Design Principles and Mechanistic Understandings of Non-Noble-Metal Bifunctional Electrocatalysts for Zinc-Air Batteries

Zinc-air batteries(ZABs)are promising energy storage systems because of high theoretical energy density,safety,low cost,and abundance of zinc.However,the slow multi-step reaction of oxygen and heavy reliance on noble-metal catalysts hinder the practical applications of ZABs.Therefore,feasible and advanced non-noble-metal elec-trocatalysts for air cathodes need to be identified to promote the oxygen catalytic reaction.In this review,we initially introduced the advancement of ZABs in the past two decades and provided an overview of key developments in this field.Then,we discussed the work-ing mechanism and the design of bifunctional electrocatalysts from the perspective of morphology design,crystal structure tuning,interface strategy,and atomic engineering.We also included theoretical studies,machine learning,and advanced characterization technologies to provide a comprehensive understanding of the structure-performance relationship of electrocatalysts and the reaction pathways of the oxygen redox reactions.Finally,we discussed the challenges and prospects related to designing advanced non-noble-metal bifunctional electrocatalysts for ZABs.

Combined Promoting Effects of Specific Organic Functional Groups and Alumina Surface Characteristics for the Design of a Highly Efficient NiMo/Al_(2)O_(3) Hydrodesulfurization Catalyst

To prepare a highly efficient NiMo/Al_(2)O_(3) hydrodesulfurization catalyst,the combined effects of specific organic functional groups and alumina surface characteristics were investigated.First,the correlation between the surface characteristics of four different alumina and the existing Mo species states was established.It was found that the Mo equilibrium adsorption capacity can be used as a specific descriptor to quantitatively evaluate the changes in surface characteristics of different alumina.A lower Mo equilibrium adsorption capacity for alumina means weaker metal-support interaction and the loaded Mo species are easier to transform into MoS2.However,the Mo-O-Al bonds still exist at the metal-support interface.The introduction of cationic surfactant hecadecyl trimethyl ammonium bromide(CTAB)can further improve Mo species dispersion through electrostatic attraction with Mo anions and interaction of its alkyl chain with the alumina surface;meanwhile,the introduction of ethylenediamine tetraacetic acid(EDTA)can complex with Ni ions to enhance the Ni-promoting effect on Mo.Therefore,the NiMo catalyst designed using alumina with lower Mo equilibrium adsorption capacity and the simultaneous addition of EDTA and CTAB exhibits the highest hydrodesulfurization activity for 4,6-dimethyl dibenzothiophene because of its proper metal-support interaction and more well-dispersed Ni-Mo-S active phases.

A Hybrid Level Set Optimization Design Method of Functionally Graded Cellular Structures Considering Connectivity

With the continuous advancement in topology optimization and additive manufacturing(AM)technology,the capability to fabricate functionally graded materials and intricate cellular structures with spatially varying microstructures has grown significantly.However,a critical challenge is encountered in the design of these structures–the absence of robust interface connections between adjacent microstructures,potentially resulting in diminished efficiency or macroscopic failure.A Hybrid Level Set Method(HLSM)is proposed,specifically designed to enhance connectivity among non-uniform microstructures,contributing to the design of functionally graded cellular structures.The HLSM introduces a pioneering algorithm for effectively blending heterogeneous microstructure interfaces.Initially,an interpolation algorithm is presented to construct transition microstructures seamlessly connected on both sides.Subsequently,the algorithm enables the morphing of non-uniform unit cells to seamlessly adapt to interconnected adjacent microstructures.The method,seamlessly integrated into a multi-scale topology optimization framework using the level set method,exhibits its efficacy through numerical examples,showcasing its prowess in optimizing 2D and 3D functionally graded materials(FGM)and multi-scale topology optimization.In essence,the pressing issue of interface connections in complex structure design is not only addressed but also a robust methodology is introduced,substantiated by numerical evidence,advancing optimization capabilities in the realm of functionally graded materials and cellular structures.

