D. Utt

activity

20202024

collaborators

3 papers

cond-mat.mtrl-sci2024

Crystal structure identification with 3D convolutional neural networks with application to high-pressure phase transitions in SiO $_{2}$

Linus C. Erhard, Daniel Utt, Arne J. Klomp +1

Efficient, reliable and easy-to-use structure recognition of atomic environments is essential for the analysis of atomic scale computer simulations. In this work, we train two neur…

cond-mat.mtrl-sci2021

Thermodynamics of vacancies in concentrated solid solutions: From dilute Ni-alloys to the Cantor system

Daniel Utt, Alexander Stukowski, Karsten Albe

The vacancy concentration at finite temperatures is studied for a series of (CoCrFeMn) $_{1 - x_{Ni}}$ Ni $_{x_{Ni}}$ alloys by grand-canonical Monte-Carlo (MC) simulation…

cond-mat.mtrl-sci2020

Experimental and theoretical study of tracer diffusion in a series of (CoCrFeMn) $_{100 - x}$ Ni $_{x}$ alloys

Josua Kottke, Daniel Utt, Mathilde Laurent-Brocq +8

Tracer diffusion of all constituting elements is studied at various temperatures in a series of (CoCrFeMn) $_{100 - x}$ Ni $_{x}$ alloys with compositions ranging from pure Ni to the equi…

Crystal structure identification with 3D convolutional neural networks with application to high-pressure phase transitions in SiO2​

Thermodynamics of vacancies in concentrated solid solutions: From dilute Ni-alloys to the Cantor system

Experimental and theoretical study of tracer diffusion in a series of (CoCrFeMn)100−x​Nix​ alloys

Crystal structure identification with 3D convolutional neural networks with application to high-pressure phase transitions in SiO $_{2}$

Experimental and theoretical study of tracer diffusion in a series of (CoCrFeMn) $_{100 - x}$ Ni $_{x}$ alloys