Volume 19 Issue 2
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Wen-lu Wang, Xin Ke. 2026: Photocatalytic degradation of antibiotics using TiO2/MOFs nanocomposites: A review. Water Science and Engineering, 19(2): 250-256. doi: 10.1016/j.wse.2026.02.001
Citation: Wen-lu Wang, Xin Ke. 2026: Photocatalytic degradation of antibiotics using TiO2/MOFs nanocomposites: A review. Water Science and Engineering, 19(2): 250-256. doi: 10.1016/j.wse.2026.02.001
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Photocatalytic degradation of antibiotics using TiO2/MOFs nanocomposites: A review

doi: 10.1016/j.wse.2026.02.001

  • Shenyang Key Laboratory of Environmental Functional Materials Construction and Pollution Control, School of Municipal and Environmental Engineering, Shenyang Jianzhu University, Shenyang 110168, China

Funds:

The work was supported by the Shenyang Social Governance Technology Special Project (Pollution Control Project) (Grant No. 24-213-3-01) and the Liaoning Revitalization Talents Program (Grant No. XLYC1807045).

  • Received Date: 2025-06-28
  • Accepted Date: 2026-01-27
    • Available Online: 2026-05-30
    Abstract
  • TiO2 nanomaterials are widely regarded as key materials for photocatalytic degradation of antibiotics. However, current research lacks systematic reviews that critically evaluate inconsistent findings or methodological limitations across studies. Existing mechanistic studies suggest that the synergy between TiO2 and metal—organic frameworks (MOFs) can enhance charge separation, extend the light absorption range, and utilize the porous structure of MOFs to adsorb pollutants, thereby collectively improving degradation efficiency. Nevertheless, most conclusions are derived from secondary data without substantial original insights. Advanced characterization techniques have partially revealed structure—activity relationships, and strategies such as heterojunction engineering and bandgap modulation have been employed to overcome the inherent limitations of TiO2. Nonetheless, there remains a notable absence of critical assessment regarding contradictions in experimental results or constraints in current methodologies. Future research should focus on morphology optimization, scalable synthesis routes, and the application of artificial intelligence (AI)-guided material design to facilitate industrial adoption, while also incorporating more primary validation and comparative analyses to resolve existing inconsistencies.

     

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