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In complexation reactions, metal cations are the electron pair acceptors, and the ligands are the electron pair donors. The stability of the metal complexes depends primarily on the complexing ability of the central metal ion and the nature of the ligands. Generally, the complexing ability of the metal ion depends on the size and charge of the ion. As the metal ion size increases, the stability of the metal complexes decreases, provided that the valency of the metal ion and the ligands remain...
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The hemoglobin in the blood, the chlorophyll in green plants, vitamin B-12, and the catalyst used in the manufacture of polyethylene all contain coordination compounds. Ions of the metals, especially the transition metals, are likely to form complexes.
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Directional multiobjective optimization of metal complexes at the billion-system scale.

Hannes Kneiding1, Ainara Nova1,2, David Balcells3

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We present the tmQMg-L ligand library and the Pareto-Lighthouse multiobjective genetic algorithm (PL-MOGA) for discovering optimal transition metal complexes (TMCs). This approach efficiently generates diverse TMCs with desired properties.

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Area of Science:

  • Computational chemistry
  • Materials science
  • Ligand design

Background:

  • Discovering transition metal complexes (TMCs) with optimal properties necessitates extensive ligand libraries and advanced optimization algorithms.
  • Existing methods often struggle with the vast chemical space and complex multiobjective optimization challenges.

Purpose of the Study:

  • To introduce the tmQMg-L library, a large collection of diverse and synthesizable ligands with assigned properties.
  • To develop and validate the Pareto-Lighthouse multiobjective genetic algorithm (PL-MOGA) for efficient TMC discovery.
  • To demonstrate the algorithm's ability to optimize multiple properties simultaneously without predefined limits.

Main Methods:

  • Generation of the tmQMg-L library comprising 30,000 ligands with characterized charges and coordination modes.
  • Creation of 1.37 million palladium TMCs using the tmQMg-L library.
  • Development and application of the PL-MOGA, employing whole-ligand mutation and crossover operations.
  • Benchmarking the PL-MOGA against established optimization strategies.

Main Results:

  • The tmQMg-L library facilitated the generation of a vast dataset of palladium TMCs.
  • The PL-MOGA successfully maximized polarizability and the highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap of TMCs.
  • The algorithm navigated complex chemical spaces, yielding thousands of diverse TMCs in an interpretable manner.
  • PL-MOGA demonstrated efficient optimization without prior knowledge of objective limits.

Conclusions:

  • The tmQMg-L library and PL-MOGA provide a powerful, integrated platform for accelerating the discovery of novel transition metal complexes.
  • The PL-MOGA's whole-ligand operations offer a more interpretable and efficient approach to exploring large chemical spaces.
  • This methodology enables fine control over property optimization, advancing the design of functional materials.