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Unravelling dataset effects in machine-learning screening of perovskite oxides for solar hydrogen production
Machine-learning (ML) models are increasingly used to accelerate the discovery of oxide materials for solar thermochemical hydrogen production (STCH), where oxygen vacancy formation enthalpy is a key descriptor of redox behaviour. However, the predictive reliability of oxygen vacancy f
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