Process Parameters Optimization of Laser Cladding for HT200 with 316L Coating Based on Response Surface Method

In order to improve the sealing surface performance of gray cast iron gas gate valves and achieve precise molding control of the cladding layer,as well as to reveal the influence of laser cladding process parameters on the morphology and structure of the cladding layer,we prepared the 316L coating on HT 200 by using Design-Expert software central composite design(CCD)based on response surface analysis.We built a regression prediction model and analyzed the ANOVA with the inspection results.With a target cladding layer width of 3.5 mm and height of 1.3 mm,the process parameters were optimized to obtain the best combination of process parameters.The microstructure,phases,and hardness variations of the cladding layer from experiments with optimal parameters were analyzed by the metallographic microscope,confocal microscope,and microhardness instrument.The experimental results indicate that laser power has a significant impact on the cladding layer width,followed by powder feed rate;scan speed has a significant impact on the cladding layer height,followed by powder feed rate.The HT200 substrate and 316L can metallurgically bond well,and the cladding layer structure consists of dendritic crystals,columnar crystals,and equiaxed crystals in sequence.The optimal process parameter combination satisfying the morphology requirements is laser power(A)of 1993 W,scan speed(B)of 8.949 mm/s,powder feed rate(C)of 1.408 r/min,with a maximum hardness of 1564.3 HV0.5,significantly higher than the hardness of the HT200 substrate.

Optimization and Characterization of Cellulose Extraction from Grevillea robusta (Silky Oak) Leaves by Soda-Anthraquinone Pulping Using Response Surface Methodology

Response surface methodology (RSM) using the central composite design (CCD) was applied to examine the impact of soda-anthraquinone pulping conditions on Grevillea robusta fall leaves. The pulping factors studied were: NaOH charge 5% to 20% w/v, pulping time 30 to 180 minutes, and the anthraquinone charge 0.1 to 0.5% w/w based on the oven-dried leaves. The responses evaluated were the pulp yield, cellulose content, and the degree of delignification. Various regression models were used to evaluate the effects of varying the pulping conditions. The optimum conditions attained were;NaOH charge of 14.63%, 0.1% anthraquinone, and a pulping period of 154 minutes, corresponding to 20.68% pulp yield, 80.56% cellulose content, and 70.34% lignin removal. Analysis of variance (ANOVA), was used to determine the most important variables that improve the extraction process of cellulose. The experiment outcomes matched those predicted by the model (Predicted R2 = 0.9980, Adjusted R2 = 0.9994), demonstrating the adequacy of the model used. FTIR analysis confirmed the elimination of the non-cellulosic fiber constituents. The lignin and hemicellulose-related bands (around 1514 cm−1, 1604 cm−1, 1239 cm−1, and 1734 cm−1) decreased with chemical treatment, indicating effective cellulose extraction by the soda-anthraquinone method. Similar results were obtained by XRD, SEM and thermogravimetric analysis of the extracted cellulose. Therefore, Grevillea robusta fall leaves are suitable renewable, cost-effective, and environmentally friendly non-wood biomass for cellulose extraction.

Optimization of Preparation of Oregano Oil Microspheres by Box-Behnken Response Surface Methodology

[Objectives]To optimize the formulation and preparation of oregano oil microspheres by Box-Behnken response surface methodology.[Methods]Chitosan was used as the carrier material to prepare oregano oil microspheres by emulsion crosslinking method.The encapsulation efficiency,drug loading and ID 50 were used as the evaluation indicators,and the comprehensive score(OD)obtained by"coefficient of variation-AHP comprehensive weighting method"was used as the final evaluation indicator.The formulation design and preparation process were optimized by single factor experiment and Box-Behnken response surface methodology,and the optimal process parameters were determined.[Results]The optimal formulation and preparation process parameters of oregano oil microspheres were as follows:the ratio of oregano oil to chitosan was 2∶1,the emulsifying speed of double emulsion was 200 r/min,the amount of emulsifier in the colostrum was 4%,and the volume of curing agent was 1.0 mL.The average encapsulation efficiency was 45.33%±1.32%,the average drug loading was 30.59%±2.45%,and the median diameter(ID 50)was 52.596μm±0.023%.[Conclusions]The encapsulation efficiency,drug loading and ID 50 of oregano oil chitosan microspheres prepared by emulsion crosslinking method met the requirements.The drug-loaded microsphere not only can be used as a preparation finished product for direct application,but also be used as a product intermediate to lay a foundation for the research and development of subsequent dosage forms.

