ORCID Profile
0000-0003-1584-6941
Current Organisation
Deakin University
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Publisher: Springer Science and Business Media LLC
Date: 26-08-2020
DOI: 10.1007/S10853-020-05109-0
Abstract: Metal additive manufacturing (AM), also known as 3D printing, is a disruptive manufacturing technology in which complex engineering parts are produced in a layer-by-layer manner, using a high-energy heating source and powder, wire or sheet as feeding material. The current paper aims to review the achievements in AM of steels in its ability to obtain superior properties that cannot be achieved through conventional manufacturing routes, thanks to the unique microstructural evolution in AM. The challenges that AM encounters are also reviewed, and suggestions for overcoming these challenges are provided if applicable. We focus on laser powder bed fusion and directed energy deposition as these two methods are currently the most common AM methods to process steels. The main foci are on austenitic stainless steels and maraging recipitation-hardened (PH) steels, the two so far most widely used classes of steels in AM, before summarising the state-of-the-art of AM of other classes of steels. Our comprehensive review highlights that a wide range of steels can be processed by AM. The unique microstructural features including hierarchical (sub)grains and fine precipitates induced by AM result in enhancements of strength, wear resistance and corrosion resistance of AM steels when compared to their conventional counterparts. Achieving an acceptable ductility and fatigue performance remains a challenge in AM steels. AM also acts as an intrinsic heat treatment, triggering ‘in situ’ phase transformations including tempering and other precipitation phenomena in different grades of steels such as PH steels and tool steels. A thorough discussion of the performance of AM steels as a function of these unique microstructural features is presented in this review.
Publisher: Elsevier BV
Date: 04-2020
Publisher: Elsevier BV
Date: 04-2020
Publisher: Elsevier BV
Date: 12-2021
Publisher: Elsevier BV
Date: 09-2011
Publisher: Emerald
Date: 23-03-2010
DOI: 10.1108/00035591011028041
Abstract: Uniform nanostructured TiO 2 thin film has been applied as an over coat on micro‐arc oxidized substrate, using the sol‐gel method. The anticorrosion performance of the coating have been evaluated using electrochemical techniques. Owing to increasing application of light alloys in industry, the purpose of this paper is to report effort to increase the corrosion and wear resistance properties of these alloys by applying a TiO 2 nanostructured coating using the sol‐gel method on the micro‐arc oxidation (MAO) surface. This approach will decrease the time for the MAO process, especially for achieving good mechanical properties, and will minimize energy consumption as well as achieving better results from the obtained coatings. Sol‐gel coatings were deposited (on titanium substrates) by spin coating techniques. The morphologies and nanostructures of thin films were analyzed using scanning electron microscope, atomic force microscopy and grazing incidence X‐ray diffraction (XRD). The anticorrosion performance of the coating has been evaluated by using electrochemical techniques. Tafel polarization measurements provide an explanation for the increased resistance of nanostructured TiO 2 coated specimen against corrosion. Effective sol‐gel coating parameters were optimized with respect to this enhancement. Electrochemical impedance spectroscopy measurements showed the role of barrier layer on corrosion resistance of MAO and nanostructured TiO 2 coating. The results showed that i corr is decreased from 0.258 to 0.169 ( μ A/cm 2 ). An optimized TiO 2 nanostructured coating with thickness of 74 nm will shift the open circuit potential (OCP) about 165 mV and will improve the corrosion prevention properties of coated s les. Corrosion resistance by these duplex coatings can be improved by a factor of more than three times, compared to that of the uncoated substrate. Increasing the coating thickness to more than 74 nm will decrease the physical and corrosion properties of coated s les. It can be concluded that s les with the optimized coating showed higher values of charge transfer resistance, due to the presence of a newly formed layer that accounted for the greater corrosion protection. The results obtained in this research into nanostructured coating can be used wherever good corrosion and wear resistances are required. The speed of treatment by this technique makes this method very suitable for industrial surface treatment of different components.
Publisher: Elsevier BV
Date: 07-2019
Publisher: Elsevier BV
Date: 04-2010
Publisher: Springer Science and Business Media LLC
Date: 06-2011
Publisher: Springer Science and Business Media LLC
Date: 08-2014
Publisher: Elsevier BV
Date: 08-2023
Publisher: Elsevier BV
Date: 03-2019
Publisher: Springer Science and Business Media LLC
Date: 20-10-2012
Publisher: Informa UK Limited
Date: 17-12-2020
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 12-2019
Publisher: Elsevier BV
Date: 04-2022
Publisher: Elsevier BV
Date: 07-2011
Publisher: Informa UK Limited
Date: 19-12-2013
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 12-2012
Publisher: MDPI AG
Date: 29-11-2022
DOI: 10.3390/CMD3040037
Abstract: Machine learning (ML) is providing a new design paradigm for many areas of technology, including corrosion inhibition. However, ML models require relatively large and erse training sets to be most effective. This paper provides an overview of developments in corrosion inhibitor research, focussing on how corrosion performance data can be incorporated into machine learning and how large sets of inhibitor performance data that are suitable for training robust ML models can be developed through various corrosion inhibition testing approaches, especially high-throughput performance testing. It examines different types of environments where corrosion by-products and electrolytes operate, with a view to understanding how conventional inhibitor testing methods may be better designed, chosen, and applied to obtain the most useful performance data for inhibitors. The authors explore the role of modern characterisation techniques in defining corrosion chemistry in occluded structures (e.g., lap joints) and examine how corrosion inhibition databases generated by these techniques can be exemplified by recent developments. Finally, the authors briefly discuss how the effects of specific structures, alloy microstructures, leaching structures, and kinetics in paint films may be incorporated into machine learning strategies.
Publisher: Springer Science and Business Media LLC
Date: 11-08-2011
Publisher: Elsevier BV
Date: 06-2011
Publisher: Springer Science and Business Media LLC
Date: 28-11-2012
No related grants have been discovered for MAJID LALEH.