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This work explores the use of joint density-functional theory, a new form of density-functional theory for the ab initio description of electronic systems in thermodynamic equilibrium with a liquid environment, to describe electrochemical systems. After reviewing the physics of the underlying fundamental electrochemical concepts, we identify the mapping between commonly measured electrochemical observables and microscopically computable quantities within an, in principle, exact theoretical framework. We then introduce a simple, computationally efficient approximate functional which we find to be quite successful in capturing a priori basic electrochemical phenomena, including the capacitive Stern and diffusive Gouy-Chapman regions in the electrochemical double layer, quantitative values for interfacial capacitance, and electrochemical potentials of zero charge for a series of metals. We explore surface charging with applied potential and are able to place our ab initio results directly on the scale associated with the Standard Hydrogen Electrode (SHE). Finally, we provide explicit details for implementation within standard density-functional theory software packages at negligible computational cost over standard calculations carried out within vacuum environments.
Density Functional Theory (DFT) calculations have been widely used to predict the activity of catalysts based on the free energies of reaction intermediates. The incorporation of the state of the catalyst surface under the electrochemical operating c
External potentials play a crucial role in modelling quantum systems, since, for a given inter- particle interaction, they define the system Hamiltonian. We use the metric space approach to quantum mechanics to derive, from the energy conservation la
We propose a method to decompose the total energy of a supercell containing defects into contributions of individual atoms, using the energy density formalism within density functional theory. The spatial energy density is unique up to a gauge transf
Local field potentials (LFPs) sampled with extracellular electrodes are frequently used as a measure of population neuronal activity. However, relating such measurements to underlying neuronal behaviour and connectivity is non-trivial. To help study
Density-functional theory (DFT) has revolutionized computational prediction of atomic-scale properties from first principles in physics, chemistry and materials science. Continuing development of new methods is necessary for accurate predictions of n