This synthesis method shows higher reaction rates in catalytic materials, highlighting machine learning integration and multimetallic design.
Abstract Engineering colloidally stable multimetallic nanocrystals has many benefits in a wide range of applications and allows manipulating physical, chemical, and electronic structure properties of materials at the nanoscale. Synthesis routes are challenged by the chemical complexity required to temporally and spatially coordinate the reduction and alloying of multiple metal species, which hampered the development of tunable libraries of colloidal materials to date. In this work, we demonstrate a seed-mediated synthesis method to incorporate five or more metal elements in uniform, colloidally stable nanocrystals. By integrating machine learning-accelerated simulations, the synthesis of shortlisted high entropy alloy nanocrystals was demonstrated. Multiple seed materials can be used, leading to a library of multimetallic nanocrystals with tunable electronic, physical, and alloying structure. The advantage of this synthetic protocol is highlighted in the preparation of catalytic materials that showed two orders of magnitude higher reaction rates than monometallic catalysts and outstanding thermal stability, thus highlighting the promise of this approach for high-performance materials in many areas.
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Cargnello et al. (2025) studied this question.
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