Electronic Stability and Global Reactivity Descriptors of Cu–Sc Nanoclusters: A Multilevel DFT–PCA Study

The electronic stability and global reactivity of CuxScγ (x + y = 4) bimetallic nanoclusters were investigated within the framework of rational design of functional materials and active catalytic phases. M06-2X/def2-TZVP DFT was used for geometric optimization and electronic characterization, and global descriptors were calculated, including ΔEgap, chemical toughness, chemical potential, and electrophilicity. The orbital contribution was analyzed using DOS/PDOS with Multiwfn; PCA and ANOVA were applied to quantify descriptor–structure relationships. The results show that adding Sc changes the cluster’s electron density and stiffness in a consistent manner, enabling distinction between more stable and more reactive configurations. In particular, Cu3Sc is the most electronically stable, exhibiting the highest ΔEgap, while Cu2Sc2 shows a more tunable electronic response, consistent with scenarios requiring greater reactivity. Multivariate analysis shows that ΔEgap accounts for most of the electronic variability in the dataset, making it the primary descriptor for selection and design. Taken together, these results open a descriptor-guided path to designing active Cu–Sc phases for supported catalysis and to their assembly into tunable metal nanocomposites.

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Publication Details

Journal
Journal of Composites Science
Published
2026-01-30
DOI
https://doi.org/10.3390/jcs10020013
Primary Topic
Machine Learning in Materials Science
Type
article
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article

Electronic Stability and Global Reactivity Descriptors of Cu–Sc Nanoclusters: A Multilevel DFT–PCA Study

Ortega-Toro Rodrigo
Journal of Composites Science
Machine Learning in Materials Science
article

Electronic Stability and Global Reactivity Descriptors of Cu–Sc Nanoclusters: A Multilevel DFT–PCA Study

Ortega-Toro Rodrigo
article en

Abstract

The electronic stability and global reactivity of CuxScγ (x + y = 4) bimetallic nanoclusters were investigated within the framework of rational design of functional materials and active catalytic phases. M06-2X/def2-TZVP DFT was used for geometric optimization and electronic characterization, and global descriptors were calculated, including ΔEgap, chemical toughness, chemical potential, and electrophilicity. The orbital contribution was analyzed using DOS/PDOS with Multiwfn; PCA and ANOVA were applied to quantify descriptor–structure relationships. The results show that adding Sc changes the cluster’s electron density and stiffness in a consistent manner, enabling distinction between more stable and more reactive configurations. In particular, Cu3Sc is the most electronically stable, exhibiting the highest ΔEgap, while Cu2Sc2 shows a more tunable electronic response, consistent with scenarios requiring greater reactivity. Multivariate analysis shows that ΔEgap accounts for most of the electronic variability in the dataset, making it the primary descriptor for selection and design. Taken together, these results open a descriptor-guided path to designing active Cu–Sc phases for supported catalysis and to their assembly into tunable metal nanocomposites.

Journal of Composites ScienceVol. 10(2)
University of Cartagena (CO), University of the Coast (CO)
Openalex Percentile: Top 73%
Machine Learning in Materials Science
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