plasmonX: an Open-Source Code for Nanoplasmonics

TL;DR

PlasmonX addresses the challenge of accurately simulating plasmonic response in complex nanosystems by unifying atomistic ($ω$FQ and $ω$FQFμ) and continuum boundary element method (BEM) PCM approaches. It provides a Fortran core with a Python interface and multiple solvers, including a memory-efficient on-the-fly GMRES, enabling scalable simulations from hundreds to millions of atoms, complemented by a post-processing suite for induced densities and fields. The open-source release demonstrates capabilities on noble metal nanoalloys and graphene-based structures, validating physical trends and hotspot localization in dimers. Looking ahead, the authors plan real-time dynamics, multiscale embedding, mixed implicit/explicit strategies, and fast multipole methods to further extend scalability and applicability.

Abstract

We present the first public release of plasmonX, a novel open-source code for simulating the plasmonic response of complex nanostructures. The code supports both fully atomistic and implicit descriptions of nanomaterials. In particular, it employs the frequency-dependent fluctuating charges ($ω$FQ) and dipoles ($ω$FQF$μ$) models to describe the response properties of atomistic structures, including simple and $d$-metals, graphene-based structures, and multi-metal nanostructures. For implicit representations, the Boundary Element Method is implemented in both the dielectric polarizable continuum model (DPCM) and integral equation formalism (IEF-PCM) variants. The distribution also includes a post-processing module that enables analysis of electric field-induced properties such as charge density and electric field patterns.

Figures (5)

• Figure 1: Nanostructure morphologies that can be created by plasmonX through the GEOM interface.
• Figure 2: Elapsed time required to solve the $\omega$FQ linear system as a function of the number of atoms for selected graphene disks at the plasmon resonance frequency by using inversion and iterative (on the fly) algorithms implemented in plasmonX.
• Figure 3: Speedup of the $\omega$FQF$\mu$ linear system solution using the iterative on-the-fly algorithm as a function of the OMP threads.
• Figure 4: (a) Graphical depiction of spherical Ag-Au nanoalloys. (b) $\omega$FQF$\mu$ plasmon resonance frequency (PRF) as a function of Au percentage.
• Figure 5: (a) Graphical depiction of Au$_{561}$ dimer; (b-d) $\omega$FQF$\mu$ absorption cross section (b), induced density (c), and enhanced electric field computed at the PRF (2.28 eV) using a polarization field along the $x$ axis.