Optimization of Enzymatic Extraction Process of Polysaccharides from Pseudostellaria heterophylla Fibrous Roots by Response Surface Methodology and Its Pilot Application

[Objectives]To study and optimize the process conditions of enzymatic hydrolysis technology for extracting polysaccharides from Pseudostellaria heterophylla fibrous roots and its application in workshop pilot tests.[Methods]P.heterophylla fibrous roots were taken as the matrix material,and Box Behnken design was used to analyze the extraction time,composite enzyme addition amount,and liquid-solid ratio for response surface optimization experiments,and then applied to the pilot extraction of P.heterophylla fibrous roots.[Results]Response surface analysis showed that all factors had a significant impact on the experimental indicators.The optimal extraction process conditions for polysaccharides from P.heterophylla fibrous roots were extraction time of 2.7 h,compound enzyme addition of 2.5%,and liquid-solid ratio of 32.The yield of polysaccharides from P.heterophylla fibrous roots was 4.83%.The water extraction process of P.heterophylla fibrous roots extraction pilot was used as the control group for response surface optimization of the pilot experiment.The optimization results showed that the extraction time was 3 h,the amount of composite enzyme added was 2.5%,and the liquid-solid ratio was 28.The polysaccharide yield was 4.75%,an increase of 4.63%compared to the control group.[Conclusions]This paper could provide feasibility for the innovation of enzy-matic hydrolysis technology for P.heterophylla fibrous roots and its workshop pilot practice application,as well as a reference for the industrial application of its medicinal resources.

Optimization of Methylene Blue Dye Adsorption onto Coconut Husk Cellulose Using Response Surface Methodology: Adsorption Kinetics, Isotherms and Reusability Studies

In this study, coconut husk cellulose was employed as a cost-effective and environmentally friendly adsorbent to eliminate methylene blue (MB) dye from aqueous solutions. The successful development of response surface methodology paired with a central composite design (RSM-CCD) enabled the optimization and modelling of the adsorption process. The study investigated the individual and combined effects of three variables (pH, contact time, and initial MB dye concentration) on the adsorption of MB dye onto coconut husk cellulose. The developed RSM-CCD model exhibited a remarkable degree of precision in predicting the removal efficiency of MB dye within the specified experimental parameters. This was demonstrated by the strong regression parameters, with an R2 value of 99.79% and an adjusted R2 value of 99.6%. The study depicted that the optimal parameters for attaining a 98.8827% removal of MB dye using coconut husk cellulose were as follows: an initial MB dye concentration of 30 mg∙L−1, contact time of 120 minutes, and pH 7 at a fixed adsorbent dose of 0.5 g. The Freundlich isotherm model provided the most satisfactory description of the equilibrium adsorption isotherms, suggesting that MB dye adsorption onto coconut husk cellulose occurs on a heterogeneous surface. The experimental results demonstrated a strong agreement with the pseudo-second-order kinetics model, indicating that the number of active sites present on the cellulose adsorbent predominantly influences the adsorption process of MB dye. Additionally, the adsorbent made from coconut husk cellulose exhibited the potential to be reused, as it retained its efficiency for a maximum of three cycles of adsorption of MB dye. The results of this study show that coconut husk cellulose has the potential to be an effective and sustainable adsorbent for removing MB dye from aqueous solutions.

Optimization of Cellulose Nanocrystal Isolation from Ayous Sawdust Using Response Surface Methodology

This study focuses on the extraction of cellulose nanocrystals (CNC), from microcrystalline cellulose (MCC), derived from Ayous sawdust. The process involves multiple steps and a large amount of chemical products. The objective of this research was to determine the effects of factors that impact the isolation process and to identify the optimal conditions for CNC isolation by using the response surface methodology. The factors that varied during the process were the quantity of MCC, the concentration of sulfuric acid, the hydrolysis time and temperature, and the ultrasonic treatment time. The response measured was the yield. The study found that with 5.80 g of microcrystalline cellulose, a sulfuric acid concentration of 63.50% (w/w), a hydrolysis time of 53 minutes, a hydrolysis temperature of 69˚C, and a sonication time of 19 minutes are the ideal conditions for isolation. The experimental yield achieved was (37.84 ± 0.99) %. The main factors influencing the process were the sulfuric acid concentration, hydrolysis time and temperature, with a significant influence (p < 0.05). Infrared characterization results showed that nanocrystals were indeed isolated. With a crystallinity of 35.23 and 79.74, respectively, for Ayous wood fiber and nanocrystalline cellulose were observed by X-ray diffraction, with the formation of type II cellulose, thermodynamically more stable than native cellulose type I.

