Artificial intelligence models for methylene blue removal using functionalized carbon nanotubes.

This study aims to assess the practicality of utilizing artificial intelligence (AI) to replicate the adsorption capability of functionalized carbon nanotubes (CNTs) in the context of methylene blue (MB) removal. The process of generating the carbon nanotubes involved the pyrolysis of acetylene under conditions that were determined to be optimal. These conditions included a reaction temperature of 550 °C, a reaction time of 37.3 min, and a gas ratio (H2/C2H2) of 1.0. The experimental data pertaining to MB adsorption on CNTs was found to be extremely well-suited to the Pseudo-second-order model, as evidenced by an R2 value of 0.998, an X2 value of 5.75, a qe value of 163.93 (mg/g), and a K2 value of 6.34 × 10-4 (g/mg min).The MB adsorption system exhibited the best agreement with the Langmuir model, yielding an R2 of 0.989, RL value of 0.031, qm value of 250.0 mg/g. The results of AI modelling demonstrated a remarkable performance using a recurrent neural network, achieving with the highest correlation coefficient of R2 = 0.9471. Additionally, the feed-forward neural network yielded a correlation coefficient of R2 = 0.9658. The modeling results hold promise for accurately predicting the adsorption capacity of CNTs, which can potentially enhance their efficiency in removing methylene blue from wastewater.

Growth and optimization of carbon nanotubes in powder activated carbon for an efficient removal of methylene blue from aqueous solution.

This work demonstrated the synthesis of carbon nanotubes (CNTs) on powder activated carbon (PAC) impregnated with Ni-catalyst through chemical vapour deposition. The optimized effects of reaction temperature, time and feedstock flow rates on CNT growth were examined. Potassium permanganate (KMnO4) and potassium permanganate in acidic solution (KMnO4/H2SO4) were used to functionalize CNTs samples. A primary screening of methylene blue (MB) adsorption was conducted. The chemical, physical and morphological properties of the adsorbent with the highest removal efficiency were investigated using FESEM, EDX, TEM, BET surface area, RAMAN, TGA, FTIR, and zeta potential. The resulting carbon nanotube-loaded activated carbons possessed abundant pore structure and large surface area. The MB removal by the as-synthesized CNTs was more remarkable than that by the modified samples. Adsorption studies were carried out to evaluate the optimum conditions, kinetics and isotherms for MB adsorption process. The response surface methodology-central composite design (RSM-CCD) was used to optimize the adsorption process parameters, including pH, adsorbent dosage and contact time. The investigation of the adsorption behaviour demonstrated that the adsorption was well fitted with the pseudo-second-order model and Langmuir isotherm with the maximum monolayer adsorption capacity of 174.5 mg/g. Meanwhile, the adsorption of MB onto adsorbent was driven by the electrostatic attraction and π-π interaction. Moreover, the as-obtained CNT-PAC exhibited good reusability after four repeated operations. In view of these empirical findings, the low-cost CNT-PAC has potential for removal of MB from aqueous solution.

The formation of hybrid carbon nanomaterial by chemical vapor deposition: an efficient adsorbent for enhanced removal of methylene blue from aqueous solution.

In this study, carbon species were grown on the surface of Ni-impregnated powder activated carbon to form a novel hybrid carbon nanomaterial by chemical vapor deposition. The carbon nanomaterial was obtained by the precipitation of the methane elemental carbon atoms on the surface of the Ni catalyst. The physiochemical properties of the hybrid material were characterized to illustrate the successful growth of carbon species on the carbon substrate. The response surface methodology was used for the evaluation of adsorption parameters effect such as pH, adsorbent dose and contact time on the percentage removal of MB dye from aqueous solution. The optimum conditions were found to be pH = 11, adsorbent dose = 15 mg and contact time of 120 min. The material we prepared showed excellent removal efficiency of 96% for initial MB concentration of 50 mg/L. The adsorption of MB was described accurately by the pseudo-second-order model with R2 of 0.998 and qe of 163.93 (mg/g). The adsorption system showed the best agreement with Langmuir model with R2 of 0.989 and maximum adsorption capacity (Qm) of 250 mg/g.

Optimization of the Synthesis of Superhydrophobic Carbon Nanomaterials by Chemical Vapor Deposition.

Demand is increasing for superhydrophobic materials in many applications, such as membrane distillation, separation and special coating technologies. In this study, we report a chemical vapor deposition (CVD) process to fabricate superhydrophobic carbon nanomaterials (CNM) on nickel (Ni)-doped powder activated carbon (PAC). The reaction temperature, reaction time and H2/C2H2 gas ratio were optimized to achieve the optimum contact angle (CA) and carbon yield (CY). For the highest CY (380%) and CA (177°), the optimal reaction temperatures were 702 °C and 687 °C, respectively. However, both the reaction time (40 min) and gas ratio (1.0) were found to have similar effects on CY and CA. Based on the Field emission scanning electron microscopy and transmission electron microscopy images, the CNM could be categorized into two main groups: a) carbon spheres (CS) free carbon nanofibers (CNFs) and b) CS mixed with CNFs, which were formed at 650 and 750 °C, respectively. Raman spectroscopy and thermogravimetric analysis also support this finding. The hydrophobicity of the CNM, expressed by the CA, follows the trend of CS-mixed CNFs (CA: 177°) > CS-free CNFs (CA: 167°) > PAC/Ni (CA: 65°). This paves the way for future applications of synthesized CNM to fabricate water-repellent industrial-grade technologies.