Strongly Localized Moiré Exciton in Twisted Homobilayers.

Artificially molding exciton flux is the cornerstone for developing promising excitonic devices. In the emerging hetero/homobilayers, the spatial separated charges prolong exciton lifetimes and create out-plane dipoles, facilitating electrically control exciton flux on a large scale, and the nanoscale periodic moiré potentials arising from twist-angle or/and lattice mismatch can substantially alter exciton dynamics, which are mainly proved in the heterostructures. However, the spatially indirect excitons dynamics in homobilayers without lattice mismatch remain elusive. Here the nonequilibrium dynamics of indirect exciton in homobilayers are systematically investigated. The homobilayers with slightly twist-angle can induce a deep moiré potential (>50 meV) in the energy landscape of indirect excitons, resulting in a strongly localized moiré excitons insulating the transport dynamics from phonons and disorder. These findings provide insights into the exciton dynamics and many-body physics in moiré superlattices modulated energy landscape, with implications for designing excitonic devices operating at room temperature.

Full-space and multi-polarization holograms realized by a non-Hermitian bilayer metasurface.

Multilayer metasurfaces break the mirror symmetry along the path of light propagation, thereby increasing the potential for light manipulation. Herein, a paradigm is proposed that building a non-Hermitian bilayer metasurface, which is composed of two identical, orthogonally oriented, chiral J-shaped Au structures in each layer, allows exceptional points (EPs) to exist in full-space. Specifically, in the reflected half-space that adheres to mirror symmetry, the circularly polarized eigenstates coalesce at the EP, while in the transmission half-space, where mirror symmetry is broken, the linearly polarized eigenstates converge at the EP. By considering the intrinsic property of topologically protected 2π-phase accumulation encircling both EPs, we investigated full-space holography through using circularly polarized light (in reflection half-space) and linearly polarized light (in transmission half-space).

Polarization-Dependent Purcell Enhancement on a Two-Dimensional h-BN/WS2 Light Emitter with a Dielectric Plasmonic Nanocavity.

Integrating two-dimensional (2D) transition-metal dichalcogenides (TMDCs) into dielectric plasmonic nanostructures enables the miniaturization of on-chip nanophotonic devices. Here we report on a high-quality light emitter based on the newly designed 2D h-BN/WS2 heterostructure integrated with an array of TiO2 nanostripes. Different from a traditional strongly coupled system such as the TMDCs/metallic plasmonic nanostructure, we first employ dielectric nanocavities and achieve a Purcell enhancement on the nanoscale at room temperature. Furthermore, we demonstrate that the light emission strength can be effectively controlled by tuning the polarization configuration. Such a polarization dependence meanwhile could be proof of the resonant energy transfer theory of dipole-dipole coupling between TMDCs and a dielectric nanostructure. This work gains experimental and simulated insights into modified spontaneous emission with dielectric nanoplasmonic platforms, presenting a promising route toward practical applications of 2D semiconducting photonic emitters on a silica-based chip.

Single photon counting compressive imaging using a generative model optimized via sampling and transfer learning.

Single photon counting compressive imaging, a combination of single-pixel-imaging and single-photon-counting technology, is provided with low cost and ultra-high sensitivity. However, it requires a long imaging time when applying traditional compressed sensing (CS) reconstruction algorithms. A deep-learning-based compressed reconstruction network refrains iterative computation while achieving efficient reconstruction. This paper proposes a compressed reconstruction network (OGTM) based on a generative model, adding sampling sub-network to achieve joint-optimization of sampling and generation for better reconstruction. To avoid the slow convergence caused by alternating training, initial weights of the sampling and generation sub-network are transferred from an autoencoder. The results indicate that the convergence speed and imaging quality are significantly improved. The OGTM validated on a single-photon compressive imaging system performs imaging experiments on specific and generalized targets. For specific targets, the results demonstrate that OGTM can quickly generate images from few measurements, and its reconstruction is better than the existing compressed sensing recovery algorithms, compensating defects of the generative models in compressed sensing.

Graphene Acoustic Phonon-Mediated Pseudo-Landau Levels Tailoring Probed by Scanning Tunneling Spectroscopy.

