Ultrasensitive Biomimetic Skin with Multimodal and Photoelectric Dual-Signal Sensing.

Mimicking biological skin enabling direct, intelligent interaction between users and devices, multimodal sensing with optical/electrical (OE) output signals is urgently required. Owing to this, this work aims to logically design a stretchable OE biomimetic skin (OE skin), which can sensitively sense complex external stimuli of pressure, strain, temperature, and localization. The OE skin consists of elastic thin polymer-stabilized cholesteric liquid crystal films, an ion-conductive hydrogel layer, and an elastic protective membrane formed with thin polydimethylsiloxane. The as-designed OE skin exhibits customizable structural color on demand, good thermochromism, and excellent mechanochromism, with the ability to extend the full visible spectrum, a good linearity of over 0.99, fast response speed of 93 ms, and wide temperature range of 119 °C. In addition, the conduction resistance variation of ion-conductive hydrogel exhibits excellent sensing capabilities under pressure, stretch, and temperature, endowing a good linearity of 0.99998 (stretching from 0 to 150%) and high thermal sensitivity of 0.86% per °C. Such an outstanding OE skin provides design concepts for the development of multifunctional biomimetic skin used in human-machine interaction and can find wide applications in intelligent wearable devices and human-machine interactions.

Phototransformation of achiral metasurfaces into handedness-selectable transient chiral media.

Chirality is a geometric property describing the lack of mirror symmetry. This unique feature enables photonic spin-selectivity in light-matter interaction, which is of great significance in stereochemistry, drug development, quantum optics, and optical polarization control. The versatile control of optical geometry renders optical metamaterials as an effective platform for engineered chiral properties at prescribed spectral regimes. Unfortunately, geometry-imposed restrictions only allow one circular polarization state of photons to effectively interact with chiral meta-structures. This limitation motivates the idea of discovering alternative techniques for dynamically reconfiguring the chiroptical responses of metamaterials in a fast and facile manner. Here, we demonstrate an approach that enables optical, sub-picosecond conversion of achiral meta-structures to transient chiral media in the visible regime with desired handedness upon the inhomogeneous generation of plasmonic hot electrons. As a proof of concept, we utilize linearly polarized laser pulse to demonstrate near-complete conversion of spin sensitivity in an achiral meta-platform-a functionality yet achieved in a non-mechanical fashion. Owing to the generation, diffusion, and relaxation dynamics of hot electrons, the demonstrated technique for all-optical creation of chirality is inherently fast, opening new avenues for ultrafast spectro-temporal construction of chiral platforms with on-demand spin-selectivity.

Effects of α-Lipoic Acid Supplementation on Growth Performance, Liver Histology, Antioxidant and Related Genes Expression of Hybrid Grouper (Epinephelus fuscoguttatus ♀ × E. lanceolatus ♂).

This study aimed to assess the impact of α-lipoic acid on the growth performance, antioxidant capacity and immunity in hybrid groupers (♀ Epinephelus fuscoguttatus × â™‚ E. lanceolatus) fed with a high-lipid diet. Groupers (8.97 ± 0.01 g) were fed six different diets, with α-lipoic acid content in diets being 0, 400, 800, 1200, 1600, and 2000 mg/kg, named S1, S2, S3, S4, S5, and S6, respectively. The results show that the addition of 2000 mg/kg α-lipoic acid in the diet inhibited the growth, weight gain rate (WGR), and specific growth rate (SGR), which were significantly lower than other groups. In serum, catalase (CAT) and superoxide dismutase (SOD) were significantly higher in the S5 group than in the S1 group. In the liver, CAT, SOD and total antioxidative capacity (T-AOC) levels were significantly increased in α-lipoic acid supplemented groups. α-lipoic acid significantly upregulated liver antioxidant genes sod and cat, anti-inflammatory factor interleukin 10 (il10) and transforming growth factor ß (tgfß) mRNA levels. Conclusion: the addition of 2000 mg/kg of α-lipoic acid inhibits the growth of hybrid groupers. In addition, 400-800 mg/kg α-lipoic acid contents improve the antioxidant capacity of groupers and have a protective effect against high-lipid-diet-induced liver oxidative damage.

