Photo-Fenton and TiO 2 Photocatalytic Inactivation of Model Microorganisms under UV-A; Comparative Efficacy and Optimization.
Eirini KanataIoannis PaspaltsisSotiris SotiriadisChrysanthi BerberidouSophia TsoumachidouTheodoros SklaviadisKonstantinos XanthopoulosMinas ArsenakisAthanasios ArsenakisIoannis PouliosTheodoros SklaviadisPublished in: Molecules (Basel, Switzerland) (2023)
Photocatalytic inactivation of pathogens in aqueous waste is gaining increasing attention. Several homogeneous and heterogeneous photocatalytic protocols exist using the Fenton's reagent and TiO 2 , respectively. A comprehensive study of homogeneous and heterogeneous photocatalysis on a range of microorganisms will significantly establish the most efficient method. Here, we report a comparative study of TiO 2 - and Fe +3 -based photocatalytic inactivation under UV-A of diverse microorganisms, including Gram-positive ( Staphylococcus aureus ) and Gram-negative ( Escherichia coli ) bacteria, bacterial spores ( Bacillus stearothermophilus spores) and viruses (MS2). We also present data on the optimization of TiO 2 photocatalysis, including optimal catalyst concentration and H 2 O 2 supplementation. Our results indicate that both photo-Fenton and TiO 2 could be successfully applied for the management of microbial loads in liquids. Efficient microorganism inactivation is achieved with homogeneous photocatalysis (7 mg/L Fe +3 , 100 mg/L H 2 O 2 , UV-A) in a shorter processing time compared to heterogeneous photocatalysis (0.5 g/L TiO 2 , UV-A), whereas similar or shorter processing is required when heterogenous photocatalysis is performed using microorganism-specific optimized TiO 2 concentrations and H 2 O 2 supplementation (100 mg/L); higher H 2 O 2 concentrations further enhance the heterogenous photocatalytic inactivation efficiency. Our study provides a template protocol for the design and further application for large-scale photocatalytic approaches to inactivate pathogens in liquid biomedical waste.
Keyphrases
- visible light
- gram negative
- multidrug resistant
- escherichia coli
- staphylococcus aureus
- multiple sclerosis
- heavy metals
- mass spectrometry
- hydrogen peroxide
- nitric oxide
- aqueous solution
- working memory
- microbial community
- cystic fibrosis
- big data
- high resolution
- gold nanoparticles
- deep learning
- artificial intelligence
- room temperature
- methicillin resistant staphylococcus aureus
- highly efficient
- bacillus subtilis
- sewage sludge
- data analysis