Cooperative User-Scheduling and Resource Allocation Optimization for Intelligent Reflecting Surface Enhanced LEO Satellite Communication

Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.

Modeling of Tuna Fish Frying Using Response Surface Methodology in the Production of Attieke “Garba” Dish in Côte D’Ivoire

With the aim of optimizing the factors which act on the frying of the fish dish “Garba”, a study using the response surface methodology was carried out. After an appropriate choice of three variables, 15 experiments led to three second-order mathematical models linking the responses (temperature, number of reuses, frying time) to the factors and allowing good control of the frying process. After carrying out the tests and analyzing the data, the study provided knowledge of the optimal conditions necessary for frying while preserving the quality of the oil. The optimal point region for maintaining this quality is obtained when the temperature is 160˚C at frying times of 7.5 minutes for only 5 reuses of the oil.

Fiber Bundle Topology Optimization for Surface Flows

This paper presents a topology optimization approach for the surface flows on variable design domains.Via this approach,the matching between the pattern of a surface flow and the 2-manifold used to define the pattern can be optimized,where the 2-manifold is implicitly defined on another fixed 2-manifold named as the base manifold.The fiber bundle topology optimization approach is developed based on the description of the topological structure of the surface flow by using the differential geometry concept of the fiber bundle.The material distribution method is used to achieve the evolution of the pattern of the surface flow.The evolution of the implicit 2-manifold is realized via a homeomorphous map.The design variable of the pattern of the surface flow and that of the implicit 2-manifold are regularized by two sequentially implemented surface-PDE filters.The two surface-PDE filters are coupled,because they are defined on the implicit 2-manifold and base manifold,respectively.The surface Navier-Stokes equations,defined on the implicit 2-manifold,are used to describe the surface flow.The fiber bundle topology optimization problem is analyzed using the continuous adjoint method implemented on the first-order Sobolev space.Several numerical examples have been provided to demonstrate this approach,where the combination of the viscous dissipation and pressure drop is used as the design objective.

The Influence of Tartaric Acid in the Silver Nanoparticle Synthesis Using Response Surface Methodology

Silver nanoparticles(AgNPs)synthesized using tartaric acid as a capping agent have a great impact on the reaction kinetics and contribute significantly to the stability of AgNPs.The protective layer formed by tartaric acid is an important factor that protects the silver surface and reduces potential cytotoxicity problems.These attributes are critical for assessing the compatibility of AgNPs with biological systems and making them suitable for drug delivery applications.The aim of this research is to conduct a comprehensive study of the effect of tartaric acid concentration,sonication time and temperature on the formation of silver nanoparticles.Using Response Surface Methodology(RSM)with Face-Centered Central Composite Design(FCCD),the optimization process identifies the most favorable synthesis conditions.UV-Vis spectrum regression analysis shows that AgNPs stabilized with tartaric acid are more stable than AgNPs without tartaric acid.This highlights the increased stability that tartaric acid provides in AgNP ssssynthesis.Particle size distribution analysis showed a multimodal distribution for AgNPs with tartaric acid and showed the smallest size peak with an average size of 20.53 nm.The second peak with increasing intensity shows a dominant average size of 108.8 nm accompanied by one standard deviation of 4.225 nm and a zeta potential of−11.08 mV.In contrast,AgNPs synthesized with polyvinylpyrrolidone(PVP)showed a unimodal particle distribution with an average particle size of 81.62 nm and a zeta potential of−2.96 mV.The more negative zeta potential of AgNP-tartaric acid indicates its increased stability.Evaluation of antibacterial activity showed that AgNPs stabilized with tartaric acid showed better performance against E.coli and B.subtilis bacteria compared with AgNPs-PVP.In summary,this study highlights the potential of tartaric acid in AgNP synthesis and suggests an avenue for the development of stable AgNPs with versatile applications.

