Abstract
Corresponding to the principles of biological synapses, an essential prerequisite for hardware neural networks using electronics devices is the continuous regulation of conductance. We implemented artificial synaptic characteristics in a (GeTe/Sb2Te3)16 iPCM with a superlattice structure under optimized identical pulse trains. By atomically controlling the Ge switch in the phase transition that appears in the GeTe/Sb2Te3 superlattice structure, multiple conductance states were implemented by applying the appropriate electrical pulses. Furthermore, we found that the bidirectional switching behavior of a (GeTe/Sb2Te3)16 iPCM can achieve a desired resistance level by using the pulse width. Therefore, we fabricated a Ge2Sb2Te5 PCM and designed a pulse scheme, which was based on the phase transition mechanism, to compare to the (GeTe/Sb2Te3)16 iPCM. We also designed an identical pulse scheme that implements both linear and symmetrical LTP and LTD, based on the iPCM mechanism. As a result, the