Subcategory: Environmental Engineering
Ahmed Yunus Ibrahim - Benedict College
Co-Author(s): Dr. Samuel Darko, Benedict College, Columbia, South Carolina
We report herein for the first time, a time-dependent engineered magnetic maghemite and magnetite nanoparticles synthesized by hydrothermal carbonization of expired waste pharmaceuticals. Unlike other studies that used high temperatures, harsh and expensive reagents, and tedious methods, our approach provides a cheaper and sustainable method for the attainment of such materials from expired iron supplements. Maghemite (Fe3O2) and magnetite (Fe3O4) were obtained at a fixed reaction temperature of 275 degrees celsius and residence times of 6 and 12 hours, respectively. The physicochemical characteristics, structure and morphology of the nanoparticles were studied using XRD, SEM, FTIR and BET. The as-prepared materials showed greater methylene blue removal when evaluated in a batch adsorptive study yielding close to 100% removal and an adsorptive capacity of 1.38 mg/g. Kinetic studies showed that the adsorption followed a pseudo-second-order reaction. The results from this study provides a cheaper yet effective route for the fabrication of magnetic magnetite nanoparticles useful in many important applications including, magnetic separation, drug delivery, energy storage and environmental protection.
Funder Acknowledgement(s): Department of Energy (DOE) ; DOE Grant # 2088-25
Faculty Advisor: Dr. Samuel Darko, firstname.lastname@example.org
Role: This research involved the fabrication of the magnetite nanoparticles using hydrothermal carbonization process, phase quantification of the end products of hydrothermal carbonization (hydrochar, liquid and gas) using Microsoft Excel, characterization of the magnetite nanoparticles using the XRD (X-ray diffractometry) to confirm what kind of compounds made up the nanoparticles, SEM (Scanning Electron Microscope) to determine the elemental analysis and morphology of the nanoparticles, FTIR (Fourier-transform infrared spectroscopy) also to identify the functional groups in the nanoparticles.