Synergistic wear-corrosion analysis and modelling of nanocomposite coatings

Authors: Nazir, M.H., Khan, Z.A., Saeed, A., Siddaiah, A. and Menezes, P.L.

Journal: Tribology International

Volume: 121

Pages: 30-44

ISSN: 0301-679X

DOI: 10.1016/j.triboint.2018.01.027

Abstract:

This paper presents analysis and modelling of synergistic wear-corrosion performance of Nickel-Graphene (Ni/GPL) nanocomposite coating and compares it with un-coated steel 1020 under reciprocating-sliding contact. A novel synergistic wear-corrosion prediction model incorporating Archard description with nano-mechanics and electrochemistry was developed for Ni/GPL and steel 1020. The model is equally applicable to any kind of nanocomposite coating and bulk material like metals. For various nanocomposite coatings; their respective mechanical parameters should be used as inputs such as poisons ratio (v), Elastic Modulus (E), Hardness (H), Coefficient of Thermal Elastic mismatch (CTE) and intrinsic grain size (Do). The synergistic wear-corrosion effects were significantly-prominent in steel compared to Ni/GPL especially under contaminated lubricating oil conditions. This behaviour of Ni/GPL attributes to compact, refined grain structure leading to minimal grain pull-out during wear cycles which was also assured by less severe micro-ploughing in Ni/GPL compared to severe micro-cutting in steel. The predictions and experimental results were in good-agreement. Modelling of synergistic effects of wear-corrosion applied to nano-composite coatings have never been presented prior to this research. The significance of this work in terms of precision based wear-corrosion synergistic analysis, modelling and predictive techniques is evident from various industrial applications. This work will bring impacts for both in-situ and remote sensor based condition monitoring techniques to automotive, locomotive, aerospace, precision manufacturing and wind turbine industries.

https://eprints.bournemouth.ac.uk/30200/

Source: Scopus

Synergistic wear-corrosion analysis and modelling of nanocomposite coatings

Authors: Nazir, M.H., Khan, Z.A., Saeed, A., Siddaiah, A. and Menezes, P.L.

Journal: TRIBOLOGY INTERNATIONAL

Volume: 121

Pages: 30-44

eISSN: 1879-2464

ISSN: 0301-679X

DOI: 10.1016/j.triboint.2018.01.027

https://eprints.bournemouth.ac.uk/30200/

Source: Web of Science (Lite)

Synergistic Wear-Corrosion Analysis and Modelling of Nanocomposite Coatings

Authors: Nazir, H., Khan, Z., Saeed, A., Siddaiah, A. and Menezes, P.

Journal: Tribology International

Volume: 121

Pages: 30-44

Publisher: Pergamon Press Ltd.

ISSN: 0301-679X

DOI: 10.1016/j.triboint.2018.01.027

Abstract:

This paper presents analysis and modelling of synergistic wear-corrosion performance of Nickel-Graphene (Ni/GPL) nanocomposite coating and compares it with un-coated steel 1020 under reciprocating-sliding contact. A novel synergistic wear-corrosion prediction model incorporating Archard description with nano-mechanics and electrochemistry was developed for Ni/GPL and steel 1020. The model is equally applicable to any kind of nanocomposite coating and bulk material like metals. For various nanocomposite coatings; their respective mechanical parameters should be used as inputs such as poisons ratio (v), Elastic Modulus (E), Hardness (H), Coefficient of Thermal Elastic mismatch (CTE) and intrinsic grain size (Do). The synergistic wear-corrosion effects were significantly-prominent in steel compared to Ni/GPL especially under contaminated lubricating oil conditions. This behaviour of Ni/GPL attributes to compact, refined grain structure leading to minimal grain pull-out during wear cycles which was also assured by less severe micro-ploughing in Ni/GPL compared to severe micro-cutting in steel. The predictions and experimental results were in good-agreement. Modelling of synergistic effects of wear-corrosion applied to nano-composite coatings have never been presented prior to this research. The significance of this work in terms of precision based wear-corrosion synergistic analysis, modelling and predictive techniques is evident from various industrial applications. This work will bring impacts for both in-situ and remote sensor based condition monitoring techniques to automotive, locomotive, aerospace, precision manufacturing and wind turbine industries.

https://eprints.bournemouth.ac.uk/30200/

https://www.sciencedirect.com/science/article/pii/S0301679X18300276

Source: Manual

Synergistic Wear-Corrosion Analysis and Modelling of Nanocomposite Coatings.

Authors: Nazir, H., Khan, Z.A., Saeed, A., Siddaiah, A. and Menezes, P.L.

Journal: Tribology International

Volume: 121

Issue: May

Pages: 30-44

ISSN: 0301-679X

Abstract:

This paper presents analysis and modelling of synergistic wear-corrosion performance of Nickel-Graphene (Ni/GPL) nanocomposite coating and compares it with un-coated steel 1020 under reciprocating-sliding contact. A novel synergistic wear-corrosion prediction model incorporating Archard description with nano-mechanics and electrochemistry was developed for Ni/GPL and steel 1020. The model is equally applicable to any kind of nanocomposite coating and bulk material like metals. For various nanocomposite coatings; their respective mechanical parameters should be used as inputs such as poisons ratio (v), Elastic Modulus (E), Hardness (H), Coefficient of Thermal Elastic mismatch (CTE) and intrinsic grain size (Do). The synergistic wear-corrosion effects were significantly-prominent in steel compared to Ni/GPL especially under contaminated lubricating oil conditions. This behaviour of Ni/GPL attributes to compact, refined grain structure leading to minimal grain pull-out during wear cycles which was also assured by less severe micro-ploughing in Ni/GPL compared to severe micro-cutting in steel. The predictions and experimental results were in good-agreement. Modelling of synergistic effects of wear-corrosion applied to nano-composite coatings have never been presented prior to this research. The significance of this work in terms of precision based wear-corrosion synergistic analysis, modelling and predictive techniques is evident from various industrial applications. This work will bring impacts for both in-situ and remote sensor based condition monitoring techniques to automotive, locomotive, aerospace, precision manufacturing and wind turbine industries.

https://eprints.bournemouth.ac.uk/30200/

Source: BURO EPrints