Electrochemically Grown Ultrathin Platinum Nanosheet Electrodes with Ultralow Loadings for Energy-Saving and Industrial-Level Hydrogen Evolution

Nanostructured catalyst-integrated electrodes with remarkably reduced catalyst loadings,high catalyst utilization and facile fabrication are urgently needed to enable cost-effective,green hydrogen production via proton exchange membrane electrolyzer cells(PEMECs).Herein,benefitting from a thin seeding layer,bottom-up grown ultrathin Pt nanosheets(Pt-NSs)were first deposited on thin Ti substrates for PEMECs via a fast,template-and surfactant-free electrochemical growth process at room temperature,showing highly uniform Pt surface coverage with ultralow loadings and vertically well-aligned nanosheet morphologies.Combined with an anode-only Nafion 117 catalyst-coated membrane(CCM),the Pt-NS electrode with an ultralow loading of 0.015 mgPt cm−2 demonstrates superior cell performance to the commercial CCM(3.0 mgPt cm^(−2)),achieving 99.5%catalyst savings and more than 237-fold higher catalyst utilization.The remarkable performance with high catalyst utilization is mainly due to the vertically well-aligned ultrathin nanosheets with good surface coverage exposing abundant active sites for the electrochemical reaction.Overall,this study not only paves a new way for optimizing the catalyst uniformity and surface coverage with ultralow loadings but also provides new insights into nanostructured electrode design and facile fabrication for highly efficient and low-cost PEMECs and other energy storage/conversion devices.

An Integrated Scheduling Algorithm for the Same Equipment Process Sequencing Based on the Root-Subtree Vertical and Horizontal Pre-Scheduling

Given the existing integrated scheduling algorithms,all processes are ordered and scheduled overall,and these algorithms ignore the influence of the vertical and horizontal characteristics of the product process tree on the product scheduling effect.This paper presents an integrated scheduling algorithm for the same equipment process sequencing based on the Root-Subtree horizontal and vertical pre-scheduling to solve the above problem.Firstly,the tree decomposition method is used to extract the root node to split the process tree into several Root-Subtrees,and the Root-Subtree priority is set from large to small through the optimal completion time of vertical and horizontal pre-scheduling.All Root-Subtree processes on the same equipment are sorted into the stack according to the equipment process pre-start time,and the stack-top processes are combined with the schedulable process set to schedule and dispatch the stack.The start processing time of each process is determined according to the dynamic start processing time strategy of the equipment process,to complete the fusion operation of the Root-Subtree processes under the constraints of the vertical process tree and the horizontal equipment.Then,the root node is retrieved to form a substantial scheduling scheme,which realizes scheduling optimization by mining the vertical and horizontal characteristics of the process tree.Verification by examples shows that,compared with the traditional integrated scheduling algorithms that sort the scheduling processes as an overall,the integrated scheduling algorithmin this paper is better.The proposed algorithmenhances the process scheduling compactness,reduces the length of the idle time of the processing equipment,and optimizes the production scheduling target,which is of universal significance to solve the integrated scheduling problem.

Combination of AAV-delivered tumor suppressor PTEN with anti-PD-1 loaded depot gel for enhanced antitumor immunity

Recent clinical studies have shown that mutation of phosphatase and tensin homolog deleted on chromosome 10(PTEN)gene in cancer cells may be associated with immunosuppressive tumor microenvironment(TME)and poor response to immune checkpoint blockade(ICB)therapy.Therefore,efficiently restoring PTEN gene expression in cancer cells is critical to improving the responding rate to ICB therapy.Here,we screened an adeno-associated virus(AAV)capsid for efficient PTEN gene delivery into B16F10 tumor cells.We demonstrated that intratumorally injected AAV6-PTEN successfully restored the tumor cell PTEN gene expression and effectively inhibited tumor progression by inducing tumor cell immunogenic cell death(ICD)and increasing immune cell infiltration.Moreover,we developed an anti-PD-1 loaded phospholipid-based phase separation gel(PPSG),which formed an in situ depot and sustainably release anti-PD-1 drugs within 42 days in vivo.In order to effectively inhibit the recurrence of melanoma,we further applied a triple therapy based on AAV6-PTEN,PPSG^(@anti-PD-1)and CpG,and showed that this triple therapy strategy enhanced the synergistic antitumor immune effect and also induced robust immune memory,which completely rejected tumor recurrence.We anticipate that this triple therapy could be used as a new tumor combination therapy with stronger immune activation capacity and tumor inhibition efficacy.

