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。

基于改进Node2vec算法的锅炉温度场分割方法研究

针对温度场特征参数差异引发的锅炉温度场分割准确性的问题,以维持温度场特征为目标,引入图结构表达场数据,通过改进Node2vec算法进行聚类分析,进而实现锅炉温度场的最佳分割。该方法基于多维度的特征信息对锅炉温度场实现分割,能够更准确地保留流场特征。在标准数据集上进行了实验验证,结果表明在具有多维度特征的数据集上,所提方法相比其他对比算法在分割效果方面有提升显著。最后将提出的方法用于分割电站锅炉温度场,结果表明该方法可以很好地捕捉温度场数据中的局部和全局特征,且结果具有较好的精确性。

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。

Advances in the structure design of substrate materials for zinc anode of aqueous zinc ion batteries

Aqueous zinc ion batteries(AZIBs) demonstrate tremendous competitiveness and application prospects because of their abundant resources,low cost, high safety, and environmental friendliness. Although the advanced electrochemical energy storage systems based on zinc ion batteries have been greatly developed, many severe problems associated with Zn anode impede its practical application, such as the dendrite formation,hydrogen evolution, corrosion and passivation phenomenon. To address these drawbacks, electrolytes, separators, zinc alloys, interfacial modification and structural design of Zn anode have been employed at present by scientists. Among them, the structural design for zinc anode is relatively mature, which is generally believed to enhance the electroactive surface area of zinc anode, reduce local current density, and promote the uniform distribution of zinc ions on the surface of anode. In order to explore new research directions, it is crucial to systematically summarize the structural design of anode materials. Herein, this review focuses on the challenges in Zn anode, modification strategies and the three-dimensional(3D) structure design of substrate materials for Zn anode including carbon substrate materials, metal substrate materials and other substrate materials. Finally, future directions and perspectives about the Zn anode are presented for developing high-performance AZIBs.

Exploration and optimization of surgical techniques for laparoscopic transhiatal lower mediastinal lymph node dissection for adenocarcinoma of esophagogastric junction: A prospective IDEAL 2a study with qualitative design

Objective: To explore the change and feasibility of surgical techniques of laparoscopic transhiatal(TH)-lower mediastinal lymph node dissection(LMLND) for adenocarcinoma of the esophagogastric junction(AEG)according to Idea, Development, Exploration, Assessment, and Long-term follow-up(IDEAL) 2a standards.Methods: Patients diagnosed with AEG who underwent laparoscopic TH-LMLND were prospectively included from April 14, 2020, to March 26, 2021. Clinical and pathological information as well as surgical outcomes were quantitatively analyzed. Semistructured interviews with the surgeon after each operation were qualitatively analyzed.Results: Thirty-five patients were included. There were no cases of transition to open surgery, but three cases involved combination with transthoracic surgery. In qualitative analysis, 108 items under three main themes were detected: explosion, dissection, and reconstruction. Revised instruction was subsequently designed according to the change in surgical technique and the cognitive process behind it. Three patients had anastomotic leaks postoperatively, with one classified as Clavien-Dindo Ⅲa.Conclusions: The surgical technique of laparoscopic TH-LMLND is stable and feasible;further IDEAL 2b research is warranted.

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.

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.

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.

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.

Machine learning for membrane design and discovery

Membrane technologies are becoming increasingly versatile and helpful today for sustainable development.Machine Learning(ML),an essential branch of artificial intelligence(AI),has substantially impacted the research and development norm of new materials for energy and environment.This review provides an overview and perspectives on ML methodologies and their applications in membrane design and dis-covery.A brief overview of membrane technologies isfirst provided with the current bottlenecks and potential solutions.Through an appli-cations-based perspective of AI-aided membrane design and discovery,we further show how ML strategies are applied to the membrane discovery cycle(including membrane material design,membrane application,membrane process design,and knowledge extraction),in various membrane systems,ranging from gas,liquid,and fuel cell separation membranes.Furthermore,the best practices of integrating ML methods and specific application targets in membrane design and discovery are presented with an ideal paradigm proposed.The challenges to be addressed and prospects of AI applications in membrane discovery are also highlighted in the end.