Design of dual-functional protic porous ionic liquids for boosting selective extractive desulfurization

Porous ionic liquids have demonstrated excellent performance in the field of separation,attributed to their high specific surface area and efficient mass transfer.Herein,task-specific protic porous ionic liquids(PPILs)were prepared by employing a novel one-step coupling neutralization reaction strategy for extractive desulfurization.The single-extraction efficiency of PPILs reached 75.0%for dibenzothiophene.Moreover,adding aromatic hydrocarbon interferents resulted in a slight decrease in the extraction efficiency of PPILs(from 45.2%to 37.3%,37.9%,and 33.5%),indicating the excellent extraction selectivity of PPILs.The experimental measurements and density functional theory calculations reveal that the surface channels of porous structures can selectively capture dibenzothiophene by the stronger electrophilicity(Eint(HS surface channel/DBT)=-39.8 kcal mol^(-1)),and the multiple extraction sites of ion pairs can effectively enrich and transport dibenzothiophene from the oil phase into PPILs throughπ...π,C-H...πand hydrogen bonds interactions.Furthermore,this straightforward synthetic strategy can be employed in preparing porous liquids,offering new possibilities for synthesizing PPILs with tailored functionalities.

Rational design of natural leather-based water evaporator for electricity generation and functional applications

In recent years,water evaporation-induced electricity has attracted a great deal of attention as an emerging green and renewable energy harvesting technology.Although abundant materials have been developed to fabricate hydrovoltaic devices,the limitations of high costs,inconvenient storage and transport,low environmental benefits,and unadaptable shape have restricted their wide applications.Here,an electricity generator driven by water evaporation has been engineered based on natural biomass leather with inherent properties of good moisture permeability,excellent wettability,physicochemical stability,flexibility,and biocompatibility.Including numerous nano/microchannels together with rich oxygen-bearing functional groups,the natural leather-based water evaporator,Leather_(Emblic-NPs-SA/CB),could continuously produce electricity even staying outside,achieving a maximum output voltage of∼3 V with six-series connection.Furthermore,the leather-based water evaporator has enormous potential for use as a flexible self-powered electronic floor and seawater demineralizer due to its sensitive pressure sensing ability as well as its excellent photothermal conversion efficiency(96.3%)and thus fast water evaporation rate(2.65 kg m^(−2)h^(−1)).This work offers a new and functional material for the construction of hydrovoltaic devices to harvest the sustained green energy from water evaporation in arbitrary ambient environments,which shows great promise in their widespread applications.

Interface Design and Functional Optimization of Chinese Learning Apps Based on User Experience

This research paper investigates the interface design and functional optimization of Chinese learning apps through the lens of user experience.With the increasing popularity of Chinese language learning apps in the era of rapid mobile internet development,users'demands for enhanced interface design and interaction experience have grown significantly.The study aims to explore the influence of user feedback on the design and functionality of Chinese learning apps,proposing optimization strategies to improve user experience and learning outcomes.By conducting a comprehensive literature review,utilizing methods such as surveys and user interviews for data collection,and analyzing user feedback,this research identifies existing issues in the interface design and interaction experience of Chinese learning apps.The results present user opinions,feedback analysis,identified problems,improvement directions,and specific optimization strategies.The study discusses the potential impact of these optimization strategies on enhancing user experience and learning outcomes,compares findings with previous research,addresses limitations,and suggests future research directions.In conclusion,this research contributes to enriching the design theory of Chinese learning apps,offering practical optimization recommendations for developers,and supporting the continuous advancement of Chinese language learning apps.

Joint Beamforming Design for Dual-Functional Radar-Communication Systems Under Beampattern Gain Constraints

The joint beamforming design challenge for dual-functional radar-communication systems is addressed in this paper.The base station in these systems is tasked with simultaneously sending shared signals for both multi-user communication and target sensing.The primary objective is to maximize the sum rate of multi-user communication,while also ensuring sufficient beampattern gain at particular angles that are of interest for sensing,all within the constraints of the transmit power budget.To tackle this complex non-convex problem,an effective algorithm that iteratively optimizes the joint beamformers is developed.This algorithm leverages the techniques of fractional programming and semidefinite relaxation to achieve its goals.The numerical results confirm the effectiveness of the proposed algorithm.

