Kernel-Level Constant-Potential Molecular Dynamics in GROMACS
Sheng Bi, Mathieu Salanne, Jun Cheng, Guang Feng
Abstract
How charge rearranges within an electrode shapes the behavior of batteries, supercapacitors, and other electrochemical devices. Molecular simulations can capture this response by allowing the charge on each electrode atom to adjust to its surroundings, but repeatedly calculating these charges adds substantial computational cost. We present an open-source implementation of the constant-potential method in GROMACS that integrates these calculations into the program's optimized CPU and GPU routines. Comparisons with established codes validate the electrode charges, while charging, voltammetry, and impedance simulations demonstrate the response to changing electrical conditions. The implementation also supports electrodes that move or deform and models of finite metallic screening and electron spillover. In a pair of charged carbon nanotubes, allowing charge to move away from the facing surfaces reduces the repulsive force at contact by about half at an intermediate charge and keeps the pair bound where a uniform-charge model opens within the simulated time. These capabilities make the electrical response of electrodes accessible within GROMACS for studies of interfacial structure, charging dynamics, and electrode motion.
Create a lesson
Related papers
The RAS-CCSD model, with applications for open-shell molecules
Sarai Dery Folkestad
Tersoff-NN: Hybrid Machine-Learned Bond-Order Extension of the Tersoff Potential
Yusuke Nishimura, Sho Kubota, Kotaro Takematsu et al.
Learning Electron Density with Virtual Atoms for Transferable Atomistic Representations
Yuzhi Liu, Xinzijian Liu, Chengqian Zhang et al.
UGME: A python package for non-Markovian protein folding dynamics
Anthony J. Dominic, Bertram Cham, Andrés Montoya-Castillo
Spin Migration in the Argon Dimer
Stefanos Carlström, Serguei Patchkovskii, Misha Yu Ivanov
Accuracy of Vibrational Properties of Machine-Learning Force Fields for Molecular Crystal Transformations
Natalia Goncharova, Oskar Schweighofer, Johannes Hoja