A novel triple periodic minimal surface-like plate lattice and its data-driven optimization method for superior mechanical properties

Lattice structures can be designed to achieve unique mechanical properties and have attracted increasing attention for applications in high-end industrial equipment,along with the advances in additive manufacturing(AM)technologies.In this work,a novel design of plate lattice structures described by a parametric model is proposed to enrich the design space of plate lattice structures with high connectivity suitable for AM processes.The parametric model takes the basic unit of the triple periodic minimal surface(TPMS)lattice as a skeleton and adopts a set of generation parameters to determine the plate lattice structure with different topologies,which takes the advantages of both plate lattices for superior specific mechanical properties and TPMS lattices for high connectivity,and therefore is referred to as a TPMS-like plate lattice(TLPL).Furthermore,a data-driven shape optimization method is proposed to optimize the TLPL structure for maximum mechanical properties with or without the isotropic constraints.In this method,the genetic algorithm for the optimization is utilized for global search capability,and an artificial neural network(ANN)model for individual fitness estimation is integrated for high efficiency.A set of optimized TLPLs at different relative densities are experimentally validated by the selective laser melting(SLM)fabricated samples.It is confirmed that the optimized TLPLs could achieve elastic isotropy and have superior stiffness over other isotropic lattice structures.

Intelligent Reflecting Surface Assisted Transmission Optimization Strategies in Wireless Networks

Wireless Power Transfer(WPT)technology can provide real-time power for many terminal devices in Internet of Things(IoT)through millimeterWave(mmWave)to support applications with large capacity and low latency.Although the intelligent reflecting surface(IRS)can be adopted to create effective virtual links to address the mmWave blockage problem,the conventional solutions only adopt IRS in the downlink from the Base Station(BS)to the users to enhance the received signal strength.In practice,the reflection of IRS is also applicable to the uplink to improve the spectral efficiency.It is a challenging to jointly optimize IRS beamforming and system resource allocation for wireless energy acquisition and information transmission.In this paper,we first design a Low-Energy Adaptive Clustering Hierarchy(LEACH)clustering protocol for clustering and data collection.Then,the problem of maximizing the minimum system spectral efficiency is constructed by jointly optimizing the transmit power of sensor devices,the uplink and downlink transmission times,the active beamforming at the BS,and the IRS dynamic beamforming.To solve this non-convex optimization problem,we propose an alternating optimization(AO)-based joint solution algorithm.Simulation results show that the use of IRS dynamic beamforming can significantly improve the spectral efficiency of the system,and ensure the reliability of equipment communication and the sustainability of energy supply under NLOS link.

Optimization for Microbial Degumming of Ramie with Bacillus subtilis DZ_(5) in Submerged Fermentation by Orthogonal Array Design and Response Surface Methodology

As a kind of natural fiber,ramie fiber has distinctive advantages in textile application,but the application is limited due to the traditional degumming mode.Compared with the traditional degumming process,the microbial degumming process has many advantages.To obtain the optimal conditions for degumming ramie with Bacillus subtilis DZ_(5)(BS DZ_(5)),a combined statistical approach of orthogonal array design(OAD)and response surface methodology(RSM)was used.The influences of initial pH of the bacteria medium,culture temperature,shaking speed,degumming time and inoculum size on submerged fermentation degumming were evaluated by using fractional factorial design.The main factors in the analysis were culture temperature,shaking speed and initial pH.The residual gum mass fraction was used as the optimization index,and the optimal conditions for degumming were determined by central composite design and RSM.Thus with only a limited number of experiments,an optimal ramie microbial degumming condition was found as the culture temperature of 40℃,the initial pH in the culture medium of 8.5,the shaking speed of 205 r/min,the degumming time of 96 h and the inoculum size of 5%.After microbial degumming of ramie under the optimal conditions,there was only 10.6%residual gum by mass in the fiber.In addition,the effective degumming of BS DZ_(5)was also confirmed by a scanning electron microscope(SEM).