水田动力底盘逆向建模与质心验证——基于Geomagic Design X

针对目前农业机械仿真和优化模型精度不高的问题,提出了一种构建精确模型的逆向建模方法。应用光学扫描仪采集点云数据,基于Geomagic Design X处理点云数据并重构零部件模型,在SolidWorks中完成水田动力底盘的装配。以VP6D-CQ型水田动力底盘为例,将测得的实际质心位置与所建的模型质心位置进行比较,并对提出的逆向建模方法进行了试验验证以及误差分析。结果表明:总质量、x坐标、y坐标、z坐标的误差值分别为4.55%、3.62%、2.23%、4.81%,误差值均在5%内。此方法可构建准确的三维模型,为后续仿真优化数据精确性奠定了基础,与传统的研发相比较,可缩短农业机械研发周期、降低设计成本。

App Designer辅助教学方法探索与实践——以软件无线电课程为例

软件无线电作为通信学科的必修课程,具有承上启下的重要作用。因课程原理抽象、理论公式复杂,学员在学习过程存在理解掌握难、实践应用难等问题。通过对当前软件无线电教学过程中存在的不足与困难进行分析,提出利用MATLAB App Designer辅助课程教学,从教学准备、课堂互动、自主实验、反馈提升四个方面开展课程教学改革。实践表明,该方法对于提升学员的工程思维、系统思维具有显著效果,同时可以增强学员理论联系实际的能力。

Unconventional Designs for Functional Sodium-Sulfur Batteries

Sodium-sulfur(Na–S)batteries that utilize earth-abundant materials of Na and S have been one of the hottest topics in battery research.The low cost and high energy density make them promising candidates for next-generation storage technologies as required in the grid and renewable energy.In recent years,extensive efforts have been devoted to the diversity and functionalities of Na–S batteries,aiming to extend their potential applications across multiple temporal and spatial dimensions.Here,we summarize the unconventional designs for the functionalities of Na–S batteries such as flexible batteries,solid-state cells,flame resistance,and operation at extreme temperatures.By highlighting these design strategies that help to realize the functionalities,we hope this review offers a pathway to foster the bright future of Na–S batteries in diverse applications.

The action mechanisms and structures designs of F-containing functional materials for high performance oxygen electrocatalysis

Non-renewable fossil fuels have led to serious problems such as global warming,environmental pollution,etc.Oxygen electrocatalysis including oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)plays a central role in clean energy conversion,enabling a number of sustainable processes for future air battery technologies.Fluorine,as the most electronegative element(4.0)not only can induce more efficient regulation for the electronic structure,but also can bring more abundant defects and other novel effects in materials selection and preparation for favorable catalysis with respect to the other nonmetal elements.However,an individual and comprehensive overview of fluorine-containing functional materials for oxygen electrocatalysis field is still blank.Therefore,it is very meaningful to review the recent progresses of fluorine-containing oxygen electrocatalysts.In this review,we first systematically summarize the controllable preparation methods and their possible development directions based on fluorine-containing materials from four preparation methods.Due to the strong electron-withdrawing properties of fluorine,its control of the electronic structure can effectively enhance the oxygen electrocatalytic activity of the materials.In addition,the catalytic enhancement effect of fluorine on carbonbased materials also includes the prevent oxidation and the layer peeling,and realizes the precise atomic control.And the catalytic improvement mechanism of fluorine containing metal-based compounds also includes the hydration of metal site,the crystal transformation,and the oxygen vacancy induction.Then,based on their various dimensions(0D–3D),we also have summarized the advantages of different morphologies on oxygen electrocatalytic performances.Finally,the prospects and possible future researching direction of F-containing oxygen electrocatalysts are presented(e.g.,novel pathways,advanced methods for measurement and simulation,field assistance and multi-functions).The review is considered valuable and helpful in exploring the novel designs and mechanism analyses of advanced fluorine-containing electrocatalysts.

