activity
20202026
most citedMachine learning plastic deformation of crystals

102 citations · 121 across the 8 of their papers we have counts for

collaborators

9 papers

cond-mat.mtrl-sci2026★ 8 cited

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…

cond-mat.mtrl-sci2026

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…

cond-mat.mtrl-sci2025★ 6 cited

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.…

cond-mat.mtrl-sci2025

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…

cond-mat.mtrl-sci2024

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…

cond-mat.stat-mech2024

Avalanches in CuZrAl metallic glasses

Tero Mäkinen, Anshul D. S. Parmar, Silvia Bonfanti +1

Metallic glasses have mechanical properties, which exhibit avalanches in the disguise of stress drops. We study these phenomena in a classical metallic glass system CuZrAl by ather…

cond-mat.stat-mech2024★ 4 cited

Effect of quenched heterogeneity on creep lifetimes of disordered materials

Juan Carlos Verano-Espitia, Jérôme Weiss, David Amitrano +2

We revisit the problem of describing creep in heterogeneous materials by an effective temperature by considering more realistic (and complex) non-mean-field elastic redistribution…

cond-mat.dis-nn2023★ 1 cited

Transmutation-accelerated sampling method for multi-component ZrCu(Al) metallic glasses

Filip Kaskosz, Rene Alvarez-Donado, Mikko Alava +2

We investigate multi-component metallic glass systems using a hybrid Molecular Dynamics (MD) and Variance-Constrained Semi-Grand Canonical approach. This method enables us to gener…

cond-mat.dis-nn2020★ 102 cited

Machine learning plastic deformation of crystals

Henri Salmenjoki, Mikko J. Alava, Lasse Laurson

Plastic deformation of micron-scale crystalline solids exhibits stress-strain curves with significant sample-to-sample variations. It is a pertinent question if this variability is…