TY - JOUR
T1 - Phase-change heterostructure enables ultralow noise and drift for memory operation
AU - Ding, Keyuan
AU - Wang, Jiangjing
AU - Zhou, Yuxing
AU - Tian, He
AU - Lu, Lu L.
AU - Mazzarello, Riccardo
AU - Jia, Chunlin
AU - Zhang, Wei
AU - Rao, Feng
AU - Ma, Evan
N1 - Publisher Copyright:
© 2019 American Association for the Advancement of Science. All rights reserved.
PY - 2019/10/11
Y1 - 2019/10/11
N2 - Artificial intelligence and other data-intensive applications have escalated the demand for data storage and processing. New computing devices, such as phase-change random access memory (PCRAM)–based neuro-inspired devices, are promising options for breaking the von Neumann barrier by unifying storage with computing in memory cells. However, current PCRAM devices have considerable noise and drift in electrical resistance that erodes the precision and consistency of these devices. We designed a phase-change heterostructure (PCH) that consists of alternately stacked phase-change and confinement nanolayers to suppress the noise and drift, allowing reliable iterative RESET and cumulative SET operations for high-performance neuro-inspired computing. Our PCH architecture is amenable to industrial production as an intrinsic materials solution, without complex manufacturing procedure or much increased fabrication cost.
AB - Artificial intelligence and other data-intensive applications have escalated the demand for data storage and processing. New computing devices, such as phase-change random access memory (PCRAM)–based neuro-inspired devices, are promising options for breaking the von Neumann barrier by unifying storage with computing in memory cells. However, current PCRAM devices have considerable noise and drift in electrical resistance that erodes the precision and consistency of these devices. We designed a phase-change heterostructure (PCH) that consists of alternately stacked phase-change and confinement nanolayers to suppress the noise and drift, allowing reliable iterative RESET and cumulative SET operations for high-performance neuro-inspired computing. Our PCH architecture is amenable to industrial production as an intrinsic materials solution, without complex manufacturing procedure or much increased fabrication cost.
UR - https://www.scopus.com/pages/publications/85073125117
U2 - 10.1126/science.aay0291
DO - 10.1126/science.aay0291
M3 - 文章
C2 - 31439757
AN - SCOPUS:85073125117
SN - 0036-8075
VL - 366
SP - 210
EP - 215
JO - Science
JF - Science
IS - 6462
ER -