journal article·2025-08

Designing innovative ZnPc/N-CQDs hybrid material as efficient photocatalyst for environmental remediation

Bojana R. Vasiljević, Jovana R. Prekodravac Filipović, Sofiya Kolusheva, Raz Jelinek, Bernhard Fickl, Jakob Rath, Markus Hofer, Dominik Eder, Bernhard C. Bayer, Dragana Marinković

Ceramics International· Volume 51· Issue 19
Publisher page

Abstract

Water contamination with biological and chemical pollutants presents a significant environmental challenge, therefore it is necessary to develop efficient photocatalysts for green remediation. Here, we introduce an innovative ZnPc/N-CQDs hybrid material designed by self-assembling of lipophilic dye, zinc (II)-phthalocyanine (ZnPc), with N-doped carbon quantum dots (N-CQDs) using microwave irradiation. The as-prepared ZnPc/N-CQDs hybrid material exhibits excellent solubility and optical properties of N-CQDs, along with NIR absorption properties of ZnPc. Evidence from high-resolution transmission electron microscope (TEM) and atomic force microscope (AFM) measurements supports that the ZnPc crystals with a rectangular shape are uniformly covered with carbon quantum dots. The photocatalytic activity of the studied hybrid material and starting dye is compared based on efficiencies in the degradation of Rose Bengal (RB). The synthesized hybrid material showed high removal efficiency towards RB, and a great capacity to adsorb organic dye pollutants in the absence of light. This study introduces a new perspective on the advanced synergistic effect of ZnPc and N-CQDs and its potential to remove reactive residues of RB remediation. Due to the environmental friendliness, hydrophilicity, and clean production, designed hybrid can find application as promising photocatalyst for wastewater treatment and environmental remediation.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced Photocatalysis Techniques · Catalytic Processes in Materials Science · ZnO doping and properties

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

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