Graphene has attracted great interests in various areas including optoelectronics, spintronics, and nanomechanics due to its unique electronic structure, a linear dispersion with a zero bandgap around the Dirac point. Shifts of Dirac cones in graphene creates pseudo-magnetic field, which generates an energy gap and brings a zero-magnetic-field analogue of the quantum Hall effect. Recent studies have demonstrated that graphene pseudo-magnetic effects can be generated by vacancy defects, atom adsorption, zigzag or armchair edges, and external strain. Here, a larger than 100 T pseudo-magnetic field is reported that generated on the step area of graphene; and with the ultrahigh vacuum scanning tunneling microscopy, the observed Landau levels can be effectively tailored by graphene phonons. The zero pseudo-Landau level is suppressed due to the phonon-mediated inelastic tunneling, and this is observed by the scanning tunneling spectroscopy spectrum and confirmed by the Vienna ab initio simulation package calculation, where graphene phonons modulate the flow of tunneling electrons and further mediate pseudo-Landau levels. These observations demonstrate a viable approach for the control of pseudo-Landau levels, which tailors the electronic structure of graphene, and further ignites applications in graphene valley electronics.

Light-Controlled Near-Field Energy Transfer in Plasmonic Metasurface Coupled MoS2 Monolayer.

The energy transfer from plasmonic nanostructures to semiconductors has been extensively studied to enhance light-harvesting and tailor light-matter interactions. In this study, the efficient energy transfer from an Au metasurface to monolayered MoS2 within a near-field coupling regime is reported. The metasurface is designed and fabricated to demonstrate strong photoluminescence (PL) and cathodoluminescence (CL) emission spectra. In the coupled heterostructure of MoS2 with a metasurface, both the Raman shift and absorption spectral intensities of monolayered MoS2 are affected. The spectral profile and PL peak position can be tailored owing to the energy transfer between plasmonic nanostructures and semiconductors. This is confirmed by ultrafast lifetime measurement. A theoretical model of two coupled oscillators is proposed, where the expanded general solutions (EGS) of such a model result in a series of eigenvalues that correspond to the renormalization of energy levels in modulated MoS2. The model can predict the peak shift up to tens of nanometers in hybrid structures and hence provides an alternative method to describe energy transfer between metallic structures and two-dimensional (2D) semiconductors. A viable approach for studying light-matter interactions in 2D semiconductors via near-field energy transfer is presented, which may stimulate the applications of functional nanophotonic devices.

Deep-learning-based single-photon-counting compressive imaging via jointly trained subpixel convolution sampling.

The combination of single-pixel-imaging and single-photon-counting technology can achieve ultrahigh-sensitivity photon-counting imaging. However, its applications in high-resolution and real-time scenarios are limited by the long sampling and reconstruction time. Deep-learning-based compressive sensing provides an effective solution due to its ability to achieve fast and high-quality reconstruction. This paper proposes a sampling and reconstruction integrated neural network for single-photon-counting compressive imaging. To effectively remove the blocking artefact, a subpixel convolutional layer is jointly trained with a deep reconstruction network to imitate compressed sampling. By modifying the forward and backward propagation of the network, the first layer is trained into a binary matrix, which can be applied to the imaging system. An improved deep-reconstruction network based on the traditional Inception network is proposed, and the experimental results show that its reconstruction quality is better than existing deep-learning-based compressive sensing reconstruction algorithms.

Imaging of Plasmonic Chiral Radiative Local Density of States with Cathodoluminescence Nanoscopy.

Chiral light-matter interactions as an emerging aspect of quantum optics enable exceptional physical phenomena and advanced applications in nanophotonics through the nanoscale exploitation of photon-emitter interactions. The chiral radiative properties of quantum emitters strongly depend on the photonic environment, which can be drastically altered by plasmonic nanostructures with a high local density of states (LDOS). Hence, precise knowledge of the chiral photonic environment is essential for manipulating the chirality of light-matter interactions, which requires high resolution chiral characterization techniques. In this work, chiral radiative LDOS distributions of single plasmonic nanostructures that directly govern the chiral radiative spontaneous decay of quantum emitters are imaged at the nanoscale by using cathodoluminescence nanoscopy, enabling precise and highly efficient control of chiral photon emission for chiroptical technologies. Radiative LDOS hot-spots with the chirality larger than 93% are obtained by properly designing chiral plasmonic modes of Au nanoantennas. After fabricating monolayered WSe2 nanodisks (NDs) at chiral radiative LDOS hot-spots and forming ND/Au hybrid nanostructures, the chiral radiative properties of WSe2 NDs are significantly modified, leading to chiral photoluminescence. Our experimental concept and method provide an effective way to characterize and manipulate chiral light-matter interactions at the nanoscale, facilitating future applications in chiral quantum nanophotonics such as single-photon sources and light emission devices.

