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      Carbon steel corrosion: a review of key surface properties and characterization methods

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          Abstract

          The effects of surface morphology, defects, texture and energy on carbon steel corrosion are elucidated along with relevant characterization methods.

          Corrosion is a subject of interest to interdisciplinary research communities, combining fields of materials science, chemistry, physics, metallurgy and chemical engineering. In order to understand mechanisms of corrosion and the function of corrosion inhibitors, the reactions at the interfaces between the corrosive electrolyte and a steel surface, particularly at the initial stages of the corrosion process, need to be described. Naturally, these reactions are strongly affected by the nature and properties of the steel surfaces. It is however seen that the majority of recent corrosion and corrosion-inhibition investigations are limited to electrochemical testing, with ex situ analysis of the treated steels (post-exposure analysis). The characterization of materials and their surface properties, such as texture and morphology, are not being considered in most studies. Similarly, in situ investigations of the initial stages of the corrosion reactions using advanced surface characterization techniques are scarce. In this review, attention is brought to the importance of surface features of carbon steels, such as texture and surface energy, along with defects dislocation related to mechanical processing of carbon steels. This work is extended to a critical review of surface analytical techniques used for characterization of carbon steels in corrosive media with particular focus on examining steel surfaces treated with corrosion inhibitors. Further, emerging surface analysis techniques and their applicability to analyse carbon steels in corrosive media are discussed. The importance of surface properties is commonly addressed by surface scientists as well as researchers in other chemistry fields such as nanotechnology, fuel cells, and catalysis. This article is expected to appeal to a broad scientific community, including but not limited to corrosion scientists, material chemists, analytical chemists, metal physicists, corrosion and materials engineers.

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          Progess in superhydrophobic surface development

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            Superhydrophobic surfaces

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              Magnetic relaxation switches capable of sensing molecular interactions.

              Highly sensitive, efficient, and high-throughput biosensors are required for genomic and proteomic data acquisition in complex biological samples and potentially for in vivo applications. To facilitate these studies, we have developed biocompatible magnetic nanosensors that act as magnetic relaxation switches (MRS) to detect molecular interactions in the reversible self-assembly of disperse magnetic particles into stable nanoassemblies. Using four different types of molecular interactions (DNA-DNA, protein-protein, protein-small molecule, and enzyme reactions) as model systems, we show that the MRS technology can be used to detect these interactions with high efficiency and sensitivity using magnetic relaxation measurements including magnetic resonance imaging (MRI). Furthermore, the magnetic changes are detectable in turbid media and in whole-cell lysates without protein purification. The developed magnetic nanosensors can be used in a variety of biological applications such as in homogeneous assays, as reagents in miniaturized microfluidic systems, as affinity ligands for rapid and high-throughput magnetic readouts of arrays, as probes for magnetic force microscopy, and potentially for in vivo imaging.
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                Author and article information

                Journal
                RSCACL
                RSC Advances
                RSC Adv.
                Royal Society of Chemistry (RSC)
                2046-2069
                2017
                2017
                : 7
                : 8
                : 4580-4610
                Article
                10.1039/C6RA25094G
                0a867d41-c833-4974-8b71-6811f78a7670
                © 2017
                History

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