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References from Global minimum search for transition metal nanoclusters with an embedded atom method potential in a DRL framework. Local targets link to admitted publications; unresolved targets remain external evidence.
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Global minima and structural properties of Au Fe nanoalloys from a Mexican enhanced genetic algorithm-based density functional theory
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Theoretical study of Cu–Au nanoalloy clusters using a genetic algorithm
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The DFT-genetic algorithm approach for global optimization of subnanometer bimetallic clusters
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Assessing the efficiency of first-principles basin-hopping sampling
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Structural and electronic properties of tungsten nanoclusters by DFT and basin-hopping calculations
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TGMin: A global-minimum structure search program based on a constrained basin-hopping algorithm
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Machine-learning driven global optimization of surface adsorbate geometries
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Nanocluster structure deduced from AC-STEM images coupled to theoretical modelling
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Study of melting phenomenon of a palladium nanocluster using molecular dynamics simulations
10.1007/978-981-96-0828-7_10 · 2025 · External reference
Reliability of two embedded atom models for the description of Ag@Au nanoalloys
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AI-accelerated search for global minimum configurations of Pt-Ni nanoclusters using embedded-atom method interatomic potential
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Fast and efficient prediction of the most stable nanoclusters using deep reinforcement learning: A case study on Ag13 (Ih) and Au7Ag6 (Ih)
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Deep reinforcement learning unveils ternary nanocluster configurations: A case study on Ag6Pd5Cu4
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