{"title":"使用镀铂聚苯乙烯粗颗粒增强亚甲基蓝降解的界面工程方法:流动调节催化活性和动力学建模","authors":"Faizan Khan , Vishal Singh Pawak , Chandra Shekhar , Venkateshwar Rao Dugyala , Tarak Mondal , Manigandan Sabapathy","doi":"10.1016/j.cscee.2025.101279","DOIUrl":null,"url":null,"abstract":"<div><div>This study explores an efficient decontamination strategy using platinum-coated polystyrene rough-particles as a micron-sized catalyst system for decomposing methylene blue (MB), a common organic pollutant. The synthesized nanomaterials were comprehensively characterized using Nanoparticle Tracking Analysis (NTA), Dynamic Light Scattering (DLS), Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM), and Transmission Electron Microscopy (TEM), confirming their morphology, size distribution, and surface properties. The decontamination was performed at the air-water interface through an interface trapping method, with enhanced mixing achieved under a controlled flow environment. The experiments were conducted with a circulation speed of 50 RPM, corresponding to a Reynolds number (NR<span><math><msub><mrow></mrow><mrow><mi>e</mi></mrow></msub></math></span>) of 1686 and a high particle packing fraction of 0.8. Under these operating conditions, complete degradation of MB was achieved within 30 min, significantly faster than the 75 min required for degradation in the bulk phase. The reaction kinetics were analyzed and found to follow the Langmuir–Hinshelwood model, with an estimated rate constant of 0.018 min<sup>−1</sup>, indicating efficient surface-mediated catalytic activity. Furthermore, an Artificial Neural Network (ANN) model was developed to validate and predict the degradation kinetics, showing a Root Mean Square Error (RMSE) of 5.5 and a high correlation coefficient (R<sup>2</sup>) of 0.9656, confirming the reliability of the predictive model. This interface-assisted, catalyst-based degradation approach demonstrates a promising, reusable, cost-effective, and environmentally friendly solution for advanced wastewater treatment applications.</div></div>","PeriodicalId":34388,"journal":{"name":"Case Studies in Chemical and Environmental Engineering","volume":"12 ","pages":"Article 101279"},"PeriodicalIF":0.0000,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Interfacial engineering approach for enhanced degradation of methylene blue using platinum-coated polystyrene rough particles: Flow-regulated catalytic activity and kinetic modeling\",\"authors\":\"Faizan Khan , Vishal Singh Pawak , Chandra Shekhar , Venkateshwar Rao Dugyala , Tarak Mondal , Manigandan Sabapathy\",\"doi\":\"10.1016/j.cscee.2025.101279\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study explores an efficient decontamination strategy using platinum-coated polystyrene rough-particles as a micron-sized catalyst system for decomposing methylene blue (MB), a common organic pollutant. The synthesized nanomaterials were comprehensively characterized using Nanoparticle Tracking Analysis (NTA), Dynamic Light Scattering (DLS), Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM), and Transmission Electron Microscopy (TEM), confirming their morphology, size distribution, and surface properties. The decontamination was performed at the air-water interface through an interface trapping method, with enhanced mixing achieved under a controlled flow environment. The experiments were conducted with a circulation speed of 50 RPM, corresponding to a Reynolds number (NR<span><math><msub><mrow></mrow><mrow><mi>e</mi></mrow></msub></math></span>) of 1686 and a high particle packing fraction of 0.8. Under these operating conditions, complete degradation of MB was achieved within 30 min, significantly faster than the 75 min required for degradation in the bulk phase. The reaction kinetics were analyzed and found to follow the Langmuir–Hinshelwood model, with an estimated rate constant of 0.018 min<sup>−1</sup>, indicating efficient surface-mediated catalytic activity. Furthermore, an Artificial Neural Network (ANN) model was developed to validate and predict the degradation kinetics, showing a Root Mean Square Error (RMSE) of 5.5 and a high correlation coefficient (R<sup>2</sup>) of 0.9656, confirming the reliability of the predictive model. This interface-assisted, catalyst-based degradation approach demonstrates a promising, reusable, cost-effective, and environmentally friendly solution for advanced wastewater treatment applications.</div></div>\",\"PeriodicalId\":34388,\"journal\":{\"name\":\"Case Studies in Chemical and Environmental Engineering\",\"volume\":\"12 \",\"pages\":\"Article 101279\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Case Studies in Chemical and Environmental Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666016425001860\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Environmental Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Case Studies in Chemical and Environmental Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666016425001860","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Environmental Science","Score":null,"Total":0}
Interfacial engineering approach for enhanced degradation of methylene blue using platinum-coated polystyrene rough particles: Flow-regulated catalytic activity and kinetic modeling
This study explores an efficient decontamination strategy using platinum-coated polystyrene rough-particles as a micron-sized catalyst system for decomposing methylene blue (MB), a common organic pollutant. The synthesized nanomaterials were comprehensively characterized using Nanoparticle Tracking Analysis (NTA), Dynamic Light Scattering (DLS), Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM), and Transmission Electron Microscopy (TEM), confirming their morphology, size distribution, and surface properties. The decontamination was performed at the air-water interface through an interface trapping method, with enhanced mixing achieved under a controlled flow environment. The experiments were conducted with a circulation speed of 50 RPM, corresponding to a Reynolds number (NR) of 1686 and a high particle packing fraction of 0.8. Under these operating conditions, complete degradation of MB was achieved within 30 min, significantly faster than the 75 min required for degradation in the bulk phase. The reaction kinetics were analyzed and found to follow the Langmuir–Hinshelwood model, with an estimated rate constant of 0.018 min−1, indicating efficient surface-mediated catalytic activity. Furthermore, an Artificial Neural Network (ANN) model was developed to validate and predict the degradation kinetics, showing a Root Mean Square Error (RMSE) of 5.5 and a high correlation coefficient (R2) of 0.9656, confirming the reliability of the predictive model. This interface-assisted, catalyst-based degradation approach demonstrates a promising, reusable, cost-effective, and environmentally friendly solution for advanced wastewater treatment applications.