Tuning the Growth of Chiral Gold Nanoparticles Through Rational Design of a Chiral Molecular Inducer.

The bottom-up production of chiral gold nanomaterials holds great potential for the advancement of biosensing and nano-optics, among other applications. Reproducible preparations of colloidal nanomaterials with chiral morphology have been reported, using cosurfactants or chiral inducers such as thiolated amino acids. However, the underlying growth mechanisms for these nanomaterials remain insufficiently understood. We introduce herein a purposely devised chiral inducer, a cysteine modified with a hydrophobic chain, as a versatile chiral inducer. The amphiphilic and chiral features of this molecule provide control over the chiral morphology and the chiroptical signature of the obtained nanoparticles by simply varying the concentration of chiral inducer. These results are supported by circular dichroism and electromagnetic modeling as well as electron tomography to analyze structural evolution at the facet scale. Our observations suggest complex roles for the factors involved in chiral synthesis: the chemical nature of the chiral inducers and the influence of cosurfactants.

High-Throughput Morphological Chirality Quantification of Twisted and Wrinkled Gold Nanorods.

Chirality in gold nanostructures offers an exciting opportunity to tune their differential optical response to left- and right-handed circularly polarized light, as well as their interactions with biomolecules and living matter. However, tuning and understanding such interactions demands quantification of the structural features that are responsible for the chiral behavior. Electron tomography (ET) enables structural characterization at the single-particle level and has been used to quantify the helicity of complex chiral nanorods. However, the technique is time-consuming and consequently lacks statistical value. To address this issue, we introduce herein a high-throughput methodology that combines images acquired by secondary electron-based electron beam-induced current (SEEBIC) with quantitative image analysis. As a result, the geometric chirality of hundreds of nanoparticles can be quantified in less than 1 h. When combining the drastic gain in data collection efficiency of SEEBIC with a limited number of ET data sets, a better understanding of how the chiral structure of individual chiral nanoparticles translates into the ensemble chiroptical response can be reached.

Chiral Seeded Growth of Gold Nanorods Into Fourfold Twisted Nanoparticles with Plasmonic Optical Activity.

A robust and reproducible methodology to prepare stable inorganic nanoparticles with chiral morphology may hold the key to the practical utilization of these materials. An optimized chiral growth method to prepare fourfold twisted gold nanorods is described herein, where the amino acid cysteine is used as a dissymmetry inducer. Four tilted ridges are found to develop on the surface of single-crystal nanorods upon repeated reduction of HAuCl4 , in the presence of cysteine as the chiral inducer and ascorbic acid as a reducing agent. From detailed electron microscopy analysis of the crystallographic structures, it is proposed that the dissymmetry results from the development of chiral facets in the form of protrusions (tilted ridges) on the initial nanorods, eventually leading to a twisted shape. The role of cysteine is attributed to assisting enantioselective facet evolution, which is supported by density functional theory simulations of the surface energies, modified upon adsorption of the chiral molecule. The development of R-type and S-type chiral structures (small facets, terraces, or kinks) would thus be non-equal, removing the mirror symmetry of the Au NR and in turn resulting in a markedly chiral morphology with high plasmonic optical activity.

Quantification of the Helical Morphology of Chiral Gold Nanorods.

Chirality in inorganic nanoparticles and nanostructures has gained increasing scientific interest, because of the possibility to tune their ability to interact differently with left- and right-handed circularly polarized light. In some cases, the optical activity is hypothesized to originate from a chiral morphology of the nanomaterial. However, quantifying the degree of chirality in objects with sizes of tens of nanometers is far from straightforward. Electron tomography offers the possibility to faithfully retrieve the three-dimensional morphology of nanomaterials, but only a qualitative interpretation of the morphology of chiral nanoparticles has been possible so far. We introduce herein a methodology that enables us to quantify the helicity of complex chiral nanomaterials, based on the geometrical properties of a helix. We demonstrate that an analysis at the single particle level can provide significant insights into the origin of chiroptical properties.

Photothermal Circular Dichroism Measurements of Single Chiral Gold Nanoparticles Correlated with Electron Tomography.

Chemically synthesized metal nanoparticles with morphological chiral features are known to exhibit strong circular dichroism. However, we still lack understanding of the correlation between morphological and chiroptical features of plasmonic nanoparticles. To shed light on that question, single nanoparticle experiments are required. We performed photothermal circular dichroism measurements of single chiral and achiral gold nanoparticles and correlated the chiroptical response to the 3D morphology of the same nanoparticles retrieved by electron tomography. In contrast to an ensemble measurement, we show that individual particles within the ensemble display a broad distribution of strength and handedness of circular dichroism signals. Whereas obvious structural chiral features, such as helical wrinkles, translate into chiroptical ones, nanoparticles with less obvious chiral morphological features can also display strong circular dichroism signals. Interestingly, we find that even seemingly achiral nanoparticles can display large g-factors. The origin of this circular dichroism signal is discussed in terms of plasmonics and other potentially relevant factors.

Morphological and Optical Transitions during Micelle-Seeded Chiral Growth on Gold Nanorods.

Chiral plasmonics is a rapidly developing field where breakthroughs and unsolved problems coexist. We have recently reported binary surfactant-assisted seeded growth of chiral gold nanorods (Au NRs) with high chiroptical activity. Such a seeded-growth process involves the use of a chiral cosurfactant that induces micellar helicity, in turn driving the transition from achiral to chiral Au NRs, from both the morphological and the optical points of view. We report herein a detailed study on both transitions, which reveals intermediate states that were hidden so far. The correlation between structure and optical response is carefully analyzed, including the (linear and CD) spectral evolution over time, electron tomography, the impact of NR dimensions on their optical response, the variation of the absorption-to-scattering ratio during the evolution from achiral to chiral Au NRs, and the near-field enhancement related to chiral plasmon modes. Our findings provide further understanding of the growth process of chiral Au NRs and the associated optical changes, which will facilitate further study and applications of chiral nanomaterials.

Deep learning-based denoising for improved dose efficiency in EDX tomography of nanoparticles.

The combination of energy-dispersive X-ray spectroscopy (EDX) and electron tomography is a powerful approach to retrieve the 3D elemental distribution in nanomaterials, providing an unprecedented level of information for complex, multi-component systems, such as semiconductor devices, as well as catalytic and plasmonic nanoparticles. Unfortunately, the applicability of EDX tomography is severely limited because of extremely long acquisition times and high electron irradiation doses required to obtain 3D EDX reconstructions with an adequate signal-to-noise ratio. One possibility to address this limitation is intelligent denoising of experimental data using prior expectations about the objects of interest. Herein, this approach is followed using the deep learning methodology, which currently demonstrates state-of-the-art performance for an increasing number of data processing problems. Design choices for the denoising approach and training data are discussed with a focus on nanoparticle-like objects and extremely noisy signals typical for EDX experiments. Quantitative analysis of the proposed method demonstrates its significantly enhanced performance in comparison to classical denoising approaches. This allows for improving the tradeoff between the reconstruction quality, acquisition time and radiation dose for EDX tomography. The proposed method is therefore especially beneficial for the 3D EDX investigation of electron beam-sensitive materials and studies of nanoparticle transformations.