Developing adaptive QM/MM computer simulations for electrochemistry

Abstract

We report the development of adaptive QM/MM computer simulations for electrochemistry, providing public access to all sources via the free and open source software development model. We present a modular workflow-based MD simulation code as a platform for algorithms for partitioning space into different regions, which can be treated at different levels of theory on a per-timestep basis. Currently implemented algorithms focus on targeting molecules and their solvation layers relevant to electrochemistry. Instead of using built-in forcefields and quantum mechanical methods, the code features a universal interface, which allows for extension to a range of external forcefield programs and programs for quantum mechanical calculations, thus enabling the user to readily implement interfaces to those programs. The purpose of this article is to describe our codes and illustrate its usage. © 2016 Wiley Periodicals, Inc.

Recent Advancements Towards Closing the Gap between Electrocatalysis and Battery Science Communities: The Computational Lithium Electrode and Activity–Stability Volcano Plots

“…Therefore, furtherm odel development in ab initio electrochemistry is called for that facilitates the incorporation of the appliede lectrode potentiald irectly into the underlying calculations, such as in ar ecent contribution of Melander et al, [124] in whichagrand canonical approach was used to investigatee lectrocatalyticsystems at constant ionand electrode potentials. The application of MD simulations [125,126] is required for ap roper sampling of solventc onfigurations, which can be linked to the applied electrode potential. [127] Hence, acombination of DFT calculations and ab initio or classical MD simulations is indispensable for developing novel approaches that go beyondthe CHE approach, [11] as discussed recently by Oberhofer.…”

Adaptive quantum/molecular mechanics: what have we learned, where are we, and where do we go from here?

“…For example, the AP family, Abrupt, Hot‐Spot, and ONIOM‐XS have been implemented in QMMM ( https://comp.chem.umn.edu/qmmm/), Abrupt, Hot‐Spot, ONIOM‐XS, BF, SAP, DAS, and HAMBC in Flex‐MD ( https://www.scm.com/doc/Scripting/FlexMD/FlexMD.html), and N‐adaptive in the AMBER‐Gaussian interface AG–IF . User‐defined simple force‐mixing algorithms are supported in Qreg ( https://github.com/sdohm/Qreg) …”

Yoink: An interaction‐based partitioning API

“…Adaptive QM/MM methods divide a molecular system into QM and MM regions on‐the‐fly based on a user‐defined QM core. They have been used in ion solvation, proton transfer, and electrochemistry simulations . There are three basic partitioning approaches allowing molecules to dynamically switch their identity between QM and MM regions.…”

“…They have been used in ion solvation, [23,24] proton transfer, [25,26] and electrochemistry simulations. [27] There are three basic partitioning approaches allowing molecules to dynamically switch their identity between QM and MM regions. A schematic depiction of these three partitioning methods is shown in Figure 1.…”