Plackett-Burman Design联用Box-Behnken Design优化香菇酱的工艺

采用Plackett-Burman Design(PBD)与Box-Behnken Design(BBD)优化香菇酱的工艺条件,以获得其最佳制作工艺。在单因素试验基础上,通过PBD筛选出黄豆酱添加量、绵白糖添加量、酵母提取物添加量3个影响香菇酱感官评分的显著因素。采用BBD与主成分分析法对3个显著因素进行条件优化。确定香菇酱最佳工艺配方:以香菇100 g为基准,黄豆酱25%、植物油10%、盐10%、芝麻0.5%、酿造酱油1%、绵白糖4%、谷氨酸钠0.6%、酵母提取物4%、5-呈味核苷酸二钠0.03%、食用香精1%。规范化综合得分为0.968分,与预测值相近。PBD与BBD联合应用,为香菇酱的制作工艺提供一种新方法,既可快速筛选出显著因子,有效优化试验,又能避免浪费试验资源。

Plackett-Burman和Central Composite Design试验设计法优化石榴皮中熊果酸的SFE-CO_2萃取工艺

目的:探讨应用SFE-CO2萃取石榴皮中熊果酸的最佳工艺。方法:以熊果酸得率为考察指标,通过Plackett-Burman(PB)试验设计筛选影响熊果酸得率的显著性因素,最陡爬坡试验逼近熊果酸得率最大区域,Central Composite Design(CCD)试验设计对显著性因素进行响应面优化得到影响熊果酸得率的二阶数学模型,进而得出最佳工艺条件。结果:SFE-CO2萃取石榴皮中熊果酸的最佳工艺条件为:萃取温度46.29℃,萃取时间91.6 min,萃取压力34.49 MPa,在此条件下,验证试验测得熊果酸得率为12.508 mg/g,与模型预测值12.645 mg/g接近。结论:将PB试验和CCD试验设计联合应用于优化石榴皮中熊果酸SFE-CO2萃取工艺,筛选结果具有统计学意义,工艺操作具有可行性。

Optimization of phenol degradation by Candida tropicalis Z-04 using Plackett-Burman design and response surface methodology

Statistical experimental designs were used to optimize the process of phenol degradation by Candida tropicalis Z-04, isolated from phenol-degrading aerobic granules. The most important factors influencing phenol degradation （p 〈 0.05）, as identified by a two-level Plackett-Burman design with 11 variables, were yeast extract, phenol, inoculum size, and temperature. Steepest ascent method was undertaken to determine the optimal regions of these four significant factors. Central composite design （CCD） and response surface analysis were adopted to further investigate the mutual interactions between these variables and to identify their optimal values that would generate maximum phenol degradation. The analysis results indicated that interactions between yeast extract and temperature, phenol and temperature, inocuhim size and temperature affected the response variable （phenol degradation） significantly. The predicted results showed that the maximum removal efficiency of phenol （99.10%） could be obtained under the optimum conditions of yeast extract 0.41 g/L, phenol 1.03 g/L, inoculum size 1.43% （V/V） and temperature 30.04℃. These predicted values were further verified by validation experiments. The excellent correlation between predicted and experimental values confirmed the validity and practicability of this statistical optimum strategy. This study indicated the excellent ability of C. tropicalis Z-04 in degrading high-strength phenol. Optimal conditions obtained in this experiment laid a solid foundation for further use of this microorganism in the treatment of highstrength phenol effluents.

Plackett-Burman Design与均匀设计法优化玫瑰色微球菌固定化脱氮的性能

【目的】采用Plackett-Burman Design(PBD)与均匀设计(Uniform Design,UD)优化玫瑰色微球菌(Micrococcus roseus)固定化脱氮的条件,以提高其脱氮性能。【方法】选择聚乙烯醇(Polyvinyl alcohol,PVA)与海藻酸钠(Sodium alginate,SA)作为固定化细胞材料,研究其成球方式与性能,应用PBD对9个影响脱氮效果的因素进行显著性检验,筛选出PVA、SA、温度、菌液接种量、菌球量5个显著性因素(P<0.05)。采用UD对5个显著因素进行条件优化,优化数据通过Minitab与Matlab软件进行逐步回归分析,并建立二阶多项式模型。【结果】最优脱氮条件为PVA 9.6%、SA 2.2%、温度33.4°C、菌液接种量8%、菌球量500个/100 m L,连续脱氮72 h,最高脱氮率达到60.9%。【结论】PBD与UD的联合使用能够在显著因子筛选与寻优中发挥重要的作用。连续脱氮试验表明,玫瑰色微球菌去除氨氮主要通过同化、硝化与反硝化途径。