Improving the Water Oxidation Efficiency with a Light-Induced Electric Field in Nanograting Photoanodes.

Severe charge recombination in solar water-splitting devices significantly limits their performance. To address this issue, we design a frustum of a cone nanograting configuration by taking the hematite and Au-based thin-film photoanode as a model system, which greatly improves the photoelectrochemical water oxidation activity, affording an approximately 10-fold increase in the photocurrent density at 1.23 V versus the reversible hydrogen electrode compared to the planar counterpart. The surface plasmon polariton-induced electric field in hematite plays a dominant role in efficiency enhancement by facilitating charge separation, thus dramatically increasing the incident photon-to-current efficiency (IPCE) by more than 2 orders of magnitude in the near band gap of hematite. And the relatively weak electric field caused by light scattering in the nanograting structure is responsible for the approximate maximum 20-fold increase in IPCE within a broadband wavelength range. Our scalable strategy can be generalized to other solar energy conversion systems.

Self-Learning Perfect Optical Chirality via a Deep Neural Network.

Optical chirality occurs when materials interact differently with light in a specific circular polarization state. Chiroptical phenomena inspire wide interdisciplinary investigations, which require advanced designs to reach strong chirality for practical applications. The development of artificial intelligence provides a new vision for the manipulation of light-matter interaction beyond the theoretical interpretation. Here, we report a self-consistent framework named the Bayesian optimization and convolutional neural network that combines Bayesian optimization and deep convolutional neural network algorithms to calculate and optimize optical properties of metallic nanostructures. Both electric-field distributions at the near field and reflection spectra at the far field are calculated and self-learned to suggest better structure designs and provide possible explanations for the origin of the optimized properties, which enables wide applications for future nanostructure analysis and design.

Near-Field Raman Spectroscopy with Aperture Tips.

In this paper, we review nano-Raman techniques based on aperture scanning near-field optical microscopy (SNOM). Fundamentals of SNOM and aperture-tip-based near-field Raman spectroscopy and their applications in key technical issues, including Raman signal intensity and collection time, are introduced. Recent advances in the tip design are discussed, and applications of the aperture-SNOM-based nano-Raman technique are presented. We attempt to identify the most pressing open questions in this field. We believe that, by improving the power transmission efficiency and combining the local field enhancing technique with the tip-enhanced spectroscopy, the performance of aperture-SNOM can be significantly improved. Its nanometer-scale excitation volume and the consequent low background make the aperture-tip technique feasible for many important samples that cannot be measured by other optical nanospectroscopies.

Reveal and Control of Chiral Cathodoluminescence at Subnanoscale.

Circularly polarized light is crucial for the modern physics research. Highly integrated nanophotonic device further requires the control of circularly polarized light at subnanoscale. Here, we report the tuning of chiral cathodoluminescence (CL) on single Au nanostructure under electron stimulation. The detected CL helicity is found ultrasensitive with the electron impinging position on the structure, and a helicity switch is achieved within a 1.86 nm electron-beam movement, which is applied to construct ternary notation sequence. The proposed configuration provides a delicate platform for the CL helicity control, which opens a way for the future chiral applications at subnanoscale like information coding and quantum communication.

Hybrid Au-Ag Nanostructures for Enhanced Plasmon-Driven Catalytic Selective Hydrogenation through Visible Light Irradiation and Surface-Enhanced Raman Scattering.

