Sugeno fuzzy inference system modeling and DFT calculations for the treatment of pesticide-laden water by newly developed arginine functionalized magnetic Mn-based metal organic framework.

Abstract

The uncontrolled utilization of pesticides poses a significant risk to the environment and human health, making its management essential. In this regard, a new arginine functionalized magnetic Mn-based metal-organic framework (Arg@m-Mn-MOF) was fabricated and assessed for the removal of cypermethrin (CYP) and chlorpyrifos (CHL) from aqueous system. The Arg@m-Mn-MOF was characterized by scanning electron microscopy, energy dispersive X-ray, Fourier transform infrared spectroscopy, X-ray diffraction, and Brunauer-Emmett-Teller analysis. Various parameters were optimized in a series of batch experiments and the following conditions were found optimal: pH: 4 and 5, contact time: 20min, adsorbent dosage: 0.6 and 0.8g L-1 with initial concentration: 10mg L-1 and temperature: 298K for CYP and CHL, respectively. The composite attained a maximum removal capacity of 44.84 and 71.42mgg-1 for CYP and CHL, respectively. The elucidated data was strongly fitted to the pseudo-second-order model of kinetics (R2 > 0.98) and Langmuir isotherm (R2 > 0.98). Based upon 350 experimental datasets obtained from batch studies and interpolated data, the adsorption capacity of the adsorbent was elucidated with R2 > 0.97 (CHL) and > 0.91 (CYP). The adsorption energy (- 11.67kcalmol-1) calculated by Gaussian software suggests a good interaction between arginine and CHL through H-bonding. The present study's findings suggested the prepared Arg@m-Mn-MOF as a promising adsorbent for the efficient removal of pesticides from agriculture runoff.