AI-driven optimization of the heterogeneous Sono-Fenton process for intensification of bacterial inactivation

Abstract

Inactivation of persistent and resistant bacterial species is key to future water treatment technologies and sustainable public health. Standalone unit operations although have been implemented for several decades, are falling short to tackle the issues related to antibiotic resistance and other associated challenges. In this regard, a systematic study is illustrated to assess the intensification in the inactivation of antibiotic-resistant Acinetobacter baumannii via novel heterogenous Sono-Fenton process (H-SF). Inactivation via H-SF process was accomplished in 120min with and above the catalyst dose (Fe<inf>3</inf>O<inf>4</inf>) of 100mgL-1 due to the ability of the Fe<inf>3</inf>O<inf>4</inf> nanoparticles to exhibit peroxidase like activity to decompose H<inf>2</inf>O<inf>2</inf> by providing active iron sites. The H-SF inactivation process was found to be effective over a wide-ranging pH (4, 6.5 and 9). No reactivation of the bacterial cell until 96h indicates the irreversible desolation of the bacterial cell membrane and associated intracellular components. In the H-SF process, H<inf>2</inf>O<inf>2</inf> and •OH were experimentally shown to be significant for the inactivation of the bacteria and corroborated from the electron microscopy images. To integrate the effect of Fenton reagents and ultrasound, Response Surface Methodology-Central Composite Design and Gaussian Process Regression were employed. Additionally, the software HSFIN.VB was developed to facilitate process control through a graphical interface. The efficiency of the H-SF process was further authenticated with real water samples and its potential for the future applications was suggested by investigating the reusability of the catalyst which further lessen the risk of sludge formation.