Deep Insight of Design,Mechanism,and Cancer Theranostic Strategy of Nanozymes

Since the discovery of enzyme-like activity of Fe3O4 nanoparticles in 2007,nanozymes are becoming the promising substitutes for natural enzymes due to their advantages of high catalytic activity,low cost,mild reaction conditions,good stability,and suitable for large-scale production.Recently,with the cross fusion of nanomedicine and nanocatalysis,nanozyme-based theranostic strategies attract great attention,since the enzymatic reactions can be triggered in the tumor microenvironment to achieve good curative effect with substrate specificity and low side effects.Thus,various nanozymes have been developed and used for tumor therapy.In this review,more than 270 research articles are discussed systematically to present progress in the past five years.First,the discovery and development of nanozymes are summarized.Second,classification and catalytic mechanism of nanozymes are discussed.Third,activity prediction and rational design of nanozymes are focused by highlighting the methods of density functional theory,machine learning,biomimetic and chemical design.Then,synergistic theranostic strategy of nanozymes are introduced.Finally,current challenges and future prospects of nanozymes used for tumor theranostic are outlined,including selectivity,biosafety,repeatability and stability,in-depth catalytic mechanism,predicting and evaluating activities.

Combining lymph node ratio to develop prognostic models for postoperative gastric neuroendocrine neoplasm patients

BACKGROUND Lymph node ratio(LNR)was demonstrated to play a crucial role in the prognosis of many tumors.However,research concerning the prognostic value of LNR in postoperative gastric neuroendocrine neoplasm(NEN)patients was limited.AIM To explore the prognostic value of LNR in postoperative gastric NEN patients and to combine LNR to develop prognostic models.METHODS A total of 286 patients from the Surveillance,Epidemiology,and End Results database were divided into the training set and validation set at a ratio of 8:2.92 patients from the First Affiliated Hospital of Soochow University in China were designated as a test set.Cox regression analysis was used to explore the relationship between LNR and disease-specific survival(DSS)of gastric NEN patients.Random survival forest(RSF)algorithm and Cox proportional hazards(CoxPH)analysis were applied to develop models to predict DSS respectively,and compared with the 8th edition American Joint Committee on Cancer(AJCC)tumornode-metastasis(TNM)staging.RESULTS Multivariate analyses indicated that LNR was an independent prognostic factor for postoperative gastric NEN patients and a higher LNR was accompanied by a higher risk of death.The RSF model exhibited the best performance in predicting DSS,with the C-index in the test set being 0.769[95%confidence interval(CI):0.691-0.846]outperforming the CoxPH model(0.744,95%CI:0.665-0.822)and the 8th edition AJCC TNM staging(0.723,95%CI:0.613-0.833).The calibration curves and decision curve analysis(DCA)demonstrated the RSF model had good calibration and clinical benefits.Furthermore,the RSF model could perform risk stratification and individual prognosis prediction effectively.CONCLUSION A higher LNR indicated a lower DSS in postoperative gastric NEN patients.The RSF model outperformed the CoxPH model and the 8th edition AJCC TNM staging in the test set,showing potential in clinical practice.

Electrolyte Design for Low‑Temperature Li‑Metal Batteries:Challenges and Prospects

Electrolyte design holds the greatest opportunity for the development of batteries that are capable of sub-zero temperature operation.To get the most energy storage out of the battery at low temperatures,improvements in electrolyte chemistry need to be coupled with optimized electrode materials and tailored electrolyte/electrode interphases.Herein,this review critically outlines electrolytes’limiting factors,including reduced ionic conductivity,large de-solvation energy,sluggish charge transfer,and slow Li-ion transportation across the electrolyte/electrode interphases,which affect the low-temperature performance of Li-metal batteries.Detailed theoretical derivations that explain the explicit influence of temperature on battery performance are presented to deepen understanding.Emerging improvement strategies from the aspects of electrolyte design and electrolyte/electrode interphase engineering are summarized and rigorously compared.Perspectives on future research are proposed to guide the ongoing exploration for better low-temperature Li-metal batteries.