Changes in carbohydrate metabolism and soil microorganisms under the stress of polyamide and polyethylene nanoplastics during rice (Oryza sativa L.) growth.

Nanoplastics (NPs) presence in agricultural soils can affect plant growth and impact the quality of agricultural products. To investigate the effect of polyamide (PA) NPs and polyethylene (PE) NPs on carbohydrate metabolism and soil microorganisms during rice growth, rice seedlings were exposed to soil containing 2 g/kg of 100 nm PA or 100 nm PE powder for 33 d. The results revealed that 100 nm PE reduced shoot length and dry weight of rice by 4.14 % and 15.68 %, respectively. Analyzing the expression of hexokinase-2 (HXK), phosphofructokinase-1 (PFK), pyruvate kinase (PK) and isocitrate dehydrogenase (IDH), which are four genes related to carbohydrate metabolism, 100 nm PA decreased the expression of PFK and increased the expression of PK and IDH. 100 nm PE increased the expression of HXK, PFK, PK, and IDH. The results of soil microorganisms showed that 100 nm PA significantly effects on 3 bacterial phyla (Bacteroidota, Deinococcota, and Desulfobacterota), whereas 100 nm PE significantly effects on phylum Rozellomycota, class Umbelopsidomycetes, and an unclassified Firmicutes. Our study provides direct evidence of the negative effects of PA and PE on rice, which may be important for assessing the risk of NPs on agroecosystems.

Determining hot-carrier transport dynamics from terahertz emission.

Understanding the ultrafast excitation and transport dynamics of plasmon-driven hot carriers is critical to the development of optoelectronics, photochemistry, and solar-energy harvesting. However, the ultrashort time and length scales associated with the behavior of these highly out-of-equilibrium carriers have impaired experimental verification of ab initio quantum theories. Here, we present an approach to studying plasmonic hot-carrier dynamics that analyzes the temporal waveform of coherent terahertz bursts radiated by photo-ejected hot carriers from designer nano-antennas with a broken symmetry. For ballistic carriers ejected from gold antennas, we find an ~11-femtosecond timescale composed of the plasmon lifetime and ballistic transport time. Polarization- and phase-sensitive detection of terahertz fields further grant direct access to their ballistic transport trajectory. Our approach opens explorations of ultrafast carrier dynamics in optically excited nanostructures.

Genetic Analysis of Novel Fertility Restoration Genes (qRf3 and qRf6) in Dongxiang Wild Rice Using GradedPool-Seq Mapping and QTL-Seq Correlation Analysis.

The improvement of grain yield, quality, and resistance can be achieved through the utilization of heterosis. The combination of cytoplasmic male sterility (CMS) and fertility restoration (Rf) gene(s) greatly facilitates the commercial development of three-line hybrid rice based on heterosis. The basis for investigating the relationship between CMS and Rf genes lies in the rapid localization of wild rice fertility restoration genes. A set of the BC4F5 population derived from interspecific crosses between Xieqingzao B (XB) and the BC1F9 XB//Dongxiang wild rice (DWR)/XB line L5339 was used to detect quantitative trait loci (QTL) for fertility restoration. The population was then crossed with two male sterile lines, Zhong9A (Z9A) and DongB11A (DB11A), in order to generate a testcrossing population for investigating spikelet fertility. Based on the linkage mapping, seven QTLs were detected on chromosomes 1, 3, 5, 6, 8, and 10, explaining 2.76 to 12.46% of the phenotypic variation. Of them, two novel fertility restoration QTLs, qRf3 and qRf6, can restore fertility of the CMS-DWR line DB11A by 16.56% and 15.12%, respectively. By employing joint QTL-seq and GradedPool-Seq methods, two novel Rf QTLs for DB11A, qRf3 and qRf6, were identified at the physical locations of 10,900,001-11,700,000 bp and 28,016,785-31,247,556 bp, respectively. These findings are useful for exploring the natural variations of Rf genes in rice. Therefore, rice's new genetic resources for the selection and breeding of rice restorer lines provide promising candidates for QTL fine localization and clarification.

