The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
An exploratory study on using Slippery-Liquid-Infused-Porous-Surface (SLIPS) for wind turbine icing mitigation
Open accessAbstract
Abstract An experimental study was conducted to explore the potentials of using a Slippery-Liquid-Infused-Porous-Surface (SLIPS) for wind turbine icing mitigation. The SLIPS was prepared by infusing a lubricant oil into a nanofibrous membrane, which can stick firmly to the surface of a turbine blade model. While the SLIPS was found to effectively suppress impact ice accretion on the blade surface where strong aerodynamic forces are exerted, ice was still found to accrete in the vicinity of the blade stagnation line where aerodynamic forces are at their minimum. A novel hybrid anti-/de-icing strategy to integrate the SLIPS with a minimized leading-edge heating was demonstrated to effectively remove the ice accretion over entire blade surface. An comprehensive experimental study was also performed to evaluate the durability of the SLIPS to resist wearing away of the substrate materials and depletion of the infused lubricant oil due to “rain erosion” effects, in considering its practical usage for wind turbine icing mitigation. It was found that the “rain erosion” effects would induce significant surface wettability degradation, substantial ice adhesion increment and even structural failures to the SLIPS as the duration of the rain erosion testing increases.
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“The frost adhesion on slippery liquid-infused porous surface is also significantly lower than that on other surfaces [111 -113].”
From Frosting mechanism and behaviors on surfaces with simple geometries: A state-of-the-art literature review (2022) · cites this paper as [112]
Citations
Cites
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Research works printed but not linked: 2
- Kim, 2012, Liquid-infused nanostructured surfaces with extreme anti-ice and anti-frost performance, ACS Nano, 6, 6569, 10.1021/nn302310q · DOI · Paper page
- Lv, 2014, Bio-inspired strategies for anti-icing, ACS Nano, 8, 3152, 10.1021/nn406522n · DOI · Paper page
Cited by
Zhang, L., Song, M., Deng, S., Shen, J., & Dang, C. (2022) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2022.118984 · Cited by 83
Metadata
- Authors
- Ma, L., Zhang, Z., Gao, L., Liu, Y., & Hu, H.
- Affiliations
- Iowa State University (US)
- Corresponding author
- Hu, Hui
- Venue
- Renewable Energy
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 162
- Pages
- 2344-2360
- ISSN
- 0960-1481 (ISSN-L)
- OpenAlex
- W3091979561
- Cited by
- 62
- References
- 53
- Citations by year
- 2026: 9 · 2025: 11 · 2024: 15 · 2023: 12 · 2022: 7 · 2021: 8
- FWCI
- 3.93
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (am, 318 d)
- Locations
- Renewable Energy (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Science Foundation
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Icing and De-icing Technologies
- Physical Sciences › Materials Science › Surfaces, Coatings and Films › Surface Modification and Superhydrophobicity
- Physical Sciences › Chemistry › Physical and Theoretical Chemistry › nanoparticles nucleation surface interactions
- Keywords
- slippery liquid-infused porous surfaces, wind turbine icing, ice accretion, turbine blades, anti-icing, de-icing, nanofibrous membranes, leading edge heating, rainfall erosion, ice adhesion, surface durability
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- CoChat. (2026). Citation check: An exploratory study on using Slippery-Liquid-Infused-Porous-Surface (SLIPS) for wind turbine icing mitigation. https://app.cochat.ai/papers/10.1016/j.renene.2020.10.013
- The paper
- Ma, L., Zhang, Z., Gao, L., Liu, Y., & Hu, H. (2020). An exploratory study on using Slippery-Liquid-Infused-Porous-Surface (SLIPS) for wind turbine icing mitigation. Renewable Energy. https://doi.org/10.1016/j.renene.2020.10.013
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.