摘要
By controlling the amorphous-to-crystalline relative volume,chalcogenide phase-change memory materials can provide multi-level data storage(MLS),which offers great potential for high-density storageclass memory and neuro-inspired computing.However,this type of MLS system suffers from high power consumption and a severe time-dependent resistance increase(‘‘drift")in the amorphous phase,which limits the number of attainable storage levels.Here,we report a new type of MLS system in yttriumdoped antimony telluride,utilizing reversible multi-level phase transitions between three states,i.e.,amorphous,metastable cubic and stable hexagonal crystalline phases,with ultralow power consumption(0.6–4.3 p J)and ultralow resistance drift for the lower two states(power-law exponent<0.007).The metastable cubic phase is stabilized by yttrium,while the evident reversible cubic-to-hexagonal transition is attributed to the sequential and directional migration of Sb atoms.Finally,the decreased heat dissipation of the material and the increase in crystallinity contribute to the overall high performance.This study opens a new way to achieve advanced multi-level phase-change memory without the need for complicated manufacturing procedures or iterative programming operations.
硫系相变存储材料能够通过调控非晶相与晶相体积占比的方式实现多级信息存储,在高密度信息存储和神经元计算等领域展现出巨大潜力.然而,多级信息存储多饱受器件功耗过高以及电阻漂移严重的困扰.基于此,本文报道了一种新型钇掺杂碲化锑多级信息存储体系.该体系存在基于非晶相、亚稳立方相以及稳定六方相之间的多级可逆相变,并具有超低器件功耗(0.6~4.3 p J)和超低电阻漂移系数(<0.007).研究表明,钇掺杂能够提高碲化锑立方相稳定性,Sb原子的顺序和定向迁移导致了立方相与六方相之间的可逆转变.这项研究开辟了一条不需要复杂制造过程或迭代编程操作即可实现先进多级相变存储的新途径.
作者
Bin Liu
Kaiqi Li
Wanliang Liu
Jian Zhou
Liangcai Wu
Zhitang Song
Stephen R.Elliott
Zhimei Sun
刘宾;李开旗;刘万良;周健;吴良才;宋志棠;Stephen R.Elliott;孙志梅(School of Materials Science and Engineering,Beihang University,Beijing 100191,China;Center for Integrated Computational Materials Engineering,International Research Institute for Multidisciplinary Science,Beihang University,Beijing 100191,China;State Key Laboratory of Functional Materials for Informatics,Shanghai Institute of Microsystem and Information Technology,Chinese Academy of Sciences,Shanghai 200050,China;College of Science,Donghua University,Shanghai 201620,China;Department of Chemistry,University of Cambridge,Cambridge CB21EW,UK;Physical and Theoretical Chemistry Laboratory,University of Oxford,Oxford OX13QZ,UK)
基金
the National Key Research and Development Program of China(2017YFB0701700)
the National Natural Science Foundation of China(51872017)
the High-Performance Computing(HPC)Resources at Beihang University。
