693.932 PEOPLE
| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Cole, Ivan
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (25/25 displayed)
- 2024Inhibitory behaviour and adsorption stability of benzothiazole derivatives as corrosion inhibitors towards galvanised steelcitations
- 2023Use of sensing, digitisation, and virtual object analyses to refine quality performance and increase production rate in additive manufacturing
- 2023Inhibitory behaviour and adsorption stability of benzothiazole derivatives as corrosion inhibitors towards galvanised steelcitations
- 2023Progress and challenges in making an aerospace component with cold spray additive manufacturing
- 2023A design and optimisation framework for cold spray additive manufacturing of lightweight aerospace structural componentscitations
- 2023Microstructure and mechanical properties of heat-treated cold spray additively manufactured titanium metal matrix compositescitations
- 2023Electrochemical and Surface Characterisation of Carbon Steel Exposed to Mixed Ce and Iodide Electrolytes
- 2022In-situ monitoring of build height during powder-based laser metal depositioncitations
- 2022Predictions of in-situ melt pool geometric signatures via machine learning techniques for laser metal depositioncitations
- 2020Nondestructive quantitative characterisation of material phases in metal additive manufacturing using multi-energy synchrotron X-rays microtomographycitations
- 2018Detection of defects of additively manufactured metal parts via synchrotron X-ray microtomography
- 2016Using high throughput experimental data and in silico models to discover alternatives to toxic chromate corrosion inhibitorscitations
- 2016Modeling corrosion inhibition efficacy of small organic molecules as non-toxic chromate alternatives using comparative molecular surface analysis (CoMSA)citations
- 2015The influence of rare earth mercaptoacetate on the initiation of corrosion on AA2024-T3 Part II: The influence of intermetallic compositions within heavily attacked sitescitations
- 2015The influence of rare earth mercaptoacetate on the initiation of corrosion on AA2024-T3 Part I: Average statistics of each intermetallic compositioncitations
- 2014Towards chromate-free corrosion inhibitors: structure property models for organic alternativescitations
- 2014Microstructure characterisation and reconstruction of intermetallic particlescitations
- 2013In-situ synthesis of functional silica nanoparticles for enhancement the corrosion resistance of TBCscitations
- 2013A corrosion map of Abu Dhabicitations
- 2012The science of pipe corrosion: A review of the literature on the corrosion of ferrous metals in soilscitations
- 2012FIB/SEM study of AA2024 corrosion under a seawater drop. Part IIcitations
- 2011Managing risk of SCC of Fin Fan air cooled heat exchangers
- 2011FIB/SEM study of AA2024 corrosion under a seawater drop: Part Icitations
- 2010Combining green self-healing coatings for metal protectioncitations
- 2010Multilayered coatings: tuneable protection for metalscitations
Places of action
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article
Using high throughput experimental data and in silico models to discover alternatives to toxic chromate corrosion inhibitors
Abstract
Restrictions on the use of toxic chromate-based corrosion inhibitors have created important issues for the aerospace and other industries. Benign alternatives that offer similar or superior performance are needed. We used high throughput experiments to assess 100 small organic molecules as potential inhibitors of corrosion in aerospace aluminium alloys AA2024 and AA7075. We generated robust, predictive, quantitative computational models of inhibitor efficiency at two pH values using these data. The models identified molecular features of inhibitor molecules that had the greatest impact on corrosion inhibition. Models can be used to discover better corrosion inhibitors by screening libraries of organic compounds for candidates with high corrosion inhibition.