Herein, we report the successful application of hybrid Au-Ag nanoparticles (NPs) and nanochains (NCs) in the harvesting of visible light energy for selective hydrogenation reactions. For individual Au@Ag NPs with Au25 cores, the conversion and turnover frequency (TOF) are approximately 8 and 10 times higher than those of Au25 NPs, respectively. Notably, after the self-assembly of the Au@Ag NPs, the conversion and TOF of 1D NCs were approximately 2.5 and 2 times higher than those of isolated Au@Ag NPs, respectively, owing to the coupling of surface plasmon and the increase in the rate at which hot (energetic) electrons are generated with the formation of plasmonic hot spots between NPs. Furthermore, the surface-enhanced Raman scattering (SERS) activity of 1D Au@Ag NCs was strengthened by nearly 2 orders of magnitude.

Valley Pseudospin with a Widely Tunable Bandgap in Doped Honeycomb BN Monolayer.

Valleytronics is a promising paradigm to explore the emergent degree of freedom for charge carriers on the energy band edges. Using ab initio calculations, we reveal that the honeycomb boron nitride (h-BN) monolayer shows a pair of inequivalent valleys in the vicinities of the vertices of hexagonal Brillouin zone even without the protection of the C3 symmetry. The inequivalent valleys give rise to a 2-fold degree of freedom named the valley pseudospin. The valley pseudospin with a tunable bandgap from deep ultraviolet to far-infrared spectra can be obtained by doping h-BN monolayer with carbon atoms. For a low-concentration carbon periodically doped h-BN monolayer, the subbands with constant valley Hall conductance are predicted due to the interaction between the artificial superlattice and valleys. In addition, the valley pseudospin can be manipulated by visible light for high-concentration carbon doped h-BN monolayer. In agreement with our calculations, the circularly polarized photoluminescence spectra of the B0.92NC2.44 sample show a maximum valley-contrasting circular polarization of 40% and 70% at room temperature and 77 K, respectively. Our work demonstrates a class of valleytronic materials with a controllable bandgap.

Magnetic plasmonic Fano resonance at optical frequency.

Plasmonic Fano resonances are typically understood and investigated assuming electrical mode hybridization. Here we demonstrate that a purely magnetic plasmon Fano resonance can be realized at optical frequency with Au split ring hexamer nanostructure excited by an azimuthally polarized incident light. Collective magnetic plasmon modes induced by the circular electric field within the hexamer and each of the split ring can be controlled and effectively hybridized by designing the size and orientation of each ring unit. With simulated results reproducing the experiment, our suggested configuration with narrow line-shape magnetic Fano resonance has significant potential applications in low-loss sensing and may serves as suitable elementary building blocks for optical metamaterials.

Broadband photodetection in a microfiber-graphene device.

We propose and experimentally demonstrate a microfiber-graphene device. Owing to the interaction between the graphene film and the evanescent field leaked from the microfiber, the hybrid photoconductive device exhibits a high photoresponse. A maximum photocurrent responsivity of ~2.81 mA/W is achieved in the telecommunication band. A nearly flat photoresponse spectrum within broad operational band ranging from 1500 nm to 1600 nm is also obtained as a consequence of the dispersionless and flat absorption of graphene. These results show that the proposed photocurrent generation device could provide an effective solution for broadband photodetection.

Active tunable absorption enhancement with graphene nanodisk arrays.

If not for its inherently weak optical absorption at visible and infrared wavelengths, graphene would show exceptional promise for optoelectronic applications. Here we show that by nanopatterning a graphene layer into an array of closely packed graphene nanodisks, its absorption efficiency can be increased from less than 3% to 30% in the infrared region of the spectrum. We examine the dependence of the enhanced absorption on nanodisk size and interparticle spacing. By incorporating graphene nanodisk arrays into an active device, we demonstrate that this enhanced absorption efficiency is voltage-tunable, indicating strong potential for nanopatterned graphene as an active medium for infrared electro-optic devices.

Evolution of light-induced vapor generation at a liquid-immersed metallic nanoparticle.

