PTML models of self assembled ligand free nanoparticle catalysts for cross coupling reactions
Abstract Cross-coupling reactions have transformed the synthesis of complex and valuable compounds used in pharmaceuticals, materials science, and chemical synthesis. Transition metal nanoparticle (NP) catalysts represent a promising strategy within this field, but their behavior and efficiency cont...
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Nature Portfolio
2025-08-01
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| Online Access: | https://doi.org/10.1038/s41598-025-14080-2 |
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| author | Andrea Ruiz-Escudero Zuriñe Serna-Burgos Sonia Arrasate Humberto González-Díaz |
| author_facet | Andrea Ruiz-Escudero Zuriñe Serna-Burgos Sonia Arrasate Humberto González-Díaz |
| author_sort | Andrea Ruiz-Escudero |
| collection | DOAJ |
| description | Abstract Cross-coupling reactions have transformed the synthesis of complex and valuable compounds used in pharmaceuticals, materials science, and chemical synthesis. Transition metal nanoparticle (NP) catalysts represent a promising strategy within this field, but their behavior and efficiency continue under investigation. The use of computational models enables rapid design, optimization, and understanding of the behavior of these molecules, thereby reducing the costs and time. In this study, the perturbation theory and machine learning (PTML) approach was used to construct a predictive model for estimating yield after multiple reuses (up to 10) of self-assembled Au- or glass-supported transition metal NP catalysts under ligand-free conditions and diverse cross-coupling reactions. The studied reactions include Suzuki–Miyaura, Kumada, Negishi, Buchwald-Hartwig, C(sp2)- and C(sp3)-H functionalization, and double carbonylation. A comprehensive dataset was built, and multiple linear regression (MLR) and artificial neural network (ANN) models were built and compared. The best MLR model achieved MAE = 7.4% and RMSE = 12.2% on the test set, demonstrating robust performance for yield prediction. Among the ANN models, MLP (9:9-20-9-1:1) and RBF (9:9-70-1:1) regression models showed similar results, with test MAE of 5.9% and 5.8% respectively, and both showed test RMSE of 9.8%. MLP (9:9-20-18-1:1) classification model showed high precision (97.0%) and recall (93.8%), effectively distinguishing high- and low-yielding reactions. These results highlight the potential of PTML-based models to guide catalyst and reaction condition selection, optimize catalytic systems, and minimize synthesis costs and environmental impact. |
| format | Article |
| id | doaj-art-c449feded7ce47c19b9767bb2dad631d |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-c449feded7ce47c19b9767bb2dad631d2025-08-20T03:42:41ZengNature PortfolioScientific Reports2045-23222025-08-0115111310.1038/s41598-025-14080-2PTML models of self assembled ligand free nanoparticle catalysts for cross coupling reactionsAndrea Ruiz-Escudero0Zuriñe Serna-Burgos1Sonia Arrasate2Humberto González-Díaz3Department of Computer Science and Information Technologies, Faculty of Computer Science, University of A CoruñaDepartment of Organic and Inorganic Chemistry, Faculty of Science and Technology, University of The Basque Country (UPV/EHU)Department of Organic and Inorganic Chemistry, Faculty of Science and Technology, University of The Basque Country (UPV/EHU)Department of Organic and Inorganic Chemistry, Faculty of Science and Technology, University of The Basque Country (UPV/EHU)Abstract Cross-coupling reactions have transformed the synthesis of complex and valuable compounds used in pharmaceuticals, materials science, and chemical synthesis. Transition metal nanoparticle (NP) catalysts represent a promising strategy within this field, but their behavior and efficiency continue under investigation. The use of computational models enables rapid design, optimization, and understanding of the behavior of these molecules, thereby reducing the costs and time. In this study, the perturbation theory and machine learning (PTML) approach was used to construct a predictive model for estimating yield after multiple reuses (up to 10) of self-assembled Au- or glass-supported transition metal NP catalysts under ligand-free conditions and diverse cross-coupling reactions. The studied reactions include Suzuki–Miyaura, Kumada, Negishi, Buchwald-Hartwig, C(sp2)- and C(sp3)-H functionalization, and double carbonylation. A comprehensive dataset was built, and multiple linear regression (MLR) and artificial neural network (ANN) models were built and compared. The best MLR model achieved MAE = 7.4% and RMSE = 12.2% on the test set, demonstrating robust performance for yield prediction. Among the ANN models, MLP (9:9-20-9-1:1) and RBF (9:9-70-1:1) regression models showed similar results, with test MAE of 5.9% and 5.8% respectively, and both showed test RMSE of 9.8%. MLP (9:9-20-18-1:1) classification model showed high precision (97.0%) and recall (93.8%), effectively distinguishing high- and low-yielding reactions. These results highlight the potential of PTML-based models to guide catalyst and reaction condition selection, optimize catalytic systems, and minimize synthesis costs and environmental impact.https://doi.org/10.1038/s41598-025-14080-2PTMLCheminformaticsLigand-freeSelf-assemblyNanoparticlesCross-coupling reaction |
| spellingShingle | Andrea Ruiz-Escudero Zuriñe Serna-Burgos Sonia Arrasate Humberto González-Díaz PTML models of self assembled ligand free nanoparticle catalysts for cross coupling reactions Scientific Reports PTML Cheminformatics Ligand-free Self-assembly Nanoparticles Cross-coupling reaction |
| title | PTML models of self assembled ligand free nanoparticle catalysts for cross coupling reactions |
| title_full | PTML models of self assembled ligand free nanoparticle catalysts for cross coupling reactions |
| title_fullStr | PTML models of self assembled ligand free nanoparticle catalysts for cross coupling reactions |
| title_full_unstemmed | PTML models of self assembled ligand free nanoparticle catalysts for cross coupling reactions |
| title_short | PTML models of self assembled ligand free nanoparticle catalysts for cross coupling reactions |
| title_sort | ptml models of self assembled ligand free nanoparticle catalysts for cross coupling reactions |
| topic | PTML Cheminformatics Ligand-free Self-assembly Nanoparticles Cross-coupling reaction |
| url | https://doi.org/10.1038/s41598-025-14080-2 |
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