Showing papers by "Zheyu Fang published in 2023"

Chiral detection of biomolecules based on reinforcement learning

Abstract: Chirality plays an important role in biological processes, and enantiomers often possess similar physical properties and different physiologic functions. In recent years, chiral detection of enantiomers become a popular topic. Plasmonic metasurfaces enhance weak inherent chiral effects of biomolecules, so they are used in chiral detection. Artificial intelligence algorithm makes a lot of contribution to many aspects of nanophotonics. Here, we propose a nanostructure design method based on reinforcement learning and devise chiral nanostructures to distinguish enantiomers. The algorithm finds out the metallic nanostructures with a sharp peak in circular dichroism spectra and emphasizes the frequency shifts caused by nearfield interaction of nanostructures and biomolecules. Our work inspires universal and efficient machine-learning methods for nanophotonic design.

A novel sol-gel strategy for constructing wood fibers and aramid nanofiber nanocomposite with strong, tough and recyclable properties

Abstract: Recently, biomass-based materials derived from wood processing residues have been developed to resolve the white pollution. However, the poor mechanical strength, weak water resistance, and non-recyclability still limit their practical applications. Aramid nanofiber (ANF) is a promising reinforcement due to the unique structural characteristics and exceptional mechanical properties. Here, a high-performance wood fibers-based nanocomposite was assembled based on chemically-modified wood fiber (CWF) and ANF via a sol-gel strategy with the solvent exchange. The dynamic noncovalent cross-linking with 3D reticular networks between CWF and ANF endow the as-prepared film with high tensile strength of 591.96 ± 11.05 MPa, high toughness of 38.68 ± 2.15 MJ/m3, and excellent solvent resistance. Moreover, the CWF-ANF gel can effectively repair the fractured CWF-ANF film under heating and maintain competitive mechanical properties after several dissolution-reconstruction, which shows the fascinating sustainability potential. Simultaneously, the as-prepared film is considered as a strong substrate to advance excellently conductive and anti-counterfeiting composite with double-layered structures. This effective strategy provides a novel pathway to reuse plant waste resources with competitive mechanical properties and high value-added utilization.

Electron-Induced Chirality-Selective Routing of Valley Photons via Metallic Nanostructure.

Abstract: Valleytronics in two-dimensional transition metal dichalcogenides has raised a great impact in nanophotonic information processing and transport as it provides the pseudospin degree of freedom for carrier control. The imbalance of carrier occupation in inequivalent valleys can be achieved by external stimulations such as helical light and electric field. With metasurfaces, it is feasible to separate the valley exciton in real space and momentum space, which is significant for logical nanophotonic circuits. However, the control of valley-separated far-field emission by a single nanostructure is rarely reported, despite the fact that it is crucial for subwavelength research of valley-dependent directional emission. Here, we demonstrate that the electron beam permits the chirality-selective routing of valley photons in a monolayer WS2 with Au nanostructures. The electron beam can locally excite valley excitons and regulate the coupling between excitons and nanostructures, hence controlling the interference effect of multipolar electric modes in nanostructures. Therefore, the separation degree can be modified by steering the electron beam, exhibiting the capability of subwavelength control of valley separation. Our work provides a novel method to create and resolve the variation of valley emission distribution in momentum space, paving the way for the design of future nanophotonic integrated devices. This article is protected by copyright. All rights reserved.

Self-design of arbitrary polarization-control waveplate via deep neural networks

Abstract: The manipulation of polarization states beyond the optical limit presents advantages in various applications. Considerable progress has been made in the design of meta-waveplates for on-demand polarization transformation, realized by numerical simulations and parameter sweep methodologies. However, due to the limited freedom in these classical strategies, particular challenges arise from the emerging requirement for multiplex optical devices and multidimensional manipulation of light, which urge for a large number of different nanostructures with great polarization control capability. Here, we demonstrate a set of self-designed arbitrary wave plates with a high polarization conversion efficiency. We combine Bayesian optimization and deep neural networks to design perfect half- and quarter-waveplates based on metallic nanostructures, which experimentally demonstrate excellent polarization control functionalities with the conversion ratios of 85% and 90%. More broadly, we develop a comprehensive wave plate database consisting of various metallic nanostructures with high polarization conversion efficiency, accompanying a flexible tuning of phase shifts (0–2 π ) and group delays (0–10 fs), and construct an achromatic metalens based on this database. Owing to the versatility and excellent performance, our self-designed wave plates can promote the performance of multiplexed broadband metasurfaces and find potential applications in compact optical devices and polarization division multiplexing optical communications.

Scalable Manufacturing of Environmentally Stable All-Solid-State Plant Protein-Based Supercapacitors with Optimal Balance of Capacitive Performance and Mechanically Robust.

Abstract: The development of advanced biomaterial with mechanically robust and high energy density is critical for flexible electronics, such as batteries and supercapacitors. Plant proteins are ideal candidates for making flexible electronics due to their renewable and eco-friendly natures. However, due to the weak intermolecular interactions and abundant hydrophilic groups of protein chains, the mechanical properties of protein-based materials, especially in bulk materials, are largely constrained, which hinders their performance in practical applications. Here, a green and scalable method is shown for the fabrication of advanced film biomaterials with high mechanical strength (36.3 MPa), toughness (21.25 MJ m-3 ), and extraordinary fatigue-resistance (213 000 times) by incorporating tailor-made core-double-shell structured nanoparticles. Subsequently, the film biomaterials combine to construct an ordered, dense bulk material by stacking-up and hot-pressing techniques. Surprisingly, the solid-state supercapacitor based on compacted bulk material shows an ultrahigh energy density of 25.8 Wh kg-1 , which is much higher than those previously reported advanced materials. Notably, the bulk material also demonstrates long-term cycling stability, which can be maintained under ambient condition or immersed in H2 SO4 electrolyte for more than 120 days. Thus, this research improves the competitiveness of protein-based materials for real-world applications such as flexible electronics and solid-state supercapacitors.

