Optimization of Adsorption Conditions Using Response Surface Methodology for Tetracycline Removal by MnFe2O4/Multi-Wall Carbon Nanotubes

Abstract

In this study, the optimal conditions and effects of external factors on tetracycline adsorption by magnetic multi-walled carbon nanotubes (MMWCNTs) were established by a response surface methodology for the first time. Batch adsorption experiments showed that increasing the dosage and contact time effectively promoted the adsorption of tetracycline and maximum removal of 97.93–99.13% was achieved at pH 3–7. The pseudo-second-order model and Fourier-transform infrared spectroscopy spectra indicated that the mechanism of adsorption may be π–π electron interaction and cation–π electron bonding. Design Expert was utilized to develop a response surface methodology for the analysis and optimization of tetracycline adsorption by magnetic multi-walled carbon nanotubes. The Box–Behnken design (BBD) results showed that the optimization exhibited high significance and reliability. The main effect plots and Pareto chart indicated that pH exerted a significant individual effect on the regulation of adsorption, while 3D response surface plots and interaction effect plots exhibited a significant antagonistic interaction between pH and contact time. A maximum tetracycline removal of 99.16% was achieved under the optimal conditions of 12 mg adsorbent dosage at pH 5.43, with an adsorption time of 120 min. Mathematical and experimental results confirmed the accuracy of the established optimal conditions.

Response surface methodology and machine learning optimisations comparisons of recycled AA6061-B4C–ZrO2 hybrid metal matrix composites via hot forging forming process

“…Also, the preheating temperature influences rising UTS according to the major effects plot, the maximum UTS is reached at the highest peak of 550 °C and 5 %. B 4 C– ZrO 2 reinforced ceramics particles [ 38 , 52 ]. The interplay of temperature and volume fraction impacts the UTS of the materials as shown in the Contour 2D Plot of UTS.…”

“… Where n is the number of data , the predicted and measured values and m data points. The mean absolute error (MAE) is used to calculate the lowest error from the predicted model and expressed in Eq (4) [ 38 ]. …”

Toxicity, physiological response, and biosorption mechanism of Dunaliella salina to copper, lead, and cadmium

“…In addition, it cannot be ignored that the biosorption and removal efficiency of algae on heavy metal ions may be relevant to multiple factors, such as pH, temperature, algal biomass, and ionic concentration. As one of the most commonly used response surface methods (RSM), Box–Behnken design (BBD) is ideal for seeking the optimal conditions of adsorption process ( Moon et al, 2013 ; Mutalik et al, 2021 ; Pascual et al, 2022 ; Ramesh et al, 2023 ; Zhao et al, 2023 ). For instance, Zeng et al (2022) reported that the peak adsorption of Microcystis aeruginosa powder on Cu 2+ , Cd 2+ , and Ni + was 83.24, 92.00, and 88.67% under the initial concentration of Cu 2+ , Cd 2+ , and Ni + of 25 mg/L, 5 mg/L,and 15 mg/L, the temperature of 30°C, 35°C, pH value of 8, 8, and 7, and the adsorption time of 5 h, 4 h, and 1 h, respectively.…”

“…Notably, the optimal temperature range of bioremediation is narrow due to the fact that the biosorption process is endothermic and the removal efficiency enhanced along with the increase in temperature. However, high temperature may destroy cell structure and some active sites, lowering the removal rate ( Zhao et al, 2023 ). Therefore, in the practical settings, D. salina cells can be domesticated to grow at pH of 5–6 and temperature of 25–30°C to adsorp the heavy metals from the wastewater, achieving a higher removal efficiency of heavy metals.…”

Modelling and optimization of fabrication parameters for multi-walled carbon nanotubes-filled GFRP composites using RSM and Rao-1 algorithm

“…RSM is one of the important experimental planning methodologies of design of experiments (DoE) [34]. RSM's primary benefit lies in its efficacy, allowing for limited experimental runs to forecast factor interactions and obtain optimal conditions with precision [23].…”