Tailored Dispersion of Spectro-Temporal Dynamics in Hot-Carrier Plasmonics.

Ultrafast optical switching in plasmonic platforms relies on the third-order Kerr nonlinearity, which is tightly linked to the dynamics of hot carriers in nanostructured metals. Although extensively utilized, a fundamental understanding on the dependence of the switching dynamics upon optical resonances has often been overlooked. Here, all-optical control of resonance bands in a hybrid photonic-plasmonic crystal is employed as an empowering technique for probing the resonance-dependent switching dynamics upon hot carrier formation. Differential optical transmission measurements reveal an enhanced switching performance near the anti-crossing point arising from strong coupling between local and nonlocal resonance modes. Furthermore, entangled with hot-carrier dynamics, the nonlinear correspondence between optical resonances and refractive index change results in tailorable dispersion of recovery speeds which can notably deviate from the characteristic lifetime of hot carriers. The comprehensive understanding provides new protocols for optically characterizing hot-carrier dynamics and optimizing resonance-based all-optical switches for operations across the visible spectrum.

Detection of acute ischemic stroke and backtracking stroke onset time via machine learning analysis of metabolomics.

The time window from stroke onset is critical for the treatment decision. However, in unknown onset stroke, it is often difficult to determine the exact onset time because of the lack of assessment methods, which can result in controversial and random treatment decisions. Previous studies have shown that serum biomarkers, in addition to imaging assessment, are useful for determining the stroke onset time. However, as yet there are no specific biomarkers or corresponding methodologies that are accurate and effective for determining the onset time of unknown onset stroke. Herein, we describe our novel advanced metabolites-based machine learning method (termed extreme gradient boost [XGBoost]) combined with recursive feature elimination, which accurately screened five metabolites from 1124 metabolites detected in serum. These metabolites were capable of both detecting acute ischemic stroke and backtracking the acute ischemic stroke onset time. To further investigate the pathological mechanisms of acute ischemic stroke, we also examined characteristic metabolites in different brain regions, and found two metabolites that could distinguish the core infarct area from the ischemic penumbra. Although this study is based on animal experiments, our machine learning framework and selected metabolites may provide a basis for clinical stroke evaluation and treatment.

Electrically driven reprogrammable phase-change metasurface reaching 80% efficiency.

Phase-change materials (PCMs) offer a compelling platform for active metaoptics, owing to their large index contrast and fast yet stable phase transition attributes. Despite recent advances in phase-change metasurfaces, a fully integrable solution that combines pronounced tuning measures, i.e., efficiency, dynamic range, speed, and power consumption, is still elusive. Here, we demonstrate an in situ electrically driven tunable metasurface by harnessing the full potential of a PCM alloy, Ge2Sb2Te5 (GST), to realize non-volatile, reversible, multilevel, fast, and remarkable optical modulation in the near-infrared spectral range. Such a reprogrammable platform presents a record eleven-fold change in the reflectance (absolute reflectance contrast reaching 80%), unprecedented quasi-continuous spectral tuning over 250 nm, and switching speed that can potentially reach a few kHz. Our scalable heterostructure architecture capitalizes on the integration of a robust resistive microheater decoupled from an optically smart metasurface enabling good modal overlap with an ultrathin layer of the largest index contrast PCM to sustain high scattering efficiency even after several reversible phase transitions. We further experimentally demonstrate an electrically reconfigurable phase-change gradient metasurface capable of steering an incident light beam into different diffraction orders. This work represents a critical advance towards the development of fully integrable dynamic metasurfaces and their potential for beamforming applications.

