{"title":"ZnFe2O4/TiO2纳米复合材料的合成与优化","authors":"I. Vashistha, Sunil Rohilla","doi":"10.1063/1.5122518","DOIUrl":null,"url":null,"abstract":"Nanocomposite of ZnFe2O4/TiO2 was synthesized by sol-gel method. Fractional Factorial Design was used to investigate the effect of the process (synthesis) parameters like concentration of precursors and annealing temperature on the particle size of resultant composite. Response surface method (RSM) was used to investigate the design of the creation process and the statistical analysis of the effect of process parameters. The RSM results were then used as objective functions for optimization of the response parameters. In the experimental design, quadratic polynomial model was fitted to predict the response value and the best fitted linear model was statistically tested through analysis of variance (ANOVA). The model validity was analyzed through the analysis of residuals.Nanocomposite of ZnFe2O4/TiO2 was synthesized by sol-gel method. Fractional Factorial Design was used to investigate the effect of the process (synthesis) parameters like concentration of precursors and annealing temperature on the particle size of resultant composite. Response surface method (RSM) was used to investigate the design of the creation process and the statistical analysis of the effect of process parameters. The RSM results were then used as objective functions for optimization of the response parameters. In the experimental design, quadratic polynomial model was fitted to predict the response value and the best fitted linear model was statistically tested through analysis of variance (ANOVA). The model validity was analyzed through the analysis of residuals.","PeriodicalId":7262,"journal":{"name":"ADVANCES IN BASIC SCIENCE (ICABS 2019)","volume":"33 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Synthesis and optimization of ZnFe2O4/TiO2 nanocomposite\",\"authors\":\"I. Vashistha, Sunil Rohilla\",\"doi\":\"10.1063/1.5122518\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nanocomposite of ZnFe2O4/TiO2 was synthesized by sol-gel method. Fractional Factorial Design was used to investigate the effect of the process (synthesis) parameters like concentration of precursors and annealing temperature on the particle size of resultant composite. Response surface method (RSM) was used to investigate the design of the creation process and the statistical analysis of the effect of process parameters. The RSM results were then used as objective functions for optimization of the response parameters. In the experimental design, quadratic polynomial model was fitted to predict the response value and the best fitted linear model was statistically tested through analysis of variance (ANOVA). The model validity was analyzed through the analysis of residuals.Nanocomposite of ZnFe2O4/TiO2 was synthesized by sol-gel method. Fractional Factorial Design was used to investigate the effect of the process (synthesis) parameters like concentration of precursors and annealing temperature on the particle size of resultant composite. Response surface method (RSM) was used to investigate the design of the creation process and the statistical analysis of the effect of process parameters. The RSM results were then used as objective functions for optimization of the response parameters. In the experimental design, quadratic polynomial model was fitted to predict the response value and the best fitted linear model was statistically tested through analysis of variance (ANOVA). The model validity was analyzed through the analysis of residuals.\",\"PeriodicalId\":7262,\"journal\":{\"name\":\"ADVANCES IN BASIC SCIENCE (ICABS 2019)\",\"volume\":\"33 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ADVANCES IN BASIC SCIENCE (ICABS 2019)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1063/1.5122518\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ADVANCES IN BASIC SCIENCE (ICABS 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1063/1.5122518","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Synthesis and optimization of ZnFe2O4/TiO2 nanocomposite
Nanocomposite of ZnFe2O4/TiO2 was synthesized by sol-gel method. Fractional Factorial Design was used to investigate the effect of the process (synthesis) parameters like concentration of precursors and annealing temperature on the particle size of resultant composite. Response surface method (RSM) was used to investigate the design of the creation process and the statistical analysis of the effect of process parameters. The RSM results were then used as objective functions for optimization of the response parameters. In the experimental design, quadratic polynomial model was fitted to predict the response value and the best fitted linear model was statistically tested through analysis of variance (ANOVA). The model validity was analyzed through the analysis of residuals.Nanocomposite of ZnFe2O4/TiO2 was synthesized by sol-gel method. Fractional Factorial Design was used to investigate the effect of the process (synthesis) parameters like concentration of precursors and annealing temperature on the particle size of resultant composite. Response surface method (RSM) was used to investigate the design of the creation process and the statistical analysis of the effect of process parameters. The RSM results were then used as objective functions for optimization of the response parameters. In the experimental design, quadratic polynomial model was fitted to predict the response value and the best fitted linear model was statistically tested through analysis of variance (ANOVA). The model validity was analyzed through the analysis of residuals.