When an Au nanoparticle in a liquid medium is illuminated with resonant light of sufficient intensity, a nanometer scale envelope of vapor-a "nanobubble"-surrounding the particle, is formed. This is the nanoscale onset of the well-known process of liquid boiling, occurring at a single nanoparticle nucleation site, resulting from the photothermal response of the nanoparticle. Here we examine bubble formation at an individual metallic nanoparticle in detail. Incipient nanobubble formation is observed by monitoring the plasmon resonance shift of an individual, illuminated Au nanoparticle, when its local environment changes from liquid to vapor. The temperature on the nanoparticle surface is monitored during this process, where a dramatic temperature jump is observed as the nanoscale vapor layer thermally decouples the nanoparticle from the surrounding liquid. By increasing the intensity of the incident light or decreasing the interparticle separation, we observe the formation of micrometer-sized bubbles resulting from the coalescence of nanoparticle-"bound" vapor envelopes. These studies provide the first direct and quantitative analysis of the evolution of light-induced steam generation by nanoparticles from the nanoscale to the macroscale, a process that is of fundamental interest for a growing number of applications.

ZFC3H1 as an Indicator of Poor Prognosis in Hepatocellular Carcinoma: Bioinformatic Analysis and Experimental Verification.

BACKGROUND: Zinc finger C3H1-type containing (ZFC3H1) might regulate RNA processes. However, research lacks the prognostic value of ZFC3H1 in hepatocellular carcinoma (HCC). METHODS: The study analyzed ZFC3H1 expression in HCC cells and its correlation with patient prognosis using transcriptomics, immunohistochemistry, and quantitative real-time reverse transcription PCR, as well as single-cell RNA expression data. Additionally, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were used to investigate the potential ZFC3H1-related cellular functions and signaling pathways. The impact of ZFC3H1 expression on the tumor microenvironment and tumor mutational burden (TMB) was assessed using the ESTIMATE algorithm. Cell-based assays, including cell counting kit 8, proliferation, colony formation, cell cycle, wound healing, and Transwell assays, were conducted to evaluate the influence of ZFC3H1 on hepatocellular carcinoma proliferation and migration. RESULTS: ZFC3H1 is upregulated in HCC and linked to tumor progression. High ZFC3H1 expression is a prognostic risk factor for HCC, according to Kaplan-Meier and Cox regression analyses. ESTIMATE analysis suggested that ZFC3H1 reduces immune cell infiltration and increases the TMB. Patients with low ZFC3H1 expression might respond better to immunotherapy. High ZFC3H1 expression is associated with increased half-maximal inhibitory concentration (IC50) of sorafenib. Functional experiments demonstrated that reducing ZFC3H1 expression inhibited HCC cell proliferation and migration. CONCLUSION: ZFC3H1 is upregulated in HCC, promoting the proliferation and migration of liver cancer cells, impacting the prognosis of HCC patients and the effectiveness of immunotherapy. ZFC3H1 might serve as a therapeutic target and biomarker for HCC.

Pharmacological targeting cGAS/STING/NF-κB axis by tryptanthrin induces microglia polarization toward M2 phenotype and promotes functional recovery in a mouse model of spinal cord injury.

ABSTRACT: The M1/M2 phenotypic shift of microglia after spinal cord injury plays an important role in the regulation of neuroinflammation during the secondary injury phase of spinal cord injury. Regulation of shifting microglia polarization from M1 (neurotoxic and proinflammatory type) to M2 (neuroprotective and anti-inflammatory type) after spinal cord injury appears to be crucial. Tryptanthrin possesses an anti-inflammatory biological function. However, its roles and the underlying molecular mechanisms in spinal cord injury remain unknown. In this study, we found that tryptanthrin inhibited microglia-derived inflammation by promoting polarization to the M2 phenotype in vitro. Tryptanthrin promoted M2 polarization through inactivating the cGAS/STING/NF-κB pathway. Additionally, we found that targeting the cGAS/STING/NF-κB pathway with tryptanthrin shifted microglia from the M1 to M2 phenotype after spinal cord injury, inhibited neuronal loss, and promoted tissue repair and functional recovery in a mouse model of spinal cord injury. Finally, using a conditional co-culture system, we found that microglia treated with tryptanthrin suppressed endoplasmic reticulum stress-related neuronal apoptosis. Taken together, these results suggest that by targeting the cGAS/STING/NF-κB axis, tryptanthrin attenuates microglia-derived neuroinflammation and promotes functional recovery after spinal cord injury through shifting microglia polarization to the M2 phenotype.