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Genetic optimization of homogeneous catalysts

Ruben Laplaza1,2, Simone Gallarati1, Clemence Corminboeuf1,2*

1 École Polytechnique Fédérale de Lausanne (EPFL), Laboratory for Computational Molecular Design (LCMD), CH-1015 Lausanne, Switzerland

2 National Center for Competence in Research-Catalysis (NCCR-Catalysis), École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland

* Corresponding authors emails: clemence.corminboeuf@epfl.ch
DOI10.24435/materialscloud:fz-sw [version v1]

Publication date: Jan 21, 2022

How to cite this record

Ruben Laplaza, Simone Gallarati, Clemence Corminboeuf, Genetic optimization of homogeneous catalysts, Materials Cloud Archive 2022.9 (2022), doi: 10.24435/materialscloud:fz-sw.

Description

We present the NaviCatGA package, a versatile genetic algorithm capable of optimizing molecular catalyst structures using well-suited fitness functions to achieve a set of targeted properties. The flexibility and generality of this tool are demonstrated with two examples: i) Ligand optimization and exploration for Ni-catalyzed aryl-ether cleavage manipulating SMILES and using a fitness function derived from molecular volcano plots, ii) multiobjective (i.e., activity/selectivity) optimization of bipyridine N.N'-dioxide Lewis basic organocatalysts for the asymmetric propargylation of benzaldehyde from 3D molecular fragments. We show that evolutionary optimization, enabled by NaviCatGA, is an efficient way of accelerating catalyst discovery that bypasses combinatorial scaling issues and incorporates compelling chemical constraints.

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Files

File name Size Description
README.txt
MD5md5:5d6fb80ada4d9630dd0a564159cecab5
2.5 KiB Describes the content of example_1.zip and example_2.zip in more detail.
example_1.zip
MD5md5:c7a611baa648f6c0daccfbdd62a33575
182.1 MiB Contains structures for the GA runs in Example 1, training data for the ML model and code snippets of the GA setup.
example_2.zip
MD5md5:f06c2df72bce0bf23a6379ccad8addf1
1.6 MiB Contains structures for the GA runs in Example 2, training data for the MLR model and code snippets of the GA setup.

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Journal reference
R. Laplaza, S. Gallarati and C. Corminboeuf. Genetic Optimization of Homogeneous Catalysts, Submitted
Software (Software associated with the data and the publication.)

Keywords

homogeneous catalysis volcano plot catalysis optimization organocatalysis

Version history:

2022.9 (version v1) [This version] Jan 21, 2022 DOI10.24435/materialscloud:fz-sw