Front Cover: Accelerating the Structure Exploration of Diverse Bi–Pt Nanoclusters via Physics-Informed Machine Learning Potential and Particle Swarm Optimization (ChemPhysChem 19/2025)
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引用次数: 0
Abstract
The Front Cover evokes particle swarm optimization applied to Bi–Pt bimetallic nanoparticles. Each bird represents a candidate nanoparticle structure. The lake and its shorelines represent the potential energy surface, generated using the ChiMES physics-informed machine learning potential. The surrounding mountains symbolize transition states, while the dark whirlpool at the lake’s center is the global energy minimum. More information can be found in the Research Article by N. T. Van-Oanh and co-workers (DOI: 10.1002/cphc.202500268).
期刊介绍:
ChemPhysChem is one of the leading chemistry/physics interdisciplinary journals (ISI Impact Factor 2018: 3.077) for physical chemistry and chemical physics. It is published on behalf of Chemistry Europe, an association of 16 European chemical societies.
ChemPhysChem is an international source for important primary and critical secondary information across the whole field of physical chemistry and chemical physics. It integrates this wide and flourishing field ranging from Solid State and Soft-Matter Research, Electro- and Photochemistry, Femtochemistry and Nanotechnology, Complex Systems, Single-Molecule Research, Clusters and Colloids, Catalysis and Surface Science, Biophysics and Physical Biochemistry, Atmospheric and Environmental Chemistry, and many more topics. ChemPhysChem is peer-reviewed.