The persistence of antibiotics in wastewater during treatment processes is related to the the complex chemical structure. The treated effluents need to be subjected to an advanced treatment process to eliminate antibiotics residues before the final disposal of these effluents into natural water sources. The removal technologies of antibiotics include adsorption, degradation, photocatalysts, and nanotechnology. The photocatalysis processes using nanosize catalysts have interested researchers in the last few years.

Researchers are also looking into a low-cost method for the synthesis of nanoparticles such as the use of green synthesis for chemical and physical processes. Moreover, artificial neural networks are one of the most advanced and powerful modelling tools with multiple areas of applications. However, very few studies have used such technologies in terms of antibiotic removal modelling. Therefore, the use of artificial neural networks would help to understand the behaviour of antibiotics for different removal processes. We could then evaluate the fate of the intermediate products generated from the degradation process.

The aim of this Special Issue is to bring together original research and review articles discussing sustainable bionanocatalysts used in the photocatalysis of antibiotics in water and wastewater.

Potential topics include but are not limited to the following:

• Efficiency of bionanocatalysts on the removal of antibiotics in water and wastewater
• Efficiency nanocomposites on the removal of antibiotics in water and wastewater
• Artificial neural networks in the photocatalysis of antibiotics
• Machine learning in the photocatalysis of antibiotics
• Techno-economic analysis of novel nanocomposites and nanoparticles for removing antibiotics on a large scale