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A previous question addressed how to deal with charge defects in bulk materials. What can be done to treat a 2D surface with respect to charge?
For example, how can an absorption energy of OH- on Pt(111) be calculated and what should be considered in this system to get meaningful values. Likewise, what about a charged defect of the surface itself in a monolayer material such as graphene.
A straightforward way to model the interaction of charged species with a surface is to use a cluster model instead of simulating the surface as a slab with periodic boundary conditions (1).
Cluster models are not perfect, they can be affected by border effects that require large clusters, to be representative of the bulk system, by coverage effects, as a single molecule interacts with the surface, and charge effects, as in a cluster there is a small number of atoms, compared to the bulk, to delocalize the charge.
But they have the advantage of being amenable to the most powerful and accurate first-principles methods (2), trivially model charged species, and are well suited to studying the details of local chemical bonding. To incorporate bulk effects in cluster models, embedding potential methods have been proposed and successfully applied to the O$_2$ reaction on Al(111) (3), H$_2$ dissociation on the Au nanoparticle (4), adsorption (2), and band gaps (5). I have used a Pt$_{15}$ cluster to investigate the adsorption of L-cysteine (that can be charged depending on the pH) on Pt(111) (The geometries for the clusters are given in the Electronic Supplementary Material) (6).
You can start with the geometry of the slab and cut a cluster that is large enough to describe your system but small enough to be run a calculation in a reasonable time. Usually, the atoms on the border of the cluster and in lower layers have their positions fixed to avoid large distortions. The charge of the system will be equal to the charge of the adsorbent, assuming that your surface is neutral. Any molecular electronic structure code can be used for that. I recommend using Orca.
References
L. A. Curtiss, M. S. Gordon (eds.), Computational Materials Chemistry: Methods and Applications, Springer (2005).
A. Kubas, D. Berger, H. Oberhofer, D. Maganas, K. Reuter, F. Neese, Surface Adsorption Energetics Studied with “gold Standard” Wave-Function-Based Ab Initio Methods: Small-Molecule Binding to TiO2(110). J. Phys. Chem. Lett. 7, 4207–4212 (2016).
F. Libisch, C. Huang, P. Liao, M. Pavone, E. A. Carter, Origin of the energy barrier to chemical reactions of O 2 on Al(111): Evidence for charge transfer, not spin selection. Phys. Rev. Lett. 109, 1–5 (2012).
F. Libisch, J. Cheng, E. A. Carter, Electron-transfer-induced dissociation of H2 on gold nanoparticles: Excited-state potential energy surfaces via embedded correlated wavefunction theory. Z. Phys. Chem. 227, 1455–1466 (2013).
A. Dittmer, R. Izsák, F. Neese, D. Maganas, Accurate Band Gap Predictions of Semiconductors in the Framework of the Similarity Transformed Equation of Motion Coupled Cluster Theory. Inorg. Chem. 58, 9303–9315 (2019).
A. H. B. Dourado, A. P. de Lima Batista, A. G. S. Oliveira-Filho, P. T. A. Sumodjo, S. I. Cordoba de Torresi, l -Cysteine electrooxidation in alkaline and acidic media: a combined spectroelectrochemical and computational study. RSC Adv. 7, 7492–7501 (2017).