Multifunctional Perovskite Photodetectors: From Molecular-Scale Crystal Structure Design to Micro/Nano-scale Morphology Manipulation

Multifunctional photodetectors boost the development of traditional optical communication technology and emerging artificial intelligence fields, such as robotics and autonomous driving. However, the current implementation of multifunctional detectors is based on the physical combination of optical lenses, gratings, and multiple photodetectors, the large size and its complex structure hinder the miniaturization, lightweight, and integration of devices. In contrast, perovskite materials have achieved remarkable progress in the field of multifunctional photodetectors due to their diverse crystal structures, simple morphology manipulation, and excellent optoelectronic properties. In this review, we first overview the crystal structures and morphology manipulation techniques of perovskite materials and then summarize the working mechanism and performance parameters of multifunctional photodetectors. Furthermore, the fabrication strategies of multifunctional perovskite photodetectors and their advancements are highlighted, including polarized light detection, spectral detection, angle-sensing detection, and selfpowered detection. Finally, the existing problems of multifunctional detectors and the perspectives of their future development are presented.

CIDP: a multi-functional platform for designing CRISPR sgRNAs

Dear Editor,Compared with traditional technologies affecting gene expression,changing DNA sequences of target genes is one of the most outstanding characters of CRISPR(Clustered Regularly Interspaced Short Palindromic Repeats).Single-guide RNAs(sgRNAs)guiding endonuclease Cas to target sites is a crucial step of CRISPR-Cas system for changing DNA sequences.An ideal sgRNA should only bind to the target gene.However,similar sequences of non-target sites can also be recognized leading to off-target effects[1].

Combining stochastic density functional theory with deep potential molecular dynamics to study warm dense matter

In traditional finite-temperature Kohn–Sham density functional theory(KSDFT),the partial occupation of a large number of high-energy KS eigenstates restricts the use of first-principles molecular dynamics methods at extremely high temperatures.However,stochastic density functional theory(SDFT)can overcome this limitation.Recently,SDFT and the related mixed stochastic–deterministic density functional theory,based on a plane-wave basis set,have been implemented in the first-principles electronic structure software ABACUS[Q.Liu and M.Chen,Phys.Rev.B 106,125132(2022)].In this study,we combine SDFT with the Born–Oppenheimer molecular dynamics method to investigate systems with temperatures ranging from a few tens of eV to 1000 eV.Importantly,we train machine-learning-based interatomic models using the SDFT data and employ these deep potential models to simulate large-scale systems with long trajectories.Subsequently,we compute and analyze the structural properties,dynamic properties,and transport coefficients of warm dense matter.

Alloy design for laser powder bed fusion additive manufacturing:a critical review

Metal additive manufacturing(AM)has been extensively studied in recent decades.Despite the significant progress achieved in manufacturing complex shapes and structures,challenges such as severe cracking when using existing alloys for laser powder bed fusion(L-PBF)AM have persisted.These challenges arise because commercial alloys are primarily designed for conventional casting or forging processes,overlooking the fast cooling rates,steep temperature gradients and multiple thermal cycles of L-PBF.To address this,there is an urgent need to develop novel alloys specifically tailored for L-PBF technologies.This review provides a comprehensive summary of the strategies employed in alloy design for L-PBF.It aims to guide future research on designing novel alloys dedicated to L-PBF instead of adapting existing alloys.The review begins by discussing the features of the L-PBF processes,focusing on rapid solidification and intrinsic heat treatment.Next,the printability of the four main existing alloys(Fe-,Ni-,Al-and Ti-based alloys)is critically assessed,with a comparison of their conventional weldability.It was found that the weldability criteria are not always applicable in estimating printability.Furthermore,the review presents recent advances in alloy development and associated strategies,categorizing them into crack mitigation-oriented,microstructure manipulation-oriented and machine learning-assisted approaches.Lastly,an outlook and suggestions are given to highlight the issues that need to be addressed in future work.

