Properties of solid-liquid interfaces are of immense importance for electrocatalytic and electrochemical systems but modeling such interfaces at the atomic level presents a serious challenge and approaches beyond standard methodologies are needed. An atomistic computational scheme needs treat at least part of the system quantum mechanically to describe adsorption and reactions while the entire system is in thermal equilibrium. The experimentally relevant macroscopic control variables are temperature, electrode potential, choice of the solvent and ions and these need to be explicitly included in the computational model as well; this calls for an thermodynamic ensemble with fixed ion and electrode potentials. In this work a general framework within density functional theory (DFT) with fixed electron and ion chemical potentials in the grand canonical (GC) ensemble is established for modeling electrocatalytic and electrochemical interfaces. Starting from a fully quantum mechanical description of multi-component GC-DFT for nuclei and electrons, a systematic coarse-graining is employed to establish various computational schemes including i) the combination of classical and electronic density functional theories within the grand canonical ensemble and ii) on the simplest level a chemically and physically sound way to obtain various (modified) Poisson-Boltzmann (mPB) implicit solvent models. The detailed and rigorous derivation clearly establishes which approximations are needed for coarse-graining as well as highlights which details and interactions are omitted in vein of computational feasibility. The transparent approximations also allow removing some the constraints and coarse-graining if needed. We implement various mPB models within a linear dielectic continuum in the GPAW code and test their capabilities to model capacitance of electrochemical interfaces as well as study different approaches for modeling partly periodic charged systems. Our rigorous and well-defined DFT coarse-graining scheme to continuum electrolytes highlights the inadequacy of current linear dielectric models for treating properties of the electrochemical interface.

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Electrochemical N 2 reduction (NRR) to ammonia is seriously limited by the competing hydrogen evolution reaction (HER), but atomic-scale factors controlling HER/NRR competition are unknown. Herein we unveil the mechanism, thermodynamics, and kinetics determining the HER/NRR efficiency on the state-of-the-art NRR electrocatalyst, Ru-N 4 , using grand canonical ensemble density functional theory (GCE-DFT). We show that NRR/HER intermediates coadsorb on the catalyst where NRR intermediates suppress HER and selectivity is determined by the initial step forming *NNH or *H. Our results provide crucial insight into the complex NRR/HER competition, show the necessity of using GCE-DFT calculations, and suggest ways to improve NRR selectivity.

A generally valid rate theory at fixed potentials is developed to treat electrochemical and electrocatalytic potential-dependent electron, proton, and proton-coupled electron reactions. Both classical and quantum reactions in adiabatic and non-adiabatic limits are treated. The applicability and new information obtained from the theory is demonstrated for the gold catalyzed acidic Volmer reaction. File list (3) download file view on ChemRxiv appendix.pdf (649.78 KiB) download file view on ChemRxiv main_article.pdf (1.12 MiB) download file view on ChemRxiv supporting_info.pdf (384.50 KiB)

Materials exhibiting a substitutional disorder such as multicomponent alloys and mixed metal oxides/oxyfluorides are of great importance in many scientific and technological sectors. Disordered materials constitute an overwhelmingly large configurational space, which makes it practically impossible to be explored manually using first-principles calculations such as density functional theory (DFT) due to the high computational costs. Consequently, the use of methods such as cluster expansion (CE) is vital in enhancing our understanding of the disordered materials. CE dramatically reduces the computational cost by mapping the first-principles calculation results on to a Hamiltonian which is much faster to evaluate. In this work, we present our implementation of the CE method, which is integrated as a part of the Atomic Simulation Environment (ASE) open-source package. The versatile and user-friendly code automates the complex set up and construction procedure of CE while giving the users the flexibility to tweak the settings and to import their own structures and previous calculation results. Recent advancements such as regularization techniques from machine learning are implemented in the developed code. The code allows the users to construct CE on any bulk lattice structure, which makes it useful for a wide range of applications involving complex materials. We demonstrate the capabilities of our implementation by analyzing the two example materials with varying complexities: a binary metal alloy and a disordered lithium chromium oxyfluoride.