Midgley, S. D.Hamad, SHamad, SaidButler, K. T.Grau-Crespo, R.2025-01-312025-01-312021-05-25J. Phys. Chem. Lett. 2021, 12, 21, 5163–516810.1021/ACS.JPCLETT.1C01031https://hdl.handle.net/10433/22979Computer simulations of alloys’ properties often require calculations in a large space of configurations in a supercell of the crystal structure. A common approach is to map density functional theory results into a simplified interaction model using so-called cluster expansions, which are linear on the cluster correlation functions. Alternative descriptors have not been sufficiently explored so far. We show here that a simple descriptor based on the Coulomb matrix eigenspectrum clearly outperforms the cluster expansion for both total energy and bandgap energy predictions in the configurational space of a MgO–ZnO solid solution, a prototypical oxide alloy for bandgap engineering. Bandgap predictions can be further improved by introducing non-linearity via gradient-boosted decision trees or neural networks based on the Coulomb matrix descriptor.application/pdfenAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/AlloysCluster ChemistryElectrical ConductivityEnergySolutionsjournal articleopen access