Chiral Smith–Purcell Radiation Light Source

Abstract: Smith–Purcell radiation (SPR) with broadly tunable spectra has attracted attention in light emission, and this free-electron-driven source shows great potential in illumination fields, such as terahertz sources, ultra-compact light sources, free-electron lasers, etc. However, it remains difficult to control the polarization properties of SPR and realize a free-electron chiral light source. In this work, the chiral SPR with the maximum chirality (>40%) is acquired in a periodic stacked nanosquare light-well, and the radiation chirality is manipulated by variations of the designed electron beam excitation positions. Furthermore, this work reveals that the chiroptical effect originates in the superposition of SPRs with different phases and polarization, which are derived from adjacent sidewalls. This work may deepen the comprehension of electron-matter interaction and facilitate the development of compact electron-driven chirality-tunable source-on-chip, highlighting potential applications in photonic integration and binary data processing.

Arbitrary Multifunctional Vortex Beam Designed by Deep Neural Network

Abstract: As topological charge constitutes an infinite-dimensional Hilbert space, vortex beam has numerous applications in optical communications and other fields where signal capacity is a vital requirement. Multifunctional vortex beams, showing up to different controllable responses subjected to separate combinations of polarization states, have significantly exhibited improved capacity of signal transport. Relying on prior physical knowledge, complex requirement brings tremendous challenge to the design of multifunctional vortex beams. Here, a deep-learning-based platform for designing metasurfaces is proposed, which can intelligently generate predesigned multifunctional vortex beams. Employing the proposed strategy, the demonstrations of bifunctional and trifunctional vortex beams are consistent with the design targets. Three samples are fabricated and measured by a Michelson interferometer. Clear observed interference patterns revealed the topological nature of the generated vortex beams, unambiguously justifying the design platform. This intelligent design strategy, which may inspire new ideas in other scientific fields, lays a solid foundation for the high-performance application of multifunctional vortex beams. This work fully exploits the potential of vortex beams for large-scale dense data communication and quantum optics with high quantum numbers, which may further promote the development of the integrated photonic chip.

Polarization Multiplexing Bifunctional Metalens Designed by Deep Neural Networks

Abstract: As planar optical elements, metasurfaces confer an unprecedented potential to manipulate light, which benefits from the deep control of the interactions between nanostructures and light. In the past decade, considerable progress has been made in various metasurfaces for on‐demand functions, drawing great interest from the scientific community. However, it is a great challenge to integrate different functions into a single metasurface, due to the incapability of manipulating light at different dimensions and the lack of universal intelligent design strategy. Here, an intelligent design platform based on deep neural networks is proposed, which can map between structure parameters and optical response. The well‐trained network model can intelligently retrieve nanostructures to meet multidimensional optical requirements of metasurfaces. Four metalenses for chiral focusing are realized by the design platform and the simulation results are highly consistent with the design target. In addition, metalenses based on arbitrary polarization at various working wavelength are also demonstrated, showing that the method has powerful design ability. Various optical properties of nanostructures, such as phase shift and polarization, are manipulated by deep neural networks, which can greatly promote the development of multifunctional devices and further pave the way for optical display, communication, computing, sensing, and other applications.

Phonon-assisted upconversion in twisted two-dimensional semiconductors

Abstract: Abstract Phonon-assisted photon upconversion (UPC) is an anti-Stokes process in which incident photons achieve higher energy emission by absorbing phonons. This letter studies phonon-assisted UPC in twisted 2D semiconductors, in which an inverted contrast between UPC and conventional photoluminescence (PL) of WSe 2 twisted bilayer is emergent. A 4-fold UPC enhancement is achieved in 5.5° twisted bilayer while PL weakens by half. Reduced interlayer exciton conversion efficiency driven by lattice relaxation, along with enhanced pump efficiency resulting from spectral redshift, lead to the rotation-angle-dependent UPC enhancement. The counterintuitive phenomenon provides a novel insight into a unique way that twisted angle affects UPC and light-matter interactions in 2D semiconductors. Furthermore, the UPC enhancement platform with various superimposable means offers an effective method for lighting bilayers and expanding the application prospect of 2D stacked van der Waals devices.

Multidimensional modulation of light fields via a combination of two-dimensional materials and meta-structures

Abstract: In recent years, researchers have increasingly directed their attention towards modulating light fields through the unique properties of two-dimensional materials and the free designability of meta-structures. Graphene, transition metal sulfides, transition metal nitrides, and other two-dimensional materials have emerged as star materials in recent years due to their extraordinary properties that are vastly different from those of traditional three-dimensional materials. As a result, these materials hold immense potential for further exploration and research. Taking advantage of the free designability of meta-structures can be an effective means of unlocking the full potential of 2D materials. Accordingly, this review presents an overview of recent research progress in the area of light field modulation achieved by combining 2D materials with meta-structures. The review initially covers the properties of 2D materials, followed by the concepts, principles, design, and preparation of meta-structures. Then the review delves into the concrete examples of the impact and effect of the combination on light field modulation. Lastly, the review concludes with a comprehensive summary and analysis of the current challenges and potential future developments of combining 2D materials with meta-structures.