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Artificial intelligence has gained significant attention for exploiting optical scattering for optical encryption. Conventional scattering media are inevitably influenced by instability or perturbations, and hence unsuitable for long-term scenarios. Additionally, the plaintext can be easily compromised due to the single channel within the medium and one-to-one mapping between input and output. To mitigate these issues, a stable spin-multiplexing disordered metasurface (DM) with numerous polarized transmission channels serves as the scattering medium, and a double-secure procedure with superposition of plaintext and security key achieves two-to-one mapping between input and output. In attack analysis, when the ciphertext, security key, and incident polarization are all correct, the plaintext can be decrypted. This system demonstrates excellent decryption efficiency over extended periods in noisy environments. The DM, functioning as an ultra-stable and active speckle generator, coupled with the double-secure approach, creates a highly secure speckle-based cryptosystem with immense potentials for practical applications. In this work, the employment of disordered metasurface as an ultra-stable and actively polarized speckle generator in a passive manner, coupled with a double-secure treatment to the plaintext, enables a highly secure speckle-based cryptosystem.

In recent years, surface electromyography (sEMG)-based human–computer interaction has been developed to improve the quality of life for people. Gesture recognition based on the instantaneous values of sEMG has the advantages of accurate prediction and low latency. However, the low generalization ability of the hand gesture recognition method limits its application to new subjects and new hand gestures, and brings a heavy training burden. For this reason, based on a convolutional neural network, a transfer learning (TL) strategy for instantaneous gesture recognition is proposed to improve the generalization performance of the target network. CapgMyo and NinaPro DB1 are used to evaluate the validity of our proposed strategy. Compared with the non-transfer learning (non-TL) strategy, our proposed strategy improves the average accuracy of new subject and new gesture recognition by 18.7% and 8.74%, respectively, when up to three repeated gestures are employed. The TL strategy reduces the training time by a factor of three. Experiments verify the transferability of spatial features and the validity of the proposed strategy in improving the recognition accuracy of new subjects and new gestures, and reducing the training burden. The proposed TL strategy provides an effective way of improving the generalization ability of the gesture recognition system.

Cobalt phosphide (CoP) has been emerging as alternative lithium-ion batteries (LIBs) anode in view of the outstanding thermodynamic stability and high theoretical capacity. However, the lithium storage behaviors were impeded by poor cycling and rate performance induced by huge volumetric changes of CoP anodes during Li+ intercalation/deintercalation and the poor reaction kinetics caused by low electronic conductivity. Herein, the uniquely designed hemoglobin-like composites consisting of CoP nanoparticles coated by N, P-doped carbon shell (CoP@PNC) were prepared via a supramolecular self-assembly method, followed by the facile heat treatment process, which presented the amorphous phase. Based on the synergistic effects of rational nano/microstructure, double heterogeneous elements doped carbon substrate and amorphous phase, the transport paths of Li+ and e− were shortened, the electronic conductivity was enhanced, the volumetric changes were effectively alleviated, resulting in outstanding electrochemical performance when applied as anode electrodes. The CoP@PNC electrodes deliver a capacity of 806.8 mAh g−1 after 100 cycles at 0.1 A g−1 and 523.9 mAh g−1 after 3000 cycles at 2.0 A g−1. Furthermore, pseudo-capacitance behavior dominates the storage mechanism of CoP@PNC electrodes based on the quantitative kinetic analysis result that a high ratio of 66% in total capacity at 0.5 mV−1. This work illuminates the route to effectively relieve the huge volumetric changes to improve the electrochemical performance of transition metal phosphide and promote their practical application steps as electrodes for high energy density batteries.

