Kim, Y.-J.; Kim, H.; Kang, M.; Rhee, K.; Shin, S. Y.; Lee, S.: Correlation of microstructure, chip-forming properties, and dynamic torsional properties in free-machining steels. Metallurgical and Materials Transactions A 44 (10), pp. 4613 - 4625 (2013)
Shin, S. Y.: Effects of microstructure on tensile, charpy impact, and crack tip opening displacement properties of two API X80 pipeline steels. Metallurgical and Materials Transactions A 44 (6), pp. 2613 - 2624 (2013)
Sohn, S. S.; Han, S. Y.; Shin, S. Y.; Bae, J.; Lee, S.: Effects of microstructure and pre-strain on Bauschinger effect in API X70 and X80 linepipe steels. Metals and Materials International 19 (3), pp. 423 - 431 (2013)
Sohn, S. S.; Han, S. Y.; Shin, S. Y.; Bae, J.; Lee, S.: Analysis and estimation of the yield strength of API X70 and X80 linepipe steels by double-cycle simulation tests. Metals and Materials International 19 (3), pp. 377 - 388 (2013)
Kim, H.; Kang, M.; Shin, S. Y.; Lee, S.: Alligatoring phenomenon occurring during hot rolling of free-machining steel wire rods. Materials Science and Engineering A: Structural Materials Properties Microstructure and Processing 568, pp. 8 - 19 (2013)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…