MoS2 Nanosheets Decorated with Fe3O4 Nanoparticles for Highly Efficient Solar Steam Generation and Water Treatment

Molecules. 2023 Feb 10;28(4):1719. doi: 10.3390/molecules28041719.

Abstract

The shortage of water resources has always been one of the most difficult problems that perplexes humanity. Solar steam generation (SSG) has been a new non-polluting and low-cost water purification method in recent years. However, the high cost of traditional photothermal conversion materials and the low efficiency of photothermal conversion has restricted the large-scale application of SSG technology. In this work, composite materials with Fe3O4 nanospheres attached to MoS2 nanosheets were synthesized, which increased the absorbance and specific surface area of the composite materials, reduced the sunlight reflection, and increased the photothermal conversion efficiency. During the experiment, the composite material was evenly coated on cotton. The strong water absorption of cotton ensured that the water could be transported sufficiently to the surface for evaporation. Under one sun irradiation intensity, the evaporation rate of the sample synthesized in this work reached 1.42 kg m-2 h-1; the evaporation efficiency is 89.18%. In addition, the surface temperature of the sample can reach 41.6 °C, which has far exceeded most photothermal conversion materials. Furthermore, the use of this composite material as an SSG device for seawater desalination and sewage purification can remove more than 98% of salt ions in seawater, and the removal rate of heavy metal ions in sewage is close to 100%, with a good seawater desalination capacity and sewage purification capacity. This work provides a new idea for the application of composite materials in the field of seawater desalination and sewage purification.

Keywords: Fe3O4; MoS2; desalination; solar steam generation; water treatment.

MeSH terms

  • Gossypium
  • Molybdenum
  • Nanospheres*
  • Sewage
  • Steam
  • Sunlight
  • Water Purification*

Substances

  • Molybdenum
  • Sewage
  • Steam

Grants and funding

This work was supported by the Suzhou University key project (2022yzd07), Major Projects of Natural Science Research in Universities of Anhui Province (KJ2021ZD0137), the Open Research Fund of National Engineering Research Center for Agro-Ecological Big Data Analysis & Application, Anhui University (AE202201), the Key Projects of Natural Science Research in Universities of Anhui Province (KJ2021A0907, 2022AH050378), the Research Platform of Anhui Provincial Engineering Laboratory on Information Fusion and Control of Intelligent Robot under grants (IFCIR2020005).