Jakub Nowak | Searcharxiv

arXiv2021

Control of Electrochemical Corrosion Properties by Influencing Mn Partitioning through Intercritically Annealing of Medium-Mn Steel

Medium-Mn steels exhibit excellent mechanical properties and lower production costs compared to high-Mn steels, which makes them a potential material for future application in the automotive industry. Intercritical annealing (ICA) after cold rolling allows to control the stacking fault energy (SFE) of austenite, the fraction of ferrite and reverted austenite, and the element partitioning (especially Mn). Although Mn deteriorates the corrosion behavior of Fe-Mn-Al alloys, the influence of austenite fraction and element partitioning of Mn on the electrochemical corrosion behavior has not been investigated yet. Therefore, the electrochemical corrosion behavior in 0.1 M H2SO4 of X6MnAl12-3, which was intercritically annealed for 2 h at 550 °C, 600 °C and 700 °C, was investigated by potentiodynamic polarization (PDP), electrochemical impedance spectroscopy (EIS) and mass spectroscopy with inductively coupled plasma (ICP-MS). Additionally, specimens after 1 h and 24 h of immersion were examined via SEM to visualize the corrosion damage. The ICA specimens showed a selective dissolution of reverted austenite due to its micro-galvanic coupling with the adjacent ferrite. The severity of the micro-galvanic coupling can be reduced by decreasing the interface area as well as the chemical gradient of mainly Mn between ferrite and reverted austenite by ICA.

cond-mat.mtrl-sci↗

arXiv2019

Hypernetwork functional image representation

Motivated by the human way of memorizing images we introduce their functional representation, where an image is represented by a neural network. For this purpose, we construct a hypernetwork which takes an image and returns weights to the target network, which maps point from the plane (representing positions of the pixel) into its corresponding color in the image. Since the obtained representation is continuous, one can easily inspect the image at various resolutions and perform on it arbitrary continuous operations. Moreover, by inspecting interpolations we show that such representation has some properties characteristic to generative models. To evaluate the proposed mechanism experimentally, we apply it to image super-resolution problem. Despite using a single model for various scaling factors, we obtained results comparable to existing super-resolution methods.

cs.LG↗