He Qiang   

Associate professor
Supervisor of Master's Candidates
Gender:Male Status:Employed Department:IC College Education Level:Postgraduate (Doctoral) Degree:Doctoral Degree in Engineering Discipline:Microelectronics and Solid-state Electronics

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Language: 中文

Paper Publications

Joule heating induced non-melting phase transition and multi-level conductance in MoTe2 based phase change memory

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Indexed by:Journal paper

Journal:Appl. Phys. Lett.

Included Journals:SCI

Affiliation of Author(s):华中科技大学

Discipline:Engineering

First-Level Discipline:Electronic Science And Technology

Document Type:J

DOI number:10.1063/5.0127160

Abstract:Phase change memory (PCM) is considered as a leading candidate for next generation data storage as well as emerging computing device, but the advancement has been hampered by high switching energy due to the melting process and amorphous relaxation induced large resistance drift. Polymorphic crystal-crystal transition without amorphization in metal dichalcogenides (TMDs) could be employed to solve these issues. Yet, the mechanism is still controversy. A melting-free PCM made of two dimensional (2D) MoTe2, which exhibits unipolar resistive switching (RS) and multi-level states with substantially reduced resistance drift via joule heating, is reported in this work. The device is first prepared based on the temperature dependence of Raman spectrum and electrical transport investigations on MoTe2 films. Significantly improved device performances on energy efficiency, switching speed, and memory window are further achieved by electrode size scaling down, indicating the key role of localized heating. Then, device scale transmission electron microscopy images reveal that the resistive switching stems from the transition between semiconducting 2H phase and metallic 1T0 phase. An entropy induced Te vacancies model is proposed to explain the reversible phase change mechanism in the MoTe2 based device. This study paves the way for further development of PCM based on atomically thin 2D TMDs, aiming for high density storage-class memory and high-precision neuromorphic computing.