Mid-infrared broadband circular polarizer based on Weyl semimetals.

As a three-dimensional topological phase of matter, Weyl semimetals possess extremely large gyrotropic optical response in the mid-infrared region, leading to the strong chiral anomaly. This study proposes a circular polarizer design with a double-WSM-layer structure. It is theoretically shown that the proposed polarizer possesses a high circular polarization efficiency and high average transmittance in the wavelength region from 9 µm to 15 µm at incidence angles up to 50°. The modified 4 × 4 matrix method is used to calculate the circularly polarized transmittance of Weyl semimetals in thin-film or multilayer structures. The temperature dependence on the transmittance is also examined to demonstrate the flexibility of the proposed polarizer in a varying temperature environment. This study reveals the technological prospect that Weyl semimetals are promising candidates for high-performance circular polarizers in infrared spectroscopy and polarimetry.

Maximized Frequency Doubling through the Inverse Design of Nonlinear Metamaterials.

The conventional process for developing an optimal design for nonlinear optical responses is based on a trial-and-error approach that is largely inefficient and does not necessarily lead to an ideal result. Deep learning can automate this process and widen the realm of nonlinear geometries and devices. This research illustrates a deep learning framework used to create an optimal plasmonic design for a nonlinear metamaterial. The algorithm produces a plasmonic pattern that can maximize the second-order nonlinear effect of a nonlinear metamaterial. A nanolaminate metamaterial is used as a nonlinear material, and plasmonic patterns are fabricated on the prepared nanolaminate to demonstrate the validity and efficacy of the deep learning algorithm. The optimal pattern produced yielded second-harmonic generation from the nanolaminate with normal incident fundamental light. The deep learning architecture applied in this research can be expanded to other optical responses and light-matter interaction processes.

Ultrasensitive Molecular Detection by Imaging of Centimeter-Scale Metasurfaces with a Deterministic Gradient Geometry.

Highly sensitive detection of trace amounts of substances is crucial for broad applications in healthcare, environmental monitoring, antiterrorism, etc., where cost effectiveness and portability are often demanded. Here, an ultrasensitive sensor is reported that can detect an angstrom-thick layer of adsorbed molecules through image acquisition and processing. The sensor features a centimeter-scale plasmonic metasurface with spatially varying geometry, where the light scattering is dependent on both the adsorbed substances and spatial locations. When illuminated with narrowband light (such as from a light emitting diode), the intensity pattern recorded on the metasurface changes with the surface-adsorbed molecules, enabling label-free, sensitive, and spectrometer-free molecular detection. The centimeter-scale size of the sensing area interfaces well with consumer-level imaging sensors on mobile devices without the need for microscopic optics and offers a high signal-to-noise ratio by leveraging the multimillion pixels for noise reduction. It is experimentally demonstrated that a single layer of Al2 O3 molecules deposited on the sensor, with a thickness of approximately one angstrom, can be detected by analyzing the images taken of the sensing chip. Furthermore, by integrating the sensor into a microfluidic setup, quantitative detection of BSA/anti-BSA immune complex formation events is demonstrated, which agrees well with the Langmuir isotherm model.

Tackling Photonic Inverse Design with Machine Learning.

Machine learning, as a study of algorithms that automate prediction and decision-making based on complex data, has become one of the most effective tools in the study of artificial intelligence. In recent years, scientific communities have been gradually merging data-driven approaches with research, enabling dramatic progress in revealing underlying mechanisms, predicting essential properties, and discovering unconventional phenomena. It is becoming an indispensable tool in the fields of, for instance, quantum physics, organic chemistry, and medical imaging. Very recently, machine learning has been adopted in the research of photonics and optics as an alternative approach to address the inverse design problem. In this report, the fast advances of machine-learning-enabled photonic design strategies in the past few years are summarized. In particular, deep learning methods, a subset of machine learning algorithms, dealing with intractable high degrees-of-freedom structure design are focused upon.

