Metallurgical Research & Technology 2019 Best Paper Award (November 2020)

In free access!

We are delighted to announce the winner of the Metallurgical Research & Technology 2019 Best Paper Award.

The Metallurgical Research & Technology Best Paper Award honors the author(s) of a paper of exceptional merit dealing with research and/or industrial aspects in metallurgy and bringing an outstanding contribution to the field. All articles published during the current year prior to the award, including Short Communications, Regular articles, Reviews and Topical contributions, can be considered for an award. The editorial committee meets every year, in December, to judge the best papers according to the criteria of originality, innovation, significance to the research community, industrial relevance, technical excellence, impact, and clarity of presentation.

The authors of the awarded articles are offered a book from the EDP Sciences catalogue. In addition, they are given the possibility to publish a press release about their work and/or their laboratory/team. Finally, the selected articles are turned into free access so that all readers can have a chance to read them.

First prize winner

Aurélie Franceschini, Fabienne Ruby-Meyer, Fabien Midroit, Bandiougou Diawara, Stéphane Hans, Thibault Poulain, Cédric Trempont, Eric Hénault and Anne-Laure Rouffié for their article "An assessment of cleanliness techniques for low alloyed steel grades", published in Metall. Res. Technol. 116, 509 (2019).

About the article


High cleanliness materials for applications such as aerospace or automotive are in full development. Because of the low volume fraction of inclusions, the standard methods of characterization have reached their limits to discriminate materials by cleanliness level. In order to find a new method, complementary techniques were tested, such as high-frequency (80 MHz) ultrasonic testing, X-ray tomography or Extreme Value Analysis (EVA). The micro-cleanliness was also characterized by standard methods based on observations of polished surfaces by light optical or scanning electronic microscopy. The combination of these techniques, enhanced by metiS software calculations, allows us to determine the complete 3D distribution of oxides or to estimate the probability of largest inclusion size by modelling virtual samples. At the end, fatigue testing was performed in order to try to link fatigue results to previous characterization outcomes.