The precise fabrication and regulation of the stable catalysts with desired performance still challengeable for single atom catalysts. Here, the Ru single atoms with different coordination environment in Ni 3 FeN lattice are synthesized and studied as a typical case over alkaline methanol electrooxidation. The Ni 3 FeN with buried Ru atoms in subsurface lattice (Ni 3 FeN-Ru buried ) exhibits high selectivity and Faradaic efficiency of methanol to formate conversion. Meanwhile, operando spectroscopies reveal that the Ni 3 FeN-Ru buried exhibits an optimized adsorption of reactants along with an inhibited surface structural reconstruction. Additional theoretical simulations demonstrate that the Ni 3 FeN-Ru buried displays a regulated local electronic states of surface metal atoms with an optimized adsorption of reactants and reduced energy barrier of potential determining step. This work not only reports a high-efficient catalyst for methanol to formate conversion in alkaline condition, but also offers the insight into the rational design of single atom catalysts with more accessible surficial active sites. Fine turning the local configuration of single atoms into substrate is challenging. Here, the authors report that burying single atoms into subsurface lattice of substrate can stimulate more surficial active sites and thus promote the overall catalytic performance in methanol electrooxidation.

Optical vortices, featured with an infinite number of orthogonal channels of orbital angular momentum, have demonstrated marvelous potentials in optical multiplexing and associated applications. However, conventional vortex beams with global phase modulation approach usually possess a single topological charge (TC) and a uniform radial distance with the donut-shaped intensity, leaving unlimited spatial intensity information unexplored. Here, to break the spatial capacity limitation, we introduce an entirely new concept of a spatial-frequency patching metasurface by patching the field distribution piece-by-piece in the spatial-frequency domain, thereby breaking the symmetry of the beam morphology and allowing for local manipulation of spatial intensity and TC distributions. Moreover, by superimposing two orthogonal circular polarized perfect VBs, our breakthrough offers a super-capacity with at least 13 channels across a 3D parametric space, including morphology, polarization azimuth and ellipticity angle, namely super-capacity perfect vector vortex beams (SC-PVVBs). Furthermore, we have designed an optimized Dammann grating to facilitate an array of SC-PVVBs, thereby unleashing the full potentials across 13 channels/bits for multi-dimensional complex information communications. Our findings promise dense data transmission in an ultra-secure manner using VBs, opening up new avenues in super-capacity optical information technology in an integrated metasurface platform.

Orbital angular momentum (OAM) multiplexing holography has emerged as a pivotal technology for high-capacity optical communication, encryption and display, but it requires multiple inputs for decoding and its security remain constrained due to the rotational symmetry of topological charge (TC) distribution in conventional OAM modes. Here, we introduce a general paradigm of OAM multiplexing holography that enables multi-channel holographic encoding using a single incident light. Our methodology leverages a discontinuous OAM with a spatially varying TC across the azimuth, which breaks the rotational symmetry and imposes angular selectivity for information retrieval. Notably, by rationally designing the TC distribution, the discontinuous OAM exhibits self-orthogonality at different rotation angles, laying the foundation for multiplexed holography. A modified weighted Gerchberg-Saxton algorithm is developed to calculate the holographic phase profile, which can then be encoded onto a pure geometry-phase metasurface. By further integrating different pairs of discontinuous OAMs, we successfully expand the channel capacity for holographic multiplexing, significantly advancing high-security and high-capacity optical information encryption. Our work establishes discontinuous OAM as a versatile platform for secure optical communications, high-density data storage, and dynamic holographic displays, bridging the gap between structured light manipulation and cryptographic robustness. Gao et al. realized a discontinuous orbital angular momentum metasurface holography, which enhances the channel capacity for holographic multiplexing and makes significant strides in high-security optical information encryption.

In order to meet the efficiency and smooth trajectory requirements of the casting sorting robotic arm, we propose a time-optimal trajectory planning method that combines a heuristic algorithm inspired by the behavior of the Genghis Khan shark (GKS) and segmented interpolation polynomials. First, the basic model of the robotic arm was constructed based on the arm parameters, and the workspace is analyzed. A matrix was formed by combining cubic and quintic polynomials using a segmented approach to solve for 14 unknown parameters and plan the trajectory. To enhance the smoothness and efficiency of the trajectory in the joint space, a dynamic nonlinear learning factor was introduced based on the traditional Particle Swarm Optimization (PSO) algorithm. Four different biological behaviors, inspired by GKS, were simulated. Within the premise of time optimality, a target function was set to effectively optimize within the feasible space. Simulation and verification were performed after determining the working tasks of the casting sorting robotic arm. The results demonstrated that the optimized robotic arm achieved a smooth and continuous trajectory velocity, while also optimizing the overall runtime within the given constraints. A comparison was made between the traditional PSO algorithm and an improved PSO algorithm, revealing that the improved algorithm exhibited better convergence. Moreover, the planning approach based on GKS behavior showed a decreased likelihood of getting trapped in local optima, thereby confirming the effectiveness of the proposed algorithm.