Dynamic Hybrid Metasurfaces.

Efficient hybrid plasmonic-photonic metasurfaces that simultaneously take advantage of the potential of both pure metallic and all-dielectric nanoantennas are identified as an emerging technology in flat optics. Nevertheless, postfabrication tunable hybrid metasurfaces are still elusive. Here, we present a reconfigurable hybrid metasurface platform by incorporating the phase-change material Ge2Sb2Te5 (GST) into metal-dielectric meta-atoms for active and nonvolatile tuning of properties of light. We systematically design a reduced-dimension meta-atom, which selectively controls the hybrid plasmonic-photonic resonances of the metasurface via the dynamic change of optical constants of GST without compromising the scattering efficiency. As a proof-of-concept, we experimentally demonstrate two tunable metasurfaces that control the amplitude (with relative modulation depth as high as ≈80%) or phase (with tunability >230°) of incident light promising for high-contrast optical switching and efficient anomalous to specular beam deflection, respectively. Our findings further substantiate dynamic hybrid metasurfaces as compelling candidates for next-generation reprogrammable meta-optics.

Building Multifunctional Metasystems via Algorithmic Construction.

Flat optics foresees a promising route to ultracompact optical devices, where metasurfaces serve as the foundation. Conventional designs of metasurfaces start with a certain structure as the prototype, followed by extensive parametric sweeps to accommodate the requirements of phase and amplitude of the emerging light. Regardless of how computation consuming the process is, a predefined structure can hardly realize the independent control over polarization, frequency, and spatial channels, which hinders the potential of metasurfaces to be multifunctional. Besides, achieving complicated and multiple functions calls for designing metasystems with multiple cascading layers of metasurfaces, which introduces exponential complexity. In this work, we present a hybrid deep learning framework for designing multilayer metasystems with multifunctional capabilities. We demonstrate examples of a polarization-multiplexed dual-functional beam generator, a second-order differentiator for all-optical computing, and a space-polarization-wavelength multiplexed hologram. These examples are barely achievable by single-layer metasurfaces and unattainable by traditional design processes.

Stable, high-performance sodium-based plasmonic devices in the near infrared.

Plasmonics enables the manipulation of light beyond the optical diffraction limit1-4 and may therefore confer advantages in applications such as photonic devices5-7, optical cloaking8,9, biochemical sensing10,11 and super-resolution imaging12,13. However, the essential field-confinement capability of plasmonic devices is always accompanied by a parasitic Ohmic loss, which severely reduces their performance. Therefore, plasmonic materials (those with collective oscillations of electrons) with a lower loss than noble metals have long been sought14-16. Here we present stable sodium-based plasmonic devices with state-of-the-art performance at near-infrared wavelengths. We fabricated high-quality sodium films with electron relaxation times as long as 0.42 picoseconds using a thermo-assisted spin-coating process. A direct-waveguide experiment shows that the propagation length of surface plasmon polaritons supported at the sodium-quartz interface can reach 200 micrometres at near-infrared wavelengths. We further demonstrate a room-temperature sodium-based plasmonic nanolaser with a lasing threshold of 140 kilowatts per square centimetre, lower than values previously reported for plasmonic nanolasers at near-infrared wavelengths. These sodium-based plasmonic devices show stable performance under ambient conditions over a period of several months after packaging with epoxy. These results indicate that the performance of plasmonic devices can be greatly improved beyond that of devices using noble metals, with implications for applications in plasmonics, nanophotonics and metamaterials.

Synthetic Engineering of Morphology and Electronic Band Gap in Lateral Heterostructures of Monolayer Transition Metal Dichalcogenides.

