journal article·2017-04

Comparison of two synthesis methods on the preparation of Fe, N-Co-doped TiO2 materials for degradation of pharmaceutical compounds under visible light

Cinthia G. Aba-Guevara, Iliana E. Medina-Ramírez, Aracely Hernández-Ramírez, Juan Jáuregui-Rincón, Juan Antonio Lozano-Álvarez, José Luis Rodríguez-López

Ceramics International· Volume 43· Issue 6
Publisher page

Abstract

Abstract In this work, we report the synthesis, characterization and photocatalytic evaluation of visible light active iron-nitrogen co-doped titanium dioxide (Fe 3+ -TiO 2−x N x ) nanostructured catalyst. Fe 3+ -TiO 2−x N x was synthesized using two different chemical approaches: sol-gel (SG) and microwave (MW) methods. The materials were fully characterized using several techniques (SEM, UV–Vis diffuse reflectance DRS, X-ray diffraction XRD, and X-ray photoelectron spectroscopy XPS). The photocatalytic activity of the nanostructured materials synthesized by both methods was evaluated for the degradation of amoxicillin (AMX), streptomycin (STR) and diclofenac (DCF) in aqueous solution. Higher degradation efficiencies were encountered for the materials synthesized by the SG method, for instance, degradation efficiencies values of 58.61% (SG) and 46.12% (MW) were observed for AMX after 240 min of photocatalytic treatment under visible light at pH 3.5. With STR the following results removal efficiencies were obtained: 49.67% (SG) and 39.90% (MW) at pH 8. It was observed the increasing of degradation efficiencies values at longer treatment periods, i.e., after 300 min of photocatalytic treatment under visible light, AMX had a degradation efficiency value of 69.15% (MW) at pH 3.5, DCF 72.3% (MW) at pH 5, and STR 58.49% (MW) at pH 8.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced Photocatalysis Techniques · Pharmaceutical and Antibiotic Environmental Impacts · TiO2 Photocatalysis and Solar Cells

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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