用于高效水分解的聚合氮化碳光电极的熔体相与气相一体化沉积

氮化碳在光催化悬浮液体系的应用受到了广泛关注,但高质量氮化碳薄膜的制备技术仍处于初级阶段,限制了其在光电催化领域的应用.本文采用小分子双氰胺和硫脲为前驱体,实现了熔体相和气相一体化沉积制备高性能的氮化碳薄膜光电极.原位的沉积技术赋予氮化碳薄膜复合结构,包括具有合适厚度利于光吸收的多孔厚膜区域和具有较高碳/氮比利于电荷传输的致密薄膜区域.本文详细阐述了氮化碳薄膜沉积的各个阶段和前驱体双氰胺和硫脲在薄膜沉积过程的功能.独特的沉积方式和复合结构使得制备的氮化碳薄膜在光电催化水分解领域表现出优异的性能,在1.23 VRHE,0.1 mol L^(-1)NaOH电解液中表现出140μA cm^(-2)的光电流密度,相较于文献报道的熔体相沉积和气相沉积制备的氮化碳光阳极具有更高的竞争力.这种熔体相和气相沉积一体化策略对理解氮化碳光阳极的生长过程具有启发意义.

Orbital angular momentum mode logical operation using optical diffractive neural network

Optical logical operations demonstrate the key role of optical digital computing,which can perform general-purpose calculations and possess fast processing speed,low crosstalk,and high throughput.The logic states usually refer to linear momentums that are distinguished by intensity distributions,which blur the discrimination boundary and limit its sustainable applications.Here,we introduce orbital angular momentum(OAM)mode logical operations performed by optical diffractive neural networks(ODNNs).Using the OAM mode as a logic state not only can improve the parallel processing ability but also enhance the logic distinction and robustness of logical gates owing to the mode infinity and orthogonality.ODNN combining scalar diffraction theory and deep learning technology is designed to independently manipulate the mode and spatial position of multiple OAM modes,which allows for complex multilight modulation functions to respond to logic inputs.We show that few-layer ODNNs successfully implement the logical operations of AND,OR,NOT,NAND,and NOR in simulations.The logic units of XNOR and XOR are obtained by cascading the basic logical gates of AND,OR,and NOT,which can further constitute logical half-adder gates.Our demonstrations may provide a new avenue for optical logical operations and are expected to promote the practical application of optical digital computing.

Cylindrical vector beam multiplexer/demultiplexer using off-axis polarization control

The emergence of cylindrical vector beam(CVB)multiplexing has opened new avenues for high-capacity optical communication.Although several configurations have been developed to couple/separate CVBs,the CVB multiplexer/demultiplexer remains elusive due to lack of effective off-axis polarization control technologies.Here we report a straightforward approach to realize off-axis polarization control for CVB multiplexing/demultiplexing based on a metal–dielectric–metal metasurface.We show that the left-and right-handed circularly polarized(LHCP/RHCP)components of CVBs are independently modulated via spin-to-orbit interactions by the properly designed metasurface,and then simultaneously multiplexed and demultiplexed due to the reversibility of light path and the conservation of vector mode.We also show that the proposed multiplexers/demultiplexers are broadband(from 1310 to 1625 nm)and compatible with wavelength-division-multiplexing.As a proof of concept,we successfully demonstrate a four-channel CVB multiplexing communication,combining wavelength-division-multiplexing and polarization-division-multiplexing with a transmission rate of 1.56 Tbit/s and a bit-error-rate of 10^(−6) at the receive power of−21.6 dBm.This study paves the way for CVB multiplexing/demultiplexing and may benefit high-capacity CVB communication.

