This thesis will focus on DFT for calculations of large metallic nanoparticles. It will show new algorithms that were developed for reduced scaling DFT methods for metals; the testing, verification and design of new descriptors for predicting the catalytic activity of metallic nanoparticles; application of large-scale DFT calculations to model nanoparticle sequences to show size and oxygen adsorption coverage trends, and finally the application of these techniques and knowledge to perform a study of oxygen adsorption on real-world, experimentally determined platinum nanoparticles in collaboration with the Nellist group at Oxford materials. We explore the binding of atomic oxygen to cuboctahedral platinum nanoparticles of up to 1000 atoms using DFT calculations in ONETEP. We demonstrate convergence to the infinite slab limit for single oxygen adsorption in chapter 4 and correlate adsorption strength against popular descriptors for catalytic activity, such as the d-band centre approach. This approach is possible because of work which will be described in chapter 3 to implement angular momentum projected density of states calculations in ONETEP. The effects of oxygen coverage on the Pt55 and Pt147 cuboctahedral nanoparticles will also be analysed, which serves to advance our simulations towards realistic conditions. We show in our investigation into half monolayer, hemispherical oxygen coverage on platinum nanoparticles that oxygen tends to gravitate towards the edges and lower coordinated sites in the nanoparticle and away from the centres of facets. This effect correlates with the site specific, single oxygen adsorption energies on Pt309 and experimental platinum nanoparticles which is presented in chapter 5. We show that when subdividing the binding of monolayers of oxygen into only (111) and (100) facets that these have a lower adsorption strength per oxygen atom than combined (100) and (111) facets as well as lower binding strength than single oxygen adsoprtion. In the next part of the study, which is discussed in chapter 5, we show large scale DFT calculations on real platinum nanoparticles, which were measured by the Nellist group at Oxford materials using advanced electron microscopy techniques. These DFT calculations provide the electronic structure of the experimentally measured nanoparticles, which allowed us to apply electron density based catalytic activity descriptors to the nanoparticles, such as the d-band centre approach, or our own electronic density based descriptor described in chapter 3. We find that surface roughness of the experimental nanoparticles contributes to more potential oxygen binding sites with low electron density, which correlatates with stronger oxygen adsorption strength in our model, when compared with the relative smoothness of cuboctahedral and truncated octahedral facets. In the analysis which is presented in chapter 5, the proportion of sites which lie within 0.2 eV of the oxygen binding strength required for optimum catalytic activity is predicted with high efficiency, based on our catalytic activity descriptor. Finally, in chapter 6 we describe a new method for large scale DFT calculations on metallic systems which we call the AQuA-FOE method. We show how this method can have a computational cost which increases effectively linearly with the number of atoms. The AQuA-FOE method works by implicitly heating and quenching the electrons in the system to find the oneparticle density matrix, while conserving the electron number. We show validation of this method inside the EDFT procedure by comparing numerically with the diagonalisation based EDFT that is already implemented in ONETEP showing agreement in the energies to better than 10⁻⁵ EH per atom. We will also demonstrate the effectively linear-scaling computational cost of our method with calculation times on regular truncated octahedral Palladium nanoparticles ranging from 2,406 to 12,934 atoms.