(768b) Effective Coordination Based Descriptors for Rational Design of Metal Nanocatalysts | AIChE

(768b) Effective Coordination Based Descriptors for Rational Design of Metal Nanocatalysts


Ma, X. - Presenter, Virginia Polytechnic Institute and State University
Wang, S., Virginia Polytechnic Institute and State University
Xin, H., Virginia Tech

Coordination based Descriptors for Rational Design of Metal Nanocatalysts

Xianfeng Ma, Siwen Wang and Hongliang Xin*

Department of Chemical Engineering,
Virginia Tech,

Blacksburg, VA, 24061


Session: Catalysis and Reaction Engineering Division
¨C Rational Catalyst Design

One major challenge for designing metal nanocatalysts
is to know a priori the appropriate surface structure for a given catalytic
reaction. Understanding the effects of particle morphology and composition on the
interaction of surface atoms with adsorbates is of pivotal importance for
identifying optimal active sites and engineering nanoparticles with maximized
fraction of such sites. Many efforts have been made aiming to predict the
binding energy of an adsorbate at metal surfaces using the electronic and/or
geometric factors of the adsorption site (termed descriptor).2,3 While these
models have been successfully used as reactivity descriptors for either
extended-metal surfaces or simple metal nanoparticles, their extension to complex
particle systems with varying broken-bond strains and/or metal ligands remains
elusive due to a formidable computational cost or the lack of an explicit
consideration of interatomic interactions.

this work, we present the effective coordination number (CNe) as an
interaction-aware reactivity descriptor for metal nanocatalysts4. The
CNe, quantified by interatomic coupling matrix elements between the
site of interest and its all neighbors within a certain cutoff radius, provides
a robust description of CO, O2, and O adsorption energies on Au
metal nanoparticles of varying sizes and shapes attributed to its explicit
consideration of broken-bond strains (see Fig. 1 for CO as an example).
Importantly, the CNe has a solid physiochemical basis via a direct
connection to the moment characteristics (e.g., center) of occupied density of
states projected onto valence orbitals of the adsorption site. Furthermore, the
CNe shows promise as a general descriptor for predicting adsorption
properties of core-shell and alloyed structures of Au nanoparticles with d10
metal ligands (e.g., Cu and Ag). The approach can be readily extended to
understand and predict reactivity trends of large and more complex metal
catalysts with defects, impurities, transition-metal additions, supports, etc,
and thus provides a general basis for rational design of metal nanocatalysts.

1. Adsorption energies of *CO atop described by CNe on various
surface sites of Au nanoparticles and extended surfaces. The statistics of linear
regression (solid line) are also given.


1. Calle-Vallejo,
F. et al. Finding optimal surface sites on heterogeneous catalysts by
counting nearest neighbors. Science 350, 185¨C189 (2015).

2. Hammer, B. & Nørskov, J. K.
Electronic factors determining the reactivity of metal surfaces. Surf. Sci.
343, 211¨C220 (1995).

3. Calle-Vallejo, F. et al. Fast
Prediction of Adsorption Properties for Platinum Nanocatalysts with Generalized
Coordination Numbers. Angew. Chem. Int. Ed. 53, 8316¨C8319 (2014).

4. Ma, X., Wang, S. & Xin, H.
Effective Coordination Number as a Reactivity Descriptor for Coinage Metal
Nanocatalysts. Submitted (2016).