Heterostructures of two-dimensional transition metal dichalcogenides (TMDs) can offer a plethora of opportunities in condensed matter physics, materials science, and device engineering. However, despite state-of-the-art demonstrations, most current methods lack enough degrees of freedom for the synthesis of heterostructures with engineerable properties. Here, we demonstrate that combining a postgrowth chalcogen-swapping procedure with the standard lithography enables the realization of lateral TMD heterostructures with controllable dimensions and spatial profiles in predefined locations on a substrate. Indeed, our protocol receives a monolithic TMD monolayer (e.g., MoSe2) as the input and delivers lateral heterostructures (e.g., MoSe2-MoS2) with fully engineerable morphologies. In addition, through establishing MoS2xSe2(1-x)-MoS2ySe2(1-y) lateral junctions, our synthesis protocol offers an extra degree of freedom for engineering the band gap energies up to ∼320 meV on each side of the heterostructure junction via changing x and y independently. Our electron microscopy analysis reveals that such continuous tuning stems from the random intermixing of sulfur and selenium atoms following the chalcogen swapping. We believe that, by adding an engineering flavor to the synthesis of TMD heterostructures, our study lowers the barrier for the integration of two-dimensional materials into practical optoelectronic platforms.

Topological encoding method for data-driven photonics inverse design.

Data-driven approaches have been proposed as effective strategies for the inverse design and optimization of photonic structures in recent years. In order to assist data-driven methods for the design of topology of photonic devices, we propose a topological encoding method that transforms photonic structures represented by binary images to a continuous sparse representation. This sparse representation can be utilized for dimensionality reduction and dataset generation, enabling effective analysis and optimization of photonic topologies with data-driven approaches. As a proof of principle, we leverage our encoding method for the design of two dimensional non-paraxial diffractive optical elements with various diffraction intensity distributions. We proved that our encoding method is able to assist machine-learning-based inverse design approaches for accurate and global optimization.

Transient Second-Order Nonlinear Media: Breaking the Spatial Symmetry in the Time Domain via Hot-Electron Transfer.

Second-order optical effects are essential to the active control of light and the generation of new spectral components. The inversion symmetry, however, prevents achieving a bulk χ^{(2)} response, limiting the portfolio of the second-order nonlinear materials. Here, we demonstrate subpicosecond conversion of a statically passive dielectric to a transient second-order nonlinear medium upon the ultrafast transfer of hot electrons. Induced by an optical switching signal, the amorphous dielectric with vanishing intrinsic χ^{(2)} develops dynamically tunable second-order nonlinear responses. By taking the second-harmonic generation as an example, we show that breaking the inversion symmetry through hot-electron dynamics can be leveraged to address the critical need for all-optical control of second-order nonlinearities in nanophotonics. Our approach can be generically adopted in a variety of material and device platforms, offering a new class of complex nonlinear media with promising potentials for all-optical information processing.

Photocarrier-Induced Active Control of Second-Order Optical Nonlinearity in Monolayer MoS2.

Atomically thin transition metal dichalcogenides (TMDs) in their excited states can serve as exceptionally small building blocks for active optical platforms. In this scheme, optical excitation provides a practical approach to control light-TMD interactions via the photocarrier generation, in an ultrafast manner. Here, it is demonstrated that via a controlled generation of photocarriers the second-harmonic generation (SHG) from a monolayer MoS2 crystal can be substantially modulated up to ≈55% within a timeframe of ≈250 fs, a set of performance characteristics that showcases the promise of low-dimensional materials for all-optical nonlinear data processing. The combined experimental and theoretical study suggests that the large SHG modulation stems from the correlation between the second-order dielectric susceptibility χ(2) and the density of photoexcited carriers in MoS2 . Indeed, the depopulation of the conduction band electrons, at the vicinity of the high-symmetry K/K' points of MoS2 , suppresses the contribution of interband electronic transitions in the effective χ(2) of the monolayer crystal, enabling the all-optical modulation of the SHG signal. The strong dependence of the second-order optical response on the density of photocarriers reveals the promise of time-resolved nonlinear characterization as an alternative route to monitoring carrier dynamics in excited states of TMDs.