Abstract
AbstractSuperlattices made of alternating blocks of the phase change compound Sb$$_2$$
2
Te$$_3$$
3
and of TiTe$$_2$$
2
confining layers have been recently proposed for applications in neuromorphic devices. The Sb$$_2$$
2
Te$$_3$$
3
/TiTe$$_2$$
2
heterostructure allows for a better control of multiple intermediate resistance states and for a lower drift with time of the electrical resistance of the amorphous phase. However, Sb$$_2$$
2
Te$$_3$$
3
suffers from a low data retention due to a low crystallization temperature T$$_x$$
x
. Substituting Sb$$_2$$
2
Te$$_3$$
3
with a phase change compound with a higher T$$_x$$
x
, such as GeTe, seems an interesting option in this respect. Nanoconfinement might, however, alters the crystallization kinetics with respect to the bulk. In this work, we investigated the crystallization process of GeTe nanoconfined in geometries mimicking GeTe/TiTe$$_2$$
2
superlattices by means of molecular dynamics simulations with a machine learning potential. The simulations reveal that nanoconfinement induces a mild reduction in the crystal growth velocities which would not hinder the application of GeTe/TiTe$$_2$$
2
heterostructures in neuromorphic devices with superior data retention.
Publisher
Springer Science and Business Media LLC
Cited by
1 articles.
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