Electrical Detection of Single Graphene Plasmons

Deep learning: an efficient method for plasmonic design of geometric nanoparticles

Plasmons of noble metal nanoparticles have played an important role in energy transfer research, biomedical sensing, drug preparation and photocatalysis in recent years. The scattering spectra of nanoparticles are dramatically affected by numerous complex parameters, such as morphology, material, and volumes, making the parameters design a necessary step before the experiment. However, the plasmonic design is limited by several difficulties, such as the high degree of freedom, expensive trial and error costs. Herein, a plasmonic design method based on dual strategy deep learning is proposed, which can provide the design proposals according to the required spectrum. To make the model closer to the real experimental situation, the boundary element method was used to build a scattering spectra dataset of geometric nanoparticles (>1200 000 samples). Driven by the above data, the artificial intelligence (AI) model learns the relationship between spectral features and design parameters. Then, the performance statistics of the model were implemented from multiple dimensions, and a high design precision of over 90% was achieved in testing cases (testing samples >120 000). Moreover, to verify the realizability of the proposed model, the scattering spectra of nanoparticles designed by AI were constructed using a dark-field microscope system. The experimental results showed that the deviation between the target and the actual spectra was very small and within the acceptable range. This proves the realizability of the AI model proposed in this paper, and sheds light on the application of AI in plasmonic design.

Gate-Tunable Optical Nonlinearities and Extinction in Graphene/LaAlO3/SrTiO3 Nanostructures

We explore the ultrafast optical response of graphene subjected to intense (∼10⁶ V/cm) local (∼10 nm) electric fields. Nanoscale gating of graphene is achieved using a voltage-biased, SrTiO₃-based conductive nanowire junction "written" directly under the graphene and isolated from it by an insulating ultrathin (<2 nm) LaAlO₃ barrier. Upon illumination with ultrafast visible-to-near-infrared (VIS-NIR) light pulses, the local field from the nanojunction creates a strong gate-tunable second-order nonlinearity in the graphene and produces a substantial difference-frequency (DFG) and sum-frequency generation (SFG) response detected by the nanojunction. Spectrally sharp, gate-tunable extinction features (>99.9%) are observed in the VIS-NIR and SFG spectral ranges, in parameter regimes that are positively correlated with the enhanced nonlinear response. The observed graphene-light interaction and nonlinear response are of fundamental interest and open the way for future exploitation in graphene-based optical devices such as phase shifters, modulators, and nanoscale THz sources.

Thermal manipulation of plasmons in atomically thin films

Nanoscale photothermal effects enable important applications in cancer therapy, imaging and catalysis. These effects also induce substantial changes in the optical response experienced by the probing light, thus suggesting their application in all-optical modulation. Here, we demonstrate the ability of graphene, thin metal films, and graphene/metal hybrid systems to undergo photothermal optical modulation with depths as large as >70% over a wide spectral range extending from the visible to the terahertz frequency domains. We envision the use of ultrafast pump laser pulses to raise the electron temperature of graphene during a picosecond timescale in which its mid-infrared plasmon resonances undergo dramatic shifts and broadenings, while visible and near-infrared plasmons in the neighboring metal films are severely attenuated by the presence of hot graphene electrons. Our study opens a promising avenue toward the active photothermal manipulation of the optical response in atomically thin materials with potential applications in ultrafast light modulation.

Photoninduced charge redistribution of graphene determined by edge structures in the infrared region

By using the ab initio density-functional theory method, we investigated the charge redistribution of monolayer graphene with ZigZag and/or ArmChair edges upon infrared excitation. The photoinduced charge redistribution is strongly dependent on edge types. The priority of electrons transfer has been revealed by charge density difference. To further investigate the influence of edge types on optical properties, the dielectric constants and absorption coefficient of graphene with various edge types have been calculated. The edge types have a non-negligible influence on optical properties of graphene, and the Zigzag edge graphene owns stronger optical absorption in infrared region. Our results are potentially beneficial for designing graphene nanodevices in the infrared region.

Efficient electrical detection of mid-infrared graphene plasmons at room temperature

Optical excitation and subsequent decay of graphene plasmons can produce a significant increase in charge-carrier temperature. An efficient method to convert this temperature elevation into electrical signals can enable important mid-infrared applications. However, the modest thermoelectric coefficient and weak temperature dependence of carrier transport in graphene hinder this goal. Here, we demonstrate mid-infrared graphene detectors consisting of arrays of plasmonic resonators interconnected by quasi-one-dimensional nanoribbons. Localized barriers associated with disorder in the nanoribbons produce a dramatic temperature dependence of carrier transport, thus enabling the electrical detection of plasmon decay in the nearby graphene resonators. Our device has a subwavelength footprint of 5 × 5 μm² and operates at 12.2 μm with an external responsivity of 16 mA W^-1 and a low noise-equivalent power of 1.3 nW Hz^-1/2 at room temperature. It is fabricated using large-scale graphene and possesses a simple two-terminal geometry, representing an essential step towards the realization of an on-chip graphene mid-infrared detector array.

Photothermal Engineering of Graphene Plasmons

Nanoscale photothermal sources find important applications in theranostics, imaging, and catalysis. In this context, graphene offers a unique suite of optical, electrical, and thermal properties, which we exploit to show self-consistent active photothermal modulation of its nanoscale response. In particular, we predict the existence of plasmons confined to the optical landscape tailored by continuous-wave external-light pumping of homogeneous graphene. This result relies on the high electron temperatures achievable in optically pumped clean graphene while its lattice remains near ambient temperature. Our study opens a new avenue toward the active optical control of the nanophotonic response in graphene with potential application in photothermal devices.

Plasmonic Nano-Oven by Concatenation of Multishell Photothermal Enhancement

Metallodielectric multishell nanoparticles are capable of hosting collective plasmon oscillations distributed among different metallic layers, which result in large near-field enhancement at specific regions of the structure, where light absorption is maximized. We exploit this capability of multishell nanoparticles, combined with thermal boundary resistances and spatial tailoring of the optical near fields, to design plasmonic nano-ovens capable of achieving high temperatures at the core region using moderate illumination intensities. We find a large optical intensity enhancement of ∼10⁴ over a relatively broad core region with a simple design consisting of three metal layers. This provides an unusual thermal environment, which together with the high pressures of ∼10⁵ atm produced by concatenated curved layers holds great potential for exploring physical and chemical processes under extreme optical/thermal/pressure conditions in confined nanoscale spaces, while the outer surface of the nano-oven is close to ambient conditions.