102 citations · 121 across the 8 of their papers we have counts for
5 papers · 1 filter
Data-driven body-centered cubic phase prediction in cobalt free high-entropy alloys
Xuliang Luo, Yulin Li, Tero Mäkinen +3
High-entropy alloys (HEAs) are known for superb combination of performance attributes, making them ideal for advanced applications, e.g., nuclear engineering. The concept of cobalt…
Early Prediction of Creep Failure via Bayesian Inference of Evolving Barriers
Juan Carlos Verano-Espitia, Tero Mäkinen, Mikko J. Alava +1
Creep under a sustained load can persist for long times yet culminate in abrupt yielding or rupture, implying a finite lifetime even when the material appears solid. Here, we formu…
Exploring the impact of Ti/Al on L12 nanoprecipitation and deformation behavior in CoNiFeAlTi multi-principal element alloys through atomistic simulations
Amin Esfandiarpour, Anshul D. S. Parmar, Silvia Bonfanti +3
Recent studies on CoNi-based multi-principal element alloys (MPEAs) have demonstrated high strength and ductility, attributed to the formation of stable L12 nanoscale precipitates.…
Efficient training of machine learning potentials for metallic glasses: CuZrAl validation
Antoni Wadowski, Anshul D. S. Parmar, Filip Kaśkosz +4
Interatomic potentials are key to uncovering microscopic structure-property relationships, essential for multiscale simulations and high-throughput experiments. For metallic glasse…
Bayesian exploration of the composition space of CuZrAl metallic glasses for mechanical properties
Tero Mäkinen, Anshul D. S. Parmar, Silvia Bonfanti +1
Designing metallic glasses in silico is a major challenge in materials science given their disordered atomic structure and the vast compositional space to explore. Here, we tackle…