In this study, activated carbon (AC) from coconut shell, as a widely available agricultural waste, was synthesised in a simple one-step procedure and used to produce a magnetic Fe₃O₄/AC/TiO₂ nano-catalyst for the degradation of methylene blue (MB) dye under UV light. Scanning electron microscopy revealed that TiO₂ nanoparticles, with an average particle size of 45 to 62 nm, covered the surface of the AC porous structure without a reunion of its structure, which according to the TGA results enhanced the stability of the photocatalyst at high temperatures. The photocatalytic activities of synthesised AC, commercial TiO₂, Fe₃O₄/AC, and Fe₃O₄/AC/TiO₂ were compared, with Fe₃O₄/AC/TiO₂ (1:2) exhibiting the highest catalytic activity (98%). Furthermore, evaluation of the recovery and reusability of the photocatalysts after treatment revealed that seven treatment cycles were possible without a significant reduction in the removal efficiency.

The adsorption of dyes using 39 adsorbents (16 kinds of agro-wastes) were modeled using random forest (RF), decision tree (DT), and gradient boosting (GB) models based on 350 sets of adsorption experimental data. In addition, the correlation between variables and their importance was applied. After comprehensive feature selection analysis, five important variables were selected from nine variables. The RF with the highest accuracy (R² = 0.9) was selected as the best model for prediction of adsorption capacity of agro-waste using the five selected variables. The results suggested that agro-waste characteristics (pore volume, surface area, agro-waste pH, and particle size) accounted for 50.7% contribution for adsorption efficiency. The pore volume and surface area are the most important influencing variables among the agro-waste characteristics, while the role of particle size was inconspicuous. The accurate ability of the developed models’ prediction could significantly reduce experimental screening efforts, such as predicting the dye removal efficiency of agro-waste activated carbon according to agro-waste characteristics. The relative importance of variables could provide a right direction for better treatments of dyes in the real wastewater.

The effects of process conditions on Fischer–Tropsch Synthesis (FTS) product distributions were studied using a fixed-bed microreactor and a Co–Mn/CNT catalyst. Cobalt and Manganese, supported on Carbon Nanotubes (CNT) catalyst were prepared by a Strong Electrostatic Adsorption (SEA) method. CNT supports were initially acid and thermally treated in order to functionalize support to uptake more Co clusters. Catalyst samples were characterized by Transmitted Electron Microscope (TEM), particle size analyzer, and Thermal Gravimetric Analysis (TGA). TEM images showed catalyst metal particle intake on CNT support with different Co and Mn loading percentage. Performance test of Co–Mn/CNT in Fischer–Tropsch synthesis (FTS) was carried out in a fixed-bed micro-reactor at different pressures (from 1 atm to 25 atm), H2/CO ratio (0.5–2.5), and reduction temperature and duration. The reactor was connected to the online Gas Chromatograph (GC) for product analysis. It was found that the reaction conditions have the dominant effect on product selectivity. Cobalt catalyst supported on acid and thermal pre-treated CNT at optimum reaction condition resulted in CO conversion of 58.7% and C5+ selectivity of 59.1%.