Optimizing Bucket Elevator Performance through a Blend of Discrete Element Method, Response Surface Methodology, and Firefly Algorithm Approaches

This research introduces a novel approach to enhancing bucket elevator design and operation through the integration of discrete element method(DEM)simulation,design of experiments(DOE),and metaheuristic optimization algorithms.Specifically,the study employs the firefly algorithm(FA),a metaheuristic optimization technique,to optimize bucket elevator parameters for maximizing transport mass and mass flow rate discharge of granular materials under specified working conditions.The experimental methodology involves several key steps:screening experiments to identify significant factors affecting bucket elevator operation,central composite design(CCD)experiments to further explore these factors,and response surface methodology(RSM)to create predictive models for transport mass and mass flow rate discharge.The FA algorithm is then applied to optimize these models,and the results are validated through simulation and empirical experiments.The study validates the optimized parameters through simulation and empirical experiments,comparing results with DEM simulation.The outcomes demonstrate the effectiveness of the FA algorithm in identifying optimal bucket parameters,showcasing less than 10%and 15%deviation for transport mass and mass flow rate discharge,respectively,between predicted and actual values.Overall,this research provides insights into the critical factors influencing bucket elevator operation and offers a systematic methodology for optimizing bucket parameters,contributing to more efficient material handling in various industrial applications.

Optimization of Photo-Fenton Catalyst Preparation Based Bamboo Carbon Fiber by Response Surface Methodology

In this paper,the residue from bamboo factory has been used to design photo-Fenton catalyst,which has the advantages of low cost and magnetic recycling.The photo-Fenton catalytic performance of the biocarbon-based catalyst was excellent and its optimal preparation process was also explored by response surface methodology.First,bamboo-carbon fiber was selected as the photo-Fenton catalyst carrier.Subsequently,the surface of the car-bon fiber was modified,with which dopamine,nano-Fe_(3)O_(4) and nano-TiO_(2) were successively loaded by hydro-thermal method.After the single factor tests,four factors including dopamine concentration,ferric chloride mass,P25 titanium dioxide mass and liquid-solid ratio were selected as the characteristic values.The degradation efficiency of photo-Fenton catalyst to methylene blue(MB)solution was treated as the response value.After the analysis of the response surface optimization,it was shown that the significance sequence of the selected 4 factors in terms of the MB degradation efficiency was arranged as follows:dopamine concentration>liquid-solid ratio>P25 titanium dioxide quality>ferric chloride quality.The optimal process parameters of fiber-carbon catalyst were affirmed as follows:the 1.7 mg/mL concentration of dopamine,the 1.2 g mass of ferric chloride,the 0.2 g mass of P25 titanium dioxide and the liquid-solid ratio of 170 mL/g.The experiment-measured average MB degra-dation efficiency performed by the optimized catalyst was 99.3%,which was nearly similar to the model-predicted value of 98.9%.It showed that the prediction model and response surface model were accurate and reliable.The results from response surface optimization could provide a good reference to design bamboo-based Fenton-like catalyst with excellent catalytic performance.

Response Surface Optimization of Ultrasound-assisted Aqueous Two-phase Extraction of Sweet Potato Leaf Polysaccharides

[Objectives]The ultrasound-assisted aqueous two-phase extraction of sweet potato leaf polysaccharides was studied.[Methods]With the yield of sweet potato leaf polysaccharides as the index,the aqueous two-phase extraction system was determined,and the optimal extraction conditions were optimized by single-factor experiments and response surface methodology.[Results]The optimal parameters were ethanol concentration 25.68%,liquid-to-material ratio 55.83,and ultrasonic treatment time 38.33 min.Under these conditions,the yield of sweet potato leaf polysaccharides could reach 20.646 mg/g.[Conclusions]The ethanol/ammonium sulfate aqueous system is a rapid and efficient method for extracting sweet potato leaf polysaccharides,which is of great significance for the application of sweet potato leaf extract as a natural food additive.

Mechanical and Permeability Analysis and Optimization of Recycled Aggregate Pervious Concrete Based on Response Surface Method

In this paper,the effects of different influencing factors and factor interaction on the compressive strength and permeability of recycled aggregate pervious concrete(RAPC)were studied based on the response surface method(RSM).By selecting the maximum aggregate size,water cement ratio and target porosity as design variables,combined with laboratory tests and numerical analysis,the influences of three factors on the compressive strength and permeability coefficient of RAPC were revealed.The regression equation of compressive strength and permeability coefficient of recycled aggregate pervious concrete were established based on RSM,and the response surface model was optimized to determine the optimal ratio of RAPC under the conditions of meeting the mechanical and permeability properties.The results show that the mismatch item of the model is not significant,the model is credible,and the accuracy and reliability of the test are high,but the degree of uncorrelation between the test data and the model is not obvious.The sensitivity of the three factors to the compressive strength is water cement ratio>maximum coarse aggregate particle size>target porosity,and the sensitivity to the permeability coefficient is target porosity>maximum coarse aggregate particle size>water cement ratio.The absolute errors of the model prediction results and the model optimization results are 1.28 MPa and 0.19 mm/s,and the relative errors are 5.06%and 4.19%,respectively.With high accuracy,RSM can match the measured results of compressive strength and permeability coefficient of RAPC.