Web Layout Design of Large Cavity Structures Based on Topology Optimization

Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topologyoptimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By usingthe variable density method, lightweight design is achieved without compromising structural strength. Theoptimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivityfiltering and projection to obtain a robust optimized configuration. The mechanical properties are checked bycomparing the stress distribution and displacement of the unoptimized and optimized structures under the sameload. The results confirm that the optimized structures exhibit improved mechanical properties, thus offering keyinsights for engineering lightweight, high-strength large cavity structures.

Accelerated design of high-performance Mg-Mn-based magnesium alloys based on novel bayesian optimization

Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.

Tailoring MXene Thickness and Functionalization for Enhanced Room‑Temperature Trace NO_(2) Sensing

In this study,precise control over the thickness and termination of Ti3C2TX MXene flakes is achieved to enhance their electrical properties,environmental stability,and gas-sensing performance.Utilizing a hybrid method involving high-pressure processing,stirring,and immiscible solutions,sub-100 nm MXene flake thickness is achieved within the MXene film on the Si-wafer.Functionalization control is achieved by defunctionalizing MXene at 650℃ under vacuum and H2 gas in a CVD furnace,followed by refunctionalization with iodine and bromine vaporization from a bubbler attached to the CVD.Notably,the introduction of iodine,which has a larger atomic size,lower electronegativity,reduce shielding effect,and lower hydrophilicity(contact angle:99°),profoundly affecting MXene.It improves the surface area(36.2 cm^(2) g^(-1)),oxidation stability in aqueous/ambient environments(21 days/80 days),and film conductivity(749 S m^(-1)).Additionally,it significantly enhances the gas-sensing performance,including the sensitivity(0.1119Ωppm^(-1)),response(0.2% and 23%to 50 ppb and 200 ppm NO_(2)),and response/recovery times(90/100 s).The reduced shielding effect of the–I-terminals and the metallic characteristics of MXene enhance the selectivity of I-MXene toward NO2.This approach paves the way for the development of stable and high-performance gas-sensing two-dimensional materials with promising prospects for future studies.

Functional biomaterials for modulating the dysfunctional pathological microenvironment of spinal cord injury

Spinal cord injury(SCI)often results in irreversible loss of sensory and motor functions,and most SCIs are incurable with current medical practice.One of the hardest challenges in treating SCI is the development of a dysfunctional pathological microenvironment,which mainly comprises excessive inflammation,deposition of inhibitory molecules,neurotrophic factor deprivation,glial scar formation,and imbalance of vascular function.To overcome this challenge,implantation of functional biomaterials at the injury site has been regarded as a potential treatment for modulating the dysfunctional microenvironment to support axon regeneration,remyelination at injury site,and functional recovery after SCI.This review summarizes characteristics of dysfunctional pathological microenvironment and recent advances in biomaterials as well as the technologies used to modulate inflammatory microenvironment,regulate inhibitory microenvironment,and reshape revascularization microenvironment.Moreover,technological limitations,challenges,and future prospects of functional biomaterials to promote efficient repair of SCI are also discussed.This review will aid further understanding and development of functional biomaterials to regulate pathological SCI microenvironment.

Inverse design of mechanical metamaterial achieving a prescribedconstitutive curve

Besides exhibiting excellent capabilities such as energy absorption,phase-transforming metamaterials offer a vast design space for achieving nonlinear constitutive relations.This is facilitated by switching between different patterns under deformation.However,the related inverse design problem is quite challenging,due to the lack of appropriate mathematical formulation and the convergence issue in the post-buckling analysis of intermediate designs.In this work,periodic unit cells are explicitly described by the moving morphable voids method and effectively analyzed by eliminating the degrees of freedom in void regions.Furthermore,by exploring the Pareto frontiers between error and cost,an inverse design formulation is proposed for unit cells.This formulation aims to achieve a prescribed constitutive curve and is validated through numerical examples and experimental results.The design approach presented here can be extended to the inverse design of other types of mechanical metamaterials with prescribed nonlinear effective properties.