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A mini-review: the ice resistance durability and mechanical durability of ice-phobic surfaces
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0003-0477-7063
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0002-4271-0380
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0003-3157-4632
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0001-6085-7880
(English)Manuscript (preprint) (Other academic)
National Category
Other Engineering and Technologies not elsewhere specified
Research subject
Machine Elements
Identifiers
URN: urn:nbn:se:ltu:diva-105225OAI: oai:DiVA.org:ltu-105225DiVA, id: diva2:1854198
Available from: 2024-04-24 Created: 2024-04-24 Last updated: 2024-04-24
In thesis
1. Optimizing Ice-Resistant Surfaces: Unifying Self-Healing, Durability, and Functional Design for Superior Anti-/De-Icing Performance
Open this publication in new window or tab >>Optimizing Ice-Resistant Surfaces: Unifying Self-Healing, Durability, and Functional Design for Superior Anti-/De-Icing Performance
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Snow and ice accumulation on critical infrastructure such as wind power turbines and power lines cause significant challenges and safety hazards in cold climate regions during wintertime. Research into anti-/de-icing technologies has been divided into two main streams, i.e., active, and passive approaches. Active technologies, including electric thermal, photothermal technologies, etc, are widely used in anti-/de-icing fields. Passive technologies, including hydrophobic and slippery surfaces, have gained increasing interest due to their low energy consumption and sustainable profile, but these passive technologies are often limited by relatively short service life and poor mechanical durability. 

A potential way of improving the anti-/de-icing performance would be to combine different technologies and create electric thermal superhydrophobic surfaces and/or photo-thermal superhydrophobic surfaces. Furthermore, the mechanical durability could be improved by developing self-healing superhydrophobic surfaces and wear-resistant electric thermal surfaces. However, some important studies of relevant mechanisms to achieve this are absent in the literature, such as the influence of self-healing on ice adhesion, and investigation on how to unify the durability and anti-/de-icing performances via molecular structure design. 

This thesis addresses these questions by focusing on enhancing the wear resistance and anti-/de-icing efficiency of anti-/de-icing materials through innovative material design. We conducted ice-phobic tests in lab environment, and long-term ice-phobic field tests, which helped us to further understand and optimize the design of ice-phobic surfaces. 

This thesis contributes to developing more durable, efficient, and sustainable anti-/de-icing solutions, addressing the critical need for reliable performance under adverse weather conditions. 

The key findings were: 

(1) A novel self-healing and low-ice adhesion poly silicon urea coating was developed, leveraging the intrinsic material structure for creating sufficient wear resistance and self-healing capabilities. The Poly silicon urea coating exhibits below 10kPa ice adhesion strength, which is far lower than the ice-phobic surface request(<100kPa). The molecular structure’s influence on self-healing and ice adhesion are specified in this work.

(2) Inspired by the low-icing bonding properties of silicon urea, a graphene-enhanced siloxane urea multi-functional coating was designed, where the low-icing properties were combined with electric and thermal conductivity to achieve both active and passive anti-/de-icing effects. This graphene enhancement coating exhibits 10 minutes of removing all ice accretion under ~570W/m2 electric power on the lab scale test. The field tests, where a graphene enhancement coating surface can keep ice-free under ~310W/m2 during the whole winter in a harsh natural environment.  

(3) To explore the influence of mechanical durability on ice-phobic, a composite coating which integrates wear resistance and thermal conductive was formulated. Graphene was proven as a suitable additive to enhance thermal conductivity and wear resistance. Compared with the blank control coating and a boron nitride composite coating, the thermal conductivity of a graphene composite coating increased around 3 times, and the anti-wear performance based on wear depth was increased around 1.5 times. The wear mechanism and wear influence on anti-/de-icing behaviour are investigated in this work. 

(4) This work also explored the impact of surface functional groups on anti-/de-icing performance, uncovering that the force interactions and steric radius of these groups significantly influence surface element distribution and material strength, thereby affecting wettability and wear behaviour. The results show that the hydrophobicity of the groups is not the only factor to influence the surface properties. A smaller steric radius and strong interactions are beneficial for reducing the van der Waals' gap between groups which can inhibit the wetting of the water molecules. The influence of five different typical groups on mechanical durability and ice adhesion is investigated in this work.

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2024
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Keywords
Anti-/de-icing
National Category
Tribology (Interacting Surfaces including Friction, Lubrication and Wear)
Research subject
Machine Elements
Identifiers
urn:nbn:se:ltu:diva-105228 (URN)978-91-8048-556-2 (ISBN)978-91-8048-557-9 (ISBN)
Public defence
2024-06-04, E632, Luleå University of Technology, Luleå, 09:00 (English)
Opponent
Supervisors
Available from: 2024-04-24 Created: 2024-04-24 Last updated: 2024-05-14Bibliographically approved

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Chen, JunBjörling, MarcusMarklund, PärShi, Yijun

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