验计算是可行的,而对于更灵活的系统则具有挑战性。由此,确定了未来开发用于自组装金属超分子系统的有效计算预测工具的关键挑战。

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