Hosted by: Jose Rodriguez

Metal nanoparticles are key components of various functional materials, including catalysts. However, properties of monometallic particles are often insufficiently versatile, which limits their applications. Properties of mixed-metal nanoparticles (nanoalloys) can be tailored for a given application much easier. Yet, it is very laborious to determine the atomically resolved composition (chemical ordering) in nanoalloys, which is required for rationalizing their reactivity. We developed a method to optimize chemical ordering in nanoalloys using density functional calculations [1,2], which is applicable to various combinations of transition metals with each other and with s,p-elements [1-5]. The method allows one to predict energetically stable atomically resolved structures of nanoalloys, which can be then manufactured. I will outline the method and illustrate its applications to nanoalloys of Pd [1,2], Pt [3,4] and Ni [5]. Our new method enables generating databases of structures and energies of bimetallic nanoalloys spanning the Periodic Table. Its simplicity and reliability allows to provide researchers with unique opportunity to efficiently perform simulations of various nanoalloys with thousands of atoms. Applications of the method can radically accelerate design of tailor- made nanoalloys and deepen the general understanding of chemical bonding in nanoalloys. In the beginning of the talk I will also highlight some of my other other studies related to approaching complexity of nanomaterials for catalysis by density functional modelling [6-10]. References [1] S.M. Kozlov, G. Kovács, R. Ferrando, K.M. Neyman. How to determine accurate chemical ordering in several nanometer large bimetallic crystallites from electronic structure calculations. Chemical Science 6 (2015) 3868 [2] G. Kovács, S.M. Kozlov, K.M. Neyman. Versatile optimization of chemical ordering in bimetallic nanoparticles. J. Phys. Chem. C 121 (2017), doi: 10.1021/acs.jpcc.6b11923