Designing highly active material to fabricate a high-performance noninvasive wearable glucose sensor was of great importance for diabetes monitoring. In this work, we developed CuxO nanoflakes (NFs)/Cu nanoparticles (NPs) nanocomposites to serve as the sensing materials for noninvasive sweat-based wearable glucose sensors. We involve CuCl2 to enhance the oxidation of Cu NPs to generate Cu2O/CuO NFs on the surface. Due to more active sites endowed by the CuxO NFs, the as-prepared sample exhibited high sensitivity (779 μA mM−1 cm−2) for noninvasive wearable sweat sensing. Combined with a low detection limit (79.1 nM), high selectivity and the durability of bending and twisting, the CuxO NFs/Cu NPs-based sensor can detect the glucose level change of sweat in daily life. Such a high-performance wearable sensor fabricated by a convenient method provides a facile way to design copper oxide nanomaterials for noninvasive wearable glucose sensors.

A rational design principle for selecting optimal anion dopants in transition-metal compounds to enhance sulfur redox activity is lacking in Li-S batteries. Herein, we propose an accurate p-p-s orbital electronic coupling descriptor (involving the p -orbitals of anion dopants and anions in transition-metal compounds and the s -orbitals of Li in lithium polysulfides) as a criterion for choosing anion dopants to guide the development of efficient anion-doped Li-S catalysts through machine-learning, theoretical, and experimental validation. We reveal the relationship between the electronic properties of various anion-doped WSe 2 and the thermodynamics and kinetics of sulfur redox. Our findings show that moderate p-p-s orbital electronic coupling optimizes polysulfide adsorption, facilitating Li 2 S nucleation and decomposition, thereby minimizing Gibbs free energy and maximizing catalytic efficiency for sulfur redox. A volcano relationship between the p-p-s coupling strength and catalytic activity is established. The optimal B-WSe 2 /MXene catalyst achieves a ~ 3 Ah pouch cell with 430 Wh kg −1 specific energy and good cycle life (81.3% capacity retention over 71 cycles). These findings provide a guideline for designing efficient anion-doped Li-S catalysts with moderate p-p-s coupling to enable rapid sulfur catalytic conversion in Li-S batteries. The mechanism of how different anion dopants influence the catalytic performance for sulfur species is currently lacking systematic theoretical studies. Here, an accurate p-p-s electronic coupling descriptor was proposed as a criterion to guide the design of anion-doped Li-S catalysts.

In contemporary society, individuals have elevated expectations for visual communication. Low-resolution images can negatively impact image quality and viewing experience. As a result, enhancing the visual communication of multiframe, low-resolution image sequences has become a primary focus of current research. This study optimized the visual communication effect of multiframe, low-resolution photo sequences using deep photo superresolution reconstruction technology based on low-resolution, color-guided photos. Meanwhile, the visual communication effect of multiframe low-resolution image sequences has also been improved. The experimental results indicated that from the perspective of infrared spectroscopy, multiframe video photo visual communication resources could have a harvest probability of 99% and a tracking efficiency of 96%. The reconstruction results of deep photos from various sources indicated that sparse encoding-based superresolution resources are suitable for doll images. Among different color photo superresolution algorithms, gradient-based upsampling network and adaptive separable data-specific transformation resources can better recover guided photos. Optimization algorithms can effectively enhance the visual communication of multiframe low-resolution image sequences by removing noise and improving image details while maintaining the natural style of the image and enhancing clarity. The proposed image strength enhancement method can address the issue of poor visual communication performance in multiframe low-resolution image sequences. The resources for optimizing visual connection effects in multiframe, low-resolution photo sequences can solve the problem of multiframe and low-resolution simultaneously. This approach has greater potential for development compared to a single solution. Therefore, this application holds significant reference value.