Implicit solvation model for density-functional study of nanocrystal surfaces and reaction pathways

TLDR

Solid‑liquid interfaces are central to many technologies, yet first‑principles simulations must incorporate solvent effects, typically via joint density functional theory. The study implements a theoretically grounded implicit solvation model into the Vienna ab initio Software Package. The authors detail the joint density functional theory framework, algorithm, and implementation, benchmark it on small molecules, and apply it to nanocrystal surface energies and an SN2 reaction pathway. Solvation lowers nanocrystal surface energies—particularly for semiconductors—and raises the SN2 reaction barrier.

Abstract

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 SN2 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 SN2 reaction.