Nanostructures of some metals can sustain light-driven electron oscillations called localized surface plasmon resonances, or LSPRs, that give rise to absorption, scattering, and local electric field enhancement. Their resonant frequency is dictated by the nanoparticle (NP) shape and size, fueling much research geared toward discovery and control of new structures. LSPR properties also depend on composition; traditional, rare, and expensive noble metals (Ag, Au) are increasingly eclipsed by earth-abundant alternatives, with Mg being an exciting candidate capable of sustaining resonances across the ultraviolet, visible, and near-infrared spectral ranges. Here, we report numerical predictions and experimental verifications of a set of shapes based on Mg NPs displaying various twinning patterns including (101̅1), (101̅2), (101̅3), and (112̅1), that create tent-, chair-, taco-, and kite-shaped NPs, respectively. These are strikingly different from what is obtained for typical plasmonic metals because Mg crystallizes in a hexagonal close packed structure, as opposed to the cubic Al, Cu, Ag, and Au. A numerical survey of the optical response of the various structures, as well as the effect of size and aspect ratio, reveals their rich array of resonances, which are supported by single-particle optical scattering experiments. Further, corresponding numerical and experimental studies of the near-field plasmon distribution via scanning transmission electron microscopy electron-energy loss spectroscopy unravels a mode nature and distribution that are unlike those of either hexagonal plates or cylindrical rods. These NPs, made from earth-abundant Mg, provide interesting ways to control light at the nanoscale across the ultraviolet, visible, and near-infrared spectral ranges.

Nanoparticles of plasmonic materials can sustain oscillations of their free electron density, called localized surface plasmon resonances (LSPRs), giving them a broad range of potential applications. Mg is an earth-abundant plasmonic material attracting growing attention owing to its ability to sustain LSPRs across the ultraviolet, visible, and near-infrared wavelength range. Tuning the LSPR frequency of plasmonic nanoparticles requires precise control over their size and shape; for Mg, this control has previously been achieved using top-down fabrication or gas-phase methods, but these are slow and expensive. Here, we systematically probe the effects of reaction parameters on the nucleation and growth of Mg nanoparticles using a facile and inexpensive colloidal synthesis. Small NPs of 80 nm were synthesized using a low reaction time of 1 min and ∼100 nm NPs were synthesized by decreasing the overall reaction concentration, replacing the naphthalene electron carrier with biphenyl or using metal salt additives of FeCl 3 or NiCl 2 at longer reaction times of 17 h. Intermediate sizes up to 400 nm were further selected via the overall reaction concentration or using other metal salt additives with different reduction potentials. Significantly larger particles of over a micrometer were produced by reducing the reaction temperature and, thus, the nucleation rate. We showed that increasing the solvent coordination reduced Mg NP sizes, while scaling up the reaction reduced the mixing efficiency and produced larger NPs. Surprisingly, varying the relative amounts of Mg precursor and electron carrier had little impact on the final NP sizes. These results pave the way for the large-scale use of Mg as a low-cost and sustainable plasmonic material.

The growing interest in plasmonic nanoparticles and their increasingly diverse applications is fuelled by the ability to tune properties via shape control, promoting intense experimental and theoretical research. Such shapes are dominated by geometries that can be described by the kinetic Wulff construction such as octahedra, thin triangular platelets, bipyramids, and decahedra, to name a few. Shape is critical in dictating the optical properties of these nanoparticles, in particular their localized surface plasmon resonance behavior, which can be modeled numerically. One challenge of the various available computational techniques is the representation of the nanoparticle shape. Specifically, in the discrete dipole approximation, a particle is represented by discretizing space via an array of uniformly distributed points-dipoles; this can be difficult to construct for complex shapes including those with multiple crystallographic facets, twins, and core–shell particles. Here, we describe a standalone user-friendly graphical user interface (GUI) that uses both kinetic and thermodynamic Wulff constructions to generate a dipole array for complex shapes, as well as the necessary input files for DDSCAT-based numerical approaches. Examples of the use of this GUI are described through three case studies spanning different shapes, compositions, and shell thicknesses. Key advances offered by this approach, in addition to simplicity, are the ability to create crystallographically correct structures and the addition of a conformal shell on complex shapes.

This is a repository copy of Decoration of plasmonic Mg nanoparticles by partial galvanic replacement.

Unlike in the bulk, at the nanoscale shape dictates properties. The imperative to understand and predict nanocrystal shape led to the development, over several decades, of a large number of mathematical models and, later, their software implementations. In this review, the various mathematical approaches used to model crystal shapes are first overviewed, from the century-old Wulff construction to the year-old (2020) approach to describe supported twinned nanocrystals, together with a discussion and disambiguation of the terminology. Then, the multitude of published software implementations of these Wulff-based shape models are described in detail, describing their technical aspects, advantages and limitations. Finally, a discussion of the scientific applications of shape models to either predict shape or use shape to deduce thermodynamic and/or kinetic parameters is offered, followed by a conclusion. This review provides a guide for scientists looking to model crystal shape in a field where ever-increasingly complex crystal shapes and compositions are required to fulfil the exciting promises of nanotechnology.