Response Surface Methodology as an Approach for Optimization of Vinegar Fermentation Conditions Using Three Different Thermotolerant Acetic Acid Bacteria

This study aimed to investigate optimal fermentation conditions of biological acetic acid fermentation for vinegar production. Optimization was performed on 3 acetic acid bacteria strains namely VMA1, VMA7 and VMAO using Response Surface Methodology (RSM). A Box-Behnken-Design (BBD) was achieved with three different independent process parameters involving: fermentation temperature, original alcohol concentration and original acetic acid concentration and one dependent variable (acetic acid yield). The results showed that the mathematical models describe correctly the relationship between responses and factors (F values of the models (p R2 (coefficient of correlation) respectively 0.96, 0.94, 0.98, and adjusted R2 0.95, 0.92, 0.98). The maximum acidity was obtained respectively at fermentation temperatures, original alcohol concentrations and original acetic acid concentrations ranging from [37.5°C - 45°C], [16% - 20% (v/v)], [1.5% - 2% (w/v)] for VMA1, [40°C - 45°C], [14.5% - 20% (v/v)], [1.7% - 2% (w/v)] for VMA7 and [42°C - 45°C], [17% - 20% (v/v)], [1.5% - 2% (w/v)] for VMAO. The use of these acetic strains in the production of vinegar may seriously lead to a decrease or even an ablation of the costs related to the cooling of bioreactors especially in warm and hot countries, in the context of global warming.

Optimization of Mortar Compressive Strength Prepared with Waste Glass Aggregate and Coir Fiber Addition Using Response Surface Methodology

Waste Glass(WGs)and Coir Fiber(CF)are not widely utilized,even though their silica and cellulose content can be used to create construction materials.This study aimed to optimize mortar compressive strength using Response Surface Methodology(RSM).The Central Composite Design(CCD)was applied to determine the optimization of WGs and CF addition to the mortar compressive strength.Compressive strength and microstructure testing with Scanning Electron Microscope(SEM),Fourier-transform Infrared Spectroscopy(FT-IR),and X-Ray Diffraction(XRD)were conducted to specify the mechanical ability and bonding between the matrix,CF,and WGs.The results showed that the chemical treatment of CF produced 49.15%cellulose,with an average particle size of 1521μm.The regression of a second-order polynomial model yielded an optimum composition consisting of 12.776%WGs and 2.344%CF with a predicted compressive strength of 19.1023 MPa.C-S-H gels were identified in the mortars due to the dissolving of SiO_(2) in WGs and cement.The silica from WGs increased the C-S-H phase.CF plays a role in preventing,bridging,and branching micro-cracks before reaching maximum stress.WGs aggregates and chemically treated CF are suitable to be composited in mortar to increase compressive strength.

Optimization of Preparation Conditions of Modified Oyster Shell Powder/Ce-N-TiO2 by Response Surface Methodology (RSM)

A new composite photocatalyst of modified oyster shell powder/Ce-N-TiO2 was prepared by sol-gel method. Based on single factor experiment, Ce doping rate, N doping rate and calcination temperature were taken as input variables. Based on the central composite design (BBD) response surface model, two functional relationship models between three independent variables and glyphosate removal rate were established to evaluate the influence degree of independent variables and interaction on catalyst. The significance of the model and regression coefficient was tested by variance analysis. The analysis of the obtained data showed that the degradation performance of the composite photocatalyst was significantly affected by the calcination temperature and the rate of N doping, while the rate of Ce doping had little effect;at the calcination temperature of 505.440°C, the degradation rate of glyphosate reached the maximum of 82.15% under the preparation conditions of 17.057 mol% N doping and 0.165 mol% Ce doping, respectively.