The resistance drift phenomenon observed in amorphous chalcogenide phase-change materials (PCMs) hinders the development of PCM-based neuro-inspired computing devices. It has been observed that the drift in electrical resistance can be effectively reduced by substituting Ge with Sn in the prototype PCM GeTe, forming amorphous (Ge1-xSnx)Te solids. However, the atomistic and chemical origin of such drift suppression phenomenon remains unclear. In this work, we carry out thorough ab initio simulations and chemical bonding analyses of amorphous Ge-Sn-Te materials. We show that the two critical driving forces for glass relaxation in PCMs, i.e. the amount of tetrahedral motifs and the degree of Peierls distortion, are gradually reduced as Sn content increases. Such trend can be explained by the increased ionicity brought about by the Ge → Sn substitution. Our work suggests that an optimal Sn-rich GeSnTe composition could be reached for PCM-based neuro-inspired computing with ultralow resistance drift.
Chemical understanding of resistance drift suppression in Ge-Sn-Te phase-change memory materials / Chen, Y.; Sun, L.; Zhou, Y.; Zewdie, G. M.; Deringer, V. L.; Mazzarello, R.; Zhang, W.. - In: JOURNAL OF MATERIALS CHEMISTRY. C. - ISSN 2050-7534. - 8:1(2020), pp. 71-77. [10.1039/c9tc04810c]
Chemical understanding of resistance drift suppression in Ge-Sn-Te phase-change memory materials
Mazzarello R.;
2020
Abstract
The resistance drift phenomenon observed in amorphous chalcogenide phase-change materials (PCMs) hinders the development of PCM-based neuro-inspired computing devices. It has been observed that the drift in electrical resistance can be effectively reduced by substituting Ge with Sn in the prototype PCM GeTe, forming amorphous (Ge1-xSnx)Te solids. However, the atomistic and chemical origin of such drift suppression phenomenon remains unclear. In this work, we carry out thorough ab initio simulations and chemical bonding analyses of amorphous Ge-Sn-Te materials. We show that the two critical driving forces for glass relaxation in PCMs, i.e. the amount of tetrahedral motifs and the degree of Peierls distortion, are gradually reduced as Sn content increases. Such trend can be explained by the increased ionicity brought about by the Ge → Sn substitution. Our work suggests that an optimal Sn-rich GeSnTe composition could be reached for PCM-based neuro-inspired computing with ultralow resistance drift.File | Dimensione | Formato | |
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