Role of vacancies in metal–insulator transitions of crystalline phase-change materials

Abstract

The study of metal-insulator transitions in crystalline solids is a subject of paramount importance, both from the fundamental point of view and for its relevance to the transport properties of materials. Recently, a metal-insulator transition governed by disorder was observed in crystalline phase-change materials. Here we report on calculations employing Density Functional Theory, which identify the microscopic mechanism that localizes the wave functions and is driving this transition. We show that, in the insulating phase, the electronic states responsible for charge transport are localized inside regions having large vacancy concentrations. The transition to the metallic state is driven by the dissolution of these vacancy clusters and the formation of ordered vacancy layers. These results provide important insights on controlling the wave function localization, which should help to develop conceptually new devices based on multiple resistance states.

Aging mechanisms in amorphous phase-change materials

“…From the bonding and aging points of view this solid is representative of a wider class of PCMs located on the pseudobinary line between GeTe and Sb 2 Te 3 [23][24][25] . Our combined computational and experimental investigation elucidates the microscopic mechanisms responsible for aging in amorphous GeTe.…”

Carbon doping induced Ge local structure change in as-deposited Ge2Sb2Te5 film by EXAFS and Raman spectrum

“…On the contrary, the TCR of C6.7-GST is -2.2×10 -3 , showing a remarkable semiconductor behavior. Given that the transition to the metallic state is driven by vacancy ordering in GST, 25,26 however, C6.7-GST, annealed at 420 • C, hasn't undergone metalinsulator transition (MIT). We can reasonable infer that carbon atoms may occupy the vacancy site and/or the interstitial site of crystalline CGST to impede the ordering of vacancy process in CGST, which will be discussed further below.…”

Recent Advances in the Korringa-Kohn-Rostoker Green Function Method

“…The computing time increases as N 2 , if no compromise on the accuracy is made, and only as N, if small errors in total energies are tolerated. In this way, the KKR-GF methods was applied to date for large systems with 4096 cells to study the role of vacancies in metal-insulator transitions of the phase-change material GeSb 2 Te 4 [13], with 1024 cells to study the role of vacancy clustering on the superparamagnetism in Gd-doped GaN [14] and with 2048 cells to study the force field pattern around antisite defects in a shape memory alloy [15].…”