Implanting titanium-oxo clusters into PVDF membrane matrix for photocatalytic self-cleaning in a continuous flow-through process

The photocatalytic ultrafiltration membranes have been demonstrated to be efficient for the treatment of various wastewaters under mild conditions at low cost, but it remains challenging to maintain their high efficiency due to irreversible membrane fouling, low mass transfer efficiency in the photocatalyst layer and low stability of the membrane to UV radiation. To this end, a negatively-charged amphiphilic PVDF ultrafiltration membranes were prepared, and polyoxotitanium clusters (PTCs) with broad visible light response were incorporated into them to develop a self-cleaning membrane. HRTEM, HAADF-STEM and corresponding EDS verify that the sub-nanometer PTCs are uniformly implanted into the membrane pore. The hydraulic test shows that the pores are not blocked by the implanted photocatalysts. The optimized composite photocatalytic membrane (PM3) benefits from the electrostatic enrichment of the basement membrane and the efficient mass transfer in a nanoscale confined channel. This allows the membrane to self-clean by degrading dyes under visible light irradiation. Compared with the original membrane, PM3 could maintain high permeate flux and dye rejection rate with negative fouling ratio during 5 cycles. This design enabled efficient removal of RhB (>85%) during 200 min continuous separation, while it could only maintain less than 50 min on the original membrane. This work provides a common and facile process to develop the photocatalytic ultrafiltration membranes with catalysts confined in nanoscale channels for efficient wastewater treatment.

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Publication Details

Journal
Carbon Future
Published
2025-09-01
DOI
https://doi.org/10.26599/cf.2025.9200054
Citations
1
Primary Topic
Optimization and Search Problems
Type
article
Field-Weighted Citation Impact
1.49

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article

Implanting titanium-oxo clusters into PVDF membrane matrix for photocatalytic self-cleaning in a continuous flow-through process

Xiaofeng Cui, Yujie Xiong, Wensong Duan, Yue Wang et al.
1 citations
Carbon Future
Optimization and Search Problems
1.49
article

Implanting titanium-oxo clusters into PVDF membrane matrix for photocatalytic self-cleaning in a continuous flow-through process

Xiaofeng Cui, Yujie Xiong, Wensong Duan, Yue Wang, Guoliang Wang, Tingting Guan
article en
1 citations

Abstract

The photocatalytic ultrafiltration membranes have been demonstrated to be efficient for the treatment of various wastewaters under mild conditions at low cost, but it remains challenging to maintain their high efficiency due to irreversible membrane fouling, low mass transfer efficiency in the photocatalyst layer and low stability of the membrane to UV radiation. To this end, a negatively-charged amphiphilic PVDF ultrafiltration membranes were prepared, and polyoxotitanium clusters (PTCs) with broad visible light response were incorporated into them to develop a self-cleaning membrane. HRTEM, HAADF-STEM and corresponding EDS verify that the sub-nanometer PTCs are uniformly implanted into the membrane pore. The hydraulic test shows that the pores are not blocked by the implanted photocatalysts. The optimized composite photocatalytic membrane (PM3) benefits from the electrostatic enrichment of the basement membrane and the efficient mass transfer in a nanoscale confined channel. This allows the membrane to self-clean by degrading dyes under visible light irradiation. Compared with the original membrane, PM3 could maintain high permeate flux and dye rejection rate with negative fouling ratio during 5 cycles. This design enabled efficient removal of RhB (>85%) during 200 min continuous separation, while it could only maintain less than 50 min on the original membrane. This work provides a common and facile process to develop the photocatalytic ultrafiltration membranes with catalysts confined in nanoscale channels for efficient wastewater treatment.

Carbon FutureVol. 2(3)
National Natural Science Foundation of China
Openalex Percentile: Top 13%
Optimization and Search Problems
1.49
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