The Rise of Two-Dimensional-Material-Based Filters for Airborne Particulate Matter Removal

Jun Liu, Enze Tian, Shaolin Zhang, Deyu Kong, Kehai Liu, Xuedong Bai, Kaihui Liu

Advanced Fiber Materials ›› 2022, Vol. 5 ›› Issue (2) : 461-483.

Advanced Fiber Materials ›› 2022, Vol. 5 ›› Issue (2) : 461-483. DOI: 10.1007/s42765-022-00242-8
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The Rise of Two-Dimensional-Material-Based Filters for Airborne Particulate Matter Removal

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Abstract

Airborne particulate matter (PM) has been the leading contributor to air pollution, posing a substantial risk to human health, and effective filtration technologies are required. Two-dimensional (2D) materials, such as graphene, graphitic carbon nitride (g-C3N4), molybdenum disulfide (MoS2), and MXenes have emerged in recent years for PM filtration due to their exceptionally large specific surface area and unique electrical properties. Here, the most extensively used 2D materials for PM filtration followed by a summary of their fabrication methods and corresponding morphologies were introduced. Among them, the coating is the most cost-effective technique for achieving large-scale and quick fabrication. Electrospinning can effectively enhance filtration efficiency and reduce pressure drop by upgrading electrostatic force and lowering the fiber diameter. The initial and long-term performance of 2D-material-based filters was summarized. Among all 2D materials, GO is the most studied and shows the best performance by upgrading the dipole–dipole and electrostatic interaction between filters and PM. Future study is expected to explore various 2D materials beyond GO, to evaluate filtration efficiency for submicron PM at m/s level air velocity, and to extend the service life for potential applications.

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Jun Liu, Enze Tian, Shaolin Zhang, Deyu Kong, Kehai Liu, Xuedong Bai, Kaihui Liu. The Rise of Two-Dimensional-Material-Based Filters for Airborne Particulate Matter Removal. Advanced Fiber Materials, 2022, 5(2): 461‒483 https://doi.org/10.1007/s42765-022-00242-8
Funding
Basic and Applied Basic Research Foundation of Guangdong Province(2021B0301030002); Key R&D Program of Guangdong Province(2018B030327001); National Natural Science Foundation of China(51972069)

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