Solid-liquid interfaces are at the heart of many modern-day technologies and provide a challenge to many materials simulation methods. A realistic first-principles computational study of such systems entails the inclusion of solvent effects. In this work, we implement an implicit solvation model that has a firm theoretical foundation into the widely used density-functional code Vienna ab initio Software Package. The implicit solvation model follows the framework of joint density functional theory. We describe the framework, our algorithm and implementation, and benchmarks for small molecular systems. We apply the solvation model to study the surface energies of different facets of semiconducting and metallic nanocrystals and the S_N2 reaction pathway. We find that solvation reduces the surface energies of the nanocrystals, especially for the semiconducting ones and increases the energy barrier of the S_N2 reaction.

Decay of surface plasmons to hot carriers finds a wide variety of applications in energy conversion, photocatalysis and photodetection. However, a detailed theoretical description of plasmonic hot-carrier generation in real materials has remained incomplete. Here we report predictions for the prompt distributions of excited ‘hot’ electrons and holes generated by plasmon decay, before inelastic relaxation, using a quantized plasmon model with detailed electronic structure. We find that carrier energy distributions are sensitive to the electronic band structure of the metal: gold and copper produce holes hotter than electrons by 1–2 eV, while silver and aluminium distribute energies more equitably between electrons and holes. Momentum-direction distributions for hot carriers are anisotropic, dominated by the plasmon polarization for aluminium and by the crystal orientation for noble metals. We show that in thin metallic films intraband transitions can alter the carrier distributions, producing hotter electrons in gold, but interband transitions remain dominant.

Energy and environmental concerns demand development of more efficient and selective electrodes for electrochemical reduction of CO2 to form fuels and chemicals. Since Cu is the only pure metal exhibiting reduction to form fuels and chemicals, we focus here on the Cu(111) electrode. We present a methodology for density functional theory (DFT) calculations to obtain accurate onset electrochemical potentials with explicit constant electrochemical potential and pH effects using implicit solvation. We predict the atomistic mechanisms underlying electrochemical reduction of CO, finding that (1) at acidic pH, the C1 pathway proceeds through COH to CHOH to form CH4 while C2 (C3) pathways are kinetically blocked; (2) at neutral pH, the C1 and C2 (C3) pathways share the COH common intermediate, where the branch to C-C coupling is realized by a novel CO-COH pathway; (3) at high pH, early C-C coupling through adsorbed CO dimerization dominates, suppressing the C1 pathways by kinetics, thereby boosting selectivity for multi-carbon products.

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 new classes of materials and properties, and for connecting to nano- and mesoscale properties using coarse-grained theories. JDFTx is a fully-featured open-source electronic DFT software designed specifically to facilitate rapid development of new theories, models and algorithms. Using an algebraic formulation as an abstraction layer, compact C++11 code automatically performs well on diverse hardware including GPUs (Graphics Processing Units). This code hosts the development of joint density-functional theory (JDFT) that combines electronic DFT with classical DFT and continuum models of liquids for first-principles calculations of solvated and electrochemical systems. In addition, the modular nature of the code makes it easy to extend and interface with, facilitating the development of multi-scale toolkits that connect to ab initio calculations, e.g. photo-excited carrier dynamics combining electron and phonon calculations with electromagnetic simulations.

Nanoscale localization of electromagnetic fields near metallic nanostructures underpins the fundamentals and applications of plasmonics. The unavoidable energy loss from plasmon decay, initially seen as a detriment, has now expanded the scope of plasmonic applications to exploit the generated hot carriers. However, quantitative understanding of the spatial localization of these hot carriers, akin to electromagnetic near-field maps, has been elusive. Here we spatially map hot-electron-driven reduction chemistry with 15 nm resolution as a function of time and electromagnetic field polarization for different plasmonic nanostructures. We combine experiments employing a six-electron photo-recycling process that modify the terminal group of a self-assembled monolayer on plasmonic silver nanoantennas, with theoretical predictions from first-principles calculations of non-equilibrium hot-carrier transport in these systems. The resulting localization of reactive regions, determined by hot-carrier transport from high-field regions, paves the way for improving efficiency in hot-carrier extraction science and nanoscale regio-selective surface chemistry.