Adsorbate-adsorbate lateral interactions have been known to significantly affect

the binding energies of adsorbates in most of the reaction networks on any given

nano-catalytic surface. In events of multiple adsorptions which is almost the case in any

reaction network on a nano-catalytic surface, interactions between adsorbed species are

termed as adsorbate-adsorbate lateral interactions. Such, interactions have been known to

weaken the binding energy, thereby affecting the reaction energetics and hence affects

the suitability of a catalytic system for a given reaction scheme. Hence, it is very

important to quantify such interactions appropriately. Since, experiments at very small

length scales are very difficult to perform, computational techniques become a natural

choice to study the adsorption phenomena at nanometer length scales. Density functional

theory (DFT) is one of the most popular computational theories to study the physical

systems at small length scales where mainly quantum effects via Schrodinger wave-

equations are the governing mechanisms determining the course of the evaluation of such

systems. Many computational techniques have been tried in the past to inherently capture

the effects of lateral interactions while evaluating the binding energies. Cluster expansion

hamiltonians are one of the most popular approaches in this regard. However, this

approach is extremely tedious to carry out and is usually limited in applicability to predict

the binding energies of select few systems which are close to the sample space used to

evaluate the hamiltonians. Hence, it is important to devise a new model for lateral

interactions in a more robust manner which could be used in a wide array of problems.

My work is based upon studying seven candidate transition metals for catalytic systems:

Ag, Au, Cu, Ir, Pd, Pt and Rh and four simple gas phase adsorbate species: C, N, O

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and CO. All my results are based upon adsorption phenomena in a vacuum environment.

First part of my work is based upon devising parameterization schemes which are based

on a previous work where the metal binding energies to the same metallic surface are

calculated based upon the coordination numbers of the adsorbing atom and adsorbate

metal atoms. In the second, part of my work I investigated and found linear scaling

relationships between the binding energies of adsorbates and binding energies of metal

atoms. These relationships were developed based on single adsorption events which do

not incur lateral interactions and can be used as predictors for further binding events. In

the final, part of my work I have introduced a lateral interaction parameter which is added

to the binding energies predicted from the scaling relationships and is calculated by

finding scaling relationships for the interaction parameter as well. In the third part of my

work I have tested my approach on nitrate adsorption network. Firstly, I have evaluated

the reaction mechanism of NOx species reduction by candidate transition metal atoms in

an electrochemical environment and then used NO as an additional species to model the

lateral interactions in terms of the interaction parameter. It is envisaged that the results

obtained here could easily be extended to other atomic and molecular species in any

given common reaction network and hence, the overall scheme has a wide applicability

since by carrying out few DFT calculations it would be possible to calculate the binding

energies and hence work out potential energy diagram for many reaction networks.