1. Evangelos Eleftheriou, IBM Fellow
IBM Research – Zurich
Bleeding Edge Next-Generation
Memory Technologies

2. ❑ It is possible to store multiple levels of information in a single
PCM cell by modulating the thickness of the amorphous region
❑ Key enabling technologies
‒ Iterative programming
‒ Non-resistance-based cell state metrics
‒ Drift-resilient detectors
‒ Drift model
G. Close et al., Proc. IEDM, 2010
N. Papandreou et al., Proc. ISCAS., 2011
N. Papandreou et al., Proc. IEDM, 2011
A. Sebastian et al., J. Appl. Phys., 2011
TLC 3 bit/cell storage
Voltage VoltageVoltage
c-GST c-GST
a-GST
Multi-level PCM chip
Drift Model
Multi-Level Phase-Change Memory
A. Sebastian et al., Nature Commun., 2014
M. Stanisavljevic et al., Proc. IRPS, 2015
A. Sebastian et al., Proc. IRPS, 2015
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Demo by
Nikolaos Papandreou

3. ❑ Phase-change memory device in which the physical mechanism
of information storage is decoupled from the information
retrieval process
❑ Exploits the unique nature of electrical transport and structural
dynamics
W. Koelmans et al., Nature Commun., 2015
Projected Memory
Resistance drift Noise
Carbon Memory
❑ Carbon-based resistive memory
– Extreme scalability
– High speed
– Robustness
– Low cost
❑ Resistance switching due to the formation and rupture of
graphitic clusters
❑ Significantly improved endurance with oxygenated
amorphous carbon
A. Sebastian et al., New J. Phys., 2011
L. Dellmann et al., Proc. ESSDERC, 2013
C. Santini et al., Nature Commun., 2015
Demo by
Abu Sebastian

4. Memcomputing:
It is possible to perform relatively high-level
computational tasks such as correlation detection
and factorization using the collective state dynamics
of a large array of phase-change devices
P. Hosseini et al., IEEE Electron. Dev. Lett., 2015
Neuromorphic Computing:
Emulate the biophysics of neurons and synapses
using phase-change devices to perform certain
computational tasks with high areal/energy
efficiency
Non-von Neumann Computing
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Demo by
Angeliki Pantazi

5. Lab Tour! Enjoy.