Design,test,and verification of in-situ condition preserved coring and analysis system in lunar-based simulation environment

The lunar surface and its deep layers contain abundant resources and valuable information resources,the exploration and exploitation of which are important for the sustainable development of the human economy and society.Technological exploration and research in the field of deep space science,especially lunar-based exploration,is a scientific strategy that has been pursued in China and worldwide.Drilling and sampling are key to accurate exploration of the desirable characteristics of deep lunar resources.In this study,an in-situ condition preserved coring(ICP-Coring)and analysis system,which can be used to test drilling tools and develop effective sampling strategies,was designed.The key features of the system include:(1)capability to replicate the extreme temperature fluctuations of the lunar environment(-185 to 200℃)with intelligent temperature control;(2)ability to maintain a vacuum environment at a scale of 10^(-3) Pa,both under unloaded conditions within Ф580 mm×1000 mm test chamber,and under loaded conditions using Ф400 mm×800 mm lunar rock simulant;(3)application of axial pressures up to 4 MPa and confining pressures up to 3.5 MPa;(4)sample rotation at any angle with a maximum sampling length of 800 mm;and(5)multiple modes of rotary-percussive drilling,controlled by penetration speed and weight on bit(WOB).Experimental studies on the drilling characteristics in the lunar rock simulant-loaded state under different drill bit-percussive-vacuum environment configurations were conducted.The results show that the outgassing rate of the lunar soil simulant is greater than that of the lunar rock simulant and that a low-temperature environment contributes to a reduced vacuum of the lunar-based simulated environment.The rotary-percussive drilling method effectively shortens the sampling time.With increasing sampling depth,the temperature rise of the drilling tools tends to rapidly increase,followed by slow growth or steady fluctuations.The temperature rise energy accumulation of the drill bits under vacuum is more significant than that under atmospheric pressure,approximately 1.47 times higher.The real-time monitored drilling pressure,penetration speed and rotary torque during drilling serve as parameters for discriminating the drilling status.The results of this research can provide a scientific basis for returning samples from lunar rock in extreme lunar-based environments.

Molecular Mechanism and Molecular Design of Lubricating Oil Antioxidants

To overcome the limitations of traditional experimental“trial and error”methods in lubricant additive design,a new molecular design method based on molecular structure parameters is established here.The molecular mechanism of the antioxidant reaction of hindered phenol,diphenylamine,and alkyl sulfide are studied via molecular simulations.Calculation results show that the strong electron-donating ability and high hydrogen-donating activity of the antioxidant molecule and the low hydrogen-abstracting activity of free radicals formed after dehydrogenation are the internal molecular causes of the shielding of phenol and diphenylamine from scavenging peroxy free radicals,and the strong electron-donating ability is the internal molecular cause of the high activity of thioether in decomposing alkyl hydrogen peroxide.Based on this antioxidant molecular mechanism,a molecular design rule of antioxidant is proposed,namely“high EHOMO,large Q(S),low bond dissociation energy BDE(O—H)and BDE(N—H)”.Two new antioxidants,PAS-I and PAS-II,are designed and prepared by chemical bonding of hindered phenol,diphenylamine,and sulfur atoms.Experimental results show that these antioxidants both have excellent antioxidant effects in lubricating oil,and that PAS-II is the superior antioxidant,consistent with theoretical predictions.