Controllable photonic spin Hall effect with phase function construction

Photonic spin Hall efect(SHE)provides new opportunities for achieving spin-based photonics applications.However,flexibly manipulating the spin-dependent sltting(SDS)of photonic SHE and imposing extra phase modulation on the two spin components are always a challenge.Here,a controllable SHE mechanism based on phase function construction is reported.It is conduded that the phases with specific functional structures performing a coordinate translation are equivalent to integrating a gradient phase to the original phases.Hence,the original phase can be used for independent phase modulation,and the gradient phase originating from the co-ordinate translation is capable of manipulating the SDS.A metasurface with Pancharatnam-Berry phase that can impose conjugate phases to the two spin components of light is fabricated to verify this mechanism.By shifing the light position,the SDS is continuously manipulated in the visible region,which is successfully used for detecting the polarization llipticity.The extra phase modulation is also performed with the original phase and thus enables measuring singular beams.It is anticipated that the controllable SHE manipulation method may open new avenues in the fields of spin photonics,optical sensing,optical communications,etc.

Training SVMs on a bound vectors set based on Fisher projection

Standard support vector machines （SVMs） train- ing algorithms have O（l3） computational and O（l2） space complexities, where l is the training set size. It is thus com- /putationally infeasible on very large data sets.To alleviate the Computational burden in SVM training, we propose an algo- rithm to train SVMs on a bound vectors set that is extracted based on Fisher projection. For linear separate problems, we use linear Fisher discriminant to compute the projection line, while for non-linear separate problems, we use kernel Fisher discriminant to compute the projection line. For each case, we select a certain ratio samples whose projections are adja- cent to those of the other class as bound vectors. Theoretical analysis shows that the proposed algorithm is with low com- putational and space complexities.Extensive experiments on several classification benchmarks demonstrate the effective- ness of our approach.

Redox switch of ionic transport in conductive polypyrrole-engineered unipolar nanofluidic diodes

Controlling ion transport in nanoconfined spaces is a key task for the creation of smart nanofluidic devices.In this work,redox-active polypyrrole （PPy） polymers are introduced into anodic aluminum oxide （AAO） nanochannels to form smart unipolar nanofluidic diodes （UNDs） for the first time.The ionic transport behavior of the present polypyrrole-engineered UNDs can be controlled through the redox reactions of PPy.Under an applied oxidation potential,conductive PPy exhibits several redox states carrying different charges,following the formation of polarons and bipolarons with different oxidation states.Combined with the asymmetric distribution of PPy in the AAO nanochannels,the UNDs investigated here exhibit redox-switchable ion rectification and ion-gating properties.The influence of the charge asymmetry of the UNDs on their ionic transport behavior is assessed by precisely controlling the length of oxidized PPy segments in the AAO nanochannels and by carrying out theoretical simulations based on the Poisson and Nernst-Planck （PNP） equations.

Neural network-based surrogate model for inverse design of metasurfaces

Metasurfaces composed of spatially arranged ultrathin subwavelength elements are promising photonic devices for manipulating optical wavefronts,with potential applications in holography,metalens,and multiplexing communications.Finding microstructures that meet light modulation requirements is always a challenge in designing metasurfaces,where parameter sweep,gradient-based inverse design,and topology optimization are the most commonly used design methods in which the massive electromagnetic iterations require the design computational cost and are sometimes prohibitive.Herein,we propose a fast inverse design method that combines a physicsbased neural network surrogate model(NNSM)with an optimization algorithm.The NNSM,which can generate an accurate electromagnetic response from the geometric topologies of the meta-atoms,is constructed for electromagnetic iterations,and the optimization algorithm is used to search for the on-demand meta-atoms from the phase library established by the NNSM to realize an inverse design.This method addresses two important problems in metasurface design:fast and accurate electromagnetic wave phase prediction and inverse design through a single phase-shift value.As a proof-of-concept,we designed an orbital angular momentum(de)multiplexer based on a phase-type metasurface,and 200 Gbit/s quadrature-phase shift-keying signals were successfully transmitted with a bit error rate approaching 1.67×10^(-6).Because the design is mainly based on an optimization algorithm,it can address the“one-to-many”inverse problem in other micro/nano devices such as integrated photonic circuits,waveguides,and nano-antennas.