基于Altium Designer软件的电子控制技术中电路设计探究

在正常的电路设计方案中,需要软硬件的互相搭配使用,普通的电路运用收稿方式或简单的办公辅助软件来完成绘制,但在面对复杂情况下的电路,专业的EDA辅助设计软件作用可以显而易见,以该辅助软件设计如SCH(电路原理图)与PCB(印制电路板)文件方面的工作。电子控制技术中电路随着时代的进步而不断创新,新型器件的不断迭代更新,其中的电路设计也变得复杂且繁琐,传统的电路设计已无法胜任最新电路的完善和使用。此时运用AD16(Altium Designer)这款辅助设计软件进行电路设计就可以事半功倍,AD都是复杂电路设计中的高效工具。

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。

Evaluation of Medium Components by Plackett-Burman Statistical Design for Lipase Production by Candida rugosa and Kinetic Modeling

Lipase production by Candida rugosa was carried out in submerged fermentation.Plackett-Burman statisticalexperimental design was applied to evaluate the fermentation medium components.The effect of twelve medium components was studied in sixteen experimental trials.Glucose,olive oil,peptone and FeCl3·6H2O were found to have more significance on lipase production by Candida rugosa.Maximum lipase activity of 3.8 u mL-1 was obtained at 50h of fermentation period.The fermentation was carried out at optimized temperature of 3℃,initial pH of 6.8 and shaking speed of 120 r/min.Unstructured kinetic models were used to simulate the experimental data.Logistic model,Luedeking-Piret model and modified Luedeking-Piret model were found suitable to efficiently predict the cell mass,lipase production and glucose consumption respectively with high determination coefficient(R2).From the estimated values of the Luedeking-Piret kinetic model parameters,α and β,it was found that the lipase production by Candida rugosa is growth associated.

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。

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.

Plackett-Burman和Box-Behnken试验优化莫海威芽孢杆菌HXS-LV12产纤维素酶发酵工艺

本试验以莫海威芽孢杆菌HXS-LV12为研究对象,优化其发酵产纤维素酶工艺。首先,通过单因素试验对其发酵工艺(碳源种类、碳源质量浓度、氮源种类、氮源质量浓度、无机盐种类、无机盐质量浓度、转速、接种量、发酵时间、初始pH和发酵温度)进行初步优化,然后通过Plackett-Burman试验,筛选出3个显著影响HXS-LV12产纤维素酶的因素,再利用最陡爬坡试验确定其产纤维素酶的最大响应区域,然后通过Box-Behnken试验确定其最优产纤维素酶工艺。优化工艺条件为羧甲基纤维素钠(CMC-Na)质量浓度32.9 g/L,酵母浸粉(YEP)质量浓度17.6 g/L,磷酸氢二钾质量浓度5.7 g/L,转速190 r/min,接种量6.5%,发酵时间24.0 h,初始pH 7.0,发酵温度33.0℃。在此培养条件下,HXS-LV12产纤维素酶活力达到(40.53±0.43)U/mL,是优化前的2.05倍。

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.

Plackett-Burman设计结合Box-Behnken响应面法筛选草乌甲素纳米乳凝胶贴膏的处方

目的优化草乌甲素纳米乳凝胶贴膏基质的处方。方法在Plackett-Burman设计、最陡爬坡实验的基础上,以甘油、酒石酸、纯化水用量作为变量,以初黏力、持黏力、感官评价的综合评分为评价指标,用Box-Behnken响应面法优化草乌甲素纳米乳凝胶贴膏基质的处方。结果最优处方为甘油用量40.877 g,酒石酸用量0.294 g,纯化水用量42.491 g,综合评分为94.937分。结论建立的方法稳定、可靠、预测性能优良,此方法可用于优化草乌甲素纳米乳凝胶贴膏基质的处方。

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.

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.

Glucocorticoids-based prodrug design:Current strategies and research progress

Attributing to their broad pharmacological effects encompassing anti-inflammation,antitoxin,and immunosuppression,glucocorticoids(GCs)are extensively utilized in the clinic for the treatment of diverse diseases such as lupus erythematosus,nephritis,arthritis,ulcerative colitis,asthma,keratitis,macular edema,and leukemia.However,longterm use often causes undesirable side effects,including metabolic disorders-induced Cushing's syndrome(buffalo back,full moon face,hyperglycemia,etc.),osteoporosis,aggravated infection,psychosis,glaucoma,and cataract.These notorious side effects seriously compromise patients'quality of life,especially in patients with chronic diseases.Therefore,glucocorticoid-based advanced drug delivery systems for reducing adverse effects have received extensive attention.Among them,prodrugs have the advantages of low investment,low risk,and high success rate,making them a promising strategy.In this review,we propose the strategies for the design and summarize current research progress of glucocorticoid-based prodrugs in recent decades,including polymer-based prodrugs,dendrimer-based prodrugs,antibody-drug conjugates,peptide-drug conjugates,carbohydrate-based prodrugs,aliphatic acid-based prodrugs and so on.Besides,we also raise issues that need to be focused on during the development of glucocorticoid-based prodrugs.This review is expected to be helpful for the research and development of novel GCs and prodrugs.

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.