arXiv subjects

Gengping Jiang

Publications and source records attributed to Gengping Jiang.

3 recordsLinked to original sources

arXiv2024

Beyond Dielectrics: Interfacial Water Polarization Governs Graphene-Based Electrochemical Interfaces

Water molecules are traditionally regarded as passive dielectric media in electrochemical systems. In this work, we challenge this conventional perspective using molecular dynamics simulations and theoretical analysis. We show that interfacial water is polarized differently from bulk water and effectively screens the electrostatic potential between ions and the surface. This goes beyond the classic electric double layer (EDL) model, which treated water as merely a passive dielectric. The observed overscreening occurs because a significant portion of water polarization directly responds to the graphene surface, in addition to screening the electrostatic interactions between ions and charged surfaces. Furthermore, we reveal that this surface-induced polarization of interfacial water governs the electric potential distribution and EDL capacitance, and can even invert the electrode surface potential polarity, overriding the contribution of ions. These molecular-level insights lead to a revised EDL model that more accurately describes the electric and chemical potential distributions in the interfacial EDL regions.

physics.chem-ph↗

arXiv2022

A Simple and Efficient Lattice Summation Method for Metallic Electrodes in Constant Potential Molecular Dynamics Simulation

The constant potential molecular dynamics simulation method proposed by Siepmann and Sprik and reformulated later by Reed (SR-CPM) has been widely employed to investigate the metallic electrolyte/electrode interfaces, especially for conducting nanochannels with complex connectivity, *e.g.*, carbide-derived carbon or graphene-assembled membrane. This work makes substantial extensions of this seminal SR-CPM approach. First, we introduce two numerical techniques to determine electrode atom charges with an order of magnitude improvement in computational efficiency compared with those widely employed methods. The first numerical technique dramatically accelerates the to calculation of the Ewald interaction matrix $\mathbf{E}$, which takes advantage of the existing highly optimised electrostatic codes. The second technique introduces a new preconditioning technique in the conjugate gradient method to considerably increase the computational efficiency of a linear equation system that determines electrode atomic charges. Our improved SR-CPM implemented in the LAMMPS package can handle extra-large systems, *e.g.*, over 8.1 million electrode atoms. Second, after demonstrating the importance of the electroneutrality constraint, we propose a two-step method to enforce electroneutrality in the following post-treatment step, applicable for matrix and iterative techniques. Third, we propose a solid theoretical analysis for the adjustable parameter $α_i$ (namely the atomic Hubbard-U $U_i^0$), which is arbitrarily selected in many SR-CPM simulation practices. We proposed that the optimised $α_i$ or $U_i^0$ should compensate for the electrical potential/energy discrepancy between the discrete atomistic model and the continuum limit. The analytical and optimal $α_i^0$ values are derived for a series of 2D materials.

physics.chem-ph↗

arXiv2018

Efficient O($N$) divide-conquer method with localized natural orbitals

An efficient O($N$) divide-conquer (DC) method based on localized natural orbitals (LNOs) is presented for large-scale density functional theories (DFT) calculations of gapped and metallic systems. The LNOs are non-iteratively calculated by a low-rank approximation via a local eigendecomposition of a projection operator for the occupied space. Introducing LNOs to represent the long range region of a truncated cluster reduces the computational cost of the DC method while keeping computational accuracy. A series of benchmark calculations and high parallel efficiency in a multilevel parallelization clearly demonstrate that the O($N$) method enables us to perform large-scale simulations for a wide variety of materials including metals with sufficient accuracy in accordance with development of massively parallel computers.

physics.comp-ph↗