Nano Colloquia 2022: S3- INTERSECT Seminar by Francesco Tavanti – May 05, 2022 at 15.00 – online

Nano Colloquia 2022: S3- INTERSECT Seminar by Francesco Tavanti – May 05, 2022 at 15.00 – online

Everything is ready for the seminar “Hierarchical ordered structures in amorphous systems”.

Dr. Francesco Tavanti (CNR Nano and INTERSECT researcher) will explain the results obtained during his last researches to all the interested colleagues, students and project partners.

Don’t miss this oppportunity!

Wednesday May 05, 2022 at 15.00 CET – online



Amorphous chalcogenides, such as GexSe1-x, have been proposed as good ovonic switch material candidates for nonvolatile memory and selector devices due to their fast switching, endurance and higher crystallization temperature with respect to standard GST compounds. The structural and electrical properties of GexSe1-x, as for other chalcogenides, are strongly related to the presence of short- and medium-range structures in the amorphous phase that are responsible for the internal structural orders at different length-scales1,2. In order to deeply understand the local geometry-dependent properties of these chalcogenides systems, we employed a combined approach based on both classical molecular dynamics (MD) simulations, innovative analysis techniques3 and ab-initio simulations.

We obtained different information about the nature of the order in these amorphous systems demonstrating that little changes in the stoichiometry greatly affect the GexSe1-x structural and electrical properties and that short- and medium-range order are intrinsically interconnected each other.

The seminar is realized in the framework of the funded project “INTERSECT”  H2020 Grant n. 814487″.


Chai, Z. et al. Dependence of switching probability on operation conditions in GexSe1-x ovonic threshold switching selectors. IEEE Electron Device Letters (2019) doi:10.1109/led.2019.2924270.

Dianat, B., Tavanti, F., Padovani, A., Larcher, L. & Calzolari, A. BELLO: A post-processing tool for the local-order analysis of disordered systems. Computational Materials Science 209, 111381 (2022).

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