Recent advances in cobalt phosphide-based materials for electrocatalytic water splitting:From catalytic mechanism and synthesis method to optimization design

Electrochemical water splitting has long been considered an effective energy conversion technology for trans-ferring intermittent renewable electricity into hydrogen fuel,and the exploration of cost-effective and high-performance electrocatalysts is crucial in making electrolyzed water technology commercially viable.Cobalt phosphide(Co-P)has emerged as a catalyst of high potential owing to its high catalytic activity and durability in water splitting.This paper systematically reviews the latest advances in the development of Co-P-based materials for use in water splitting.The essential effects of P in enhancing the catalytic performance of the hydrogen evolution reaction and oxygen evolution reaction are first outlined.Then,versatile synthesis techniques for Co-P electrocatalysts are summarized,followed by advanced strategies to enhance the electrocatalytic performance of Co-P materials,including heteroatom doping,composite construction,integration with well-conductive sub-strates,and structure control from the viewpoint of experiment.Along with these optimization strategies,the understanding of the inherent mechanism of enhanced catalytic performance is also discussed.Finally,some existing challenges in the development of highly active and stable Co-P-based materials are clarified,and pro-spective directions for prompting the wide commercialization of water electrolysis technology are proposed.

双十字路口交通灯控制Stateflow和App Designer仿真

为培养学生能够独立从事自动化相关领域的工程设计、应用研究,解决自动化领域复杂工程实施过程中遇到的关键技术问题,以双十字路口交通灯为研究对象,为计算机辅助建模与仿真类课程设计了一个综合性教学案例。教学案例主要内容为双十字路口Simulink/Stateflow建模与基于Matlab App Designer的交通灯控制可视化仿真。通过此教学案例的实施,明显提高了学生对Matlab的综合应用和工程设计能力,并为后续课程“单片机原理及应用”和“电气控制和PLC”作铺垫。

Rationally designing electrolyte additives for highly improving cyclability of LiNi_(0.5)Mn_(1.5)O_(4)/Graphite cells

High voltage is necessary for high energy lithium-ion batteries but difficult to achieve because of the highly deteriorated cyclability of the batteries.A novel strategy is developed to extend cyclability of a high voltage lithium-ion battery,LiNi_(0.5)Mn_(1.5)O_(4)/Graphite(LNMO/Graphite)cell,which emphasizes a rational design of an electrolyte additive that can effectively construct protective interphases on anode and cathode and highly eliminate the effect of hydrogen fluoride(HF).5-Trifluoromethylpyridine-trime thyl lithium borate(LTFMP-TMB),is synthesized,featuring with multi-functionalities.Its anion TFMPTMB-tends to be enriched on cathode and can be preferentially oxidized yielding TMB and radical TFMP-.Both TMB and radical TFMP can combine HF and thus eliminate the detrimental effect of HF on cathode,while the TMB dragged on cathode thus takes a preferential oxidation and constructs a protective cathode interphase.On the other hand,LTFMP-TMB is preferentially reduced on anode and constructs a protective anode interphase.Consequently,a small amount of LTFMP-TMB(0.2%)in 1.0 M LiPF6in EC/DEC/EMC(3/2/5,wt%)results in a highly improved cyclability of LNMO/Graphite cell,with the capacity retention enhanced from 52%to 80%after 150 cycles at 0.5 C between 3.5 and 4.8 V.The as-developed strategy provides a model of designing electrolyte additives for improving cyclability of high voltage batteries.

OptoGPT: A foundation model for inverse design in optical multilayer thin film structures

Optical multilayer thin film structures have been widely used in numerous photonic applications.However,existing inverse design methods have many drawbacks because they either fail to quickly adapt to different design targets,or are difficult to suit for different types of structures,e.g.,designing for different materials at each layer.These methods also cannot accommodate versatile design situations under different angles and polarizations.In addition,how to benefit practical fabrications and manufacturing has not been extensively considered yet.In this work,we introduce OptoGPT(Opto Generative Pretrained Transformer),a decoder-only transformer,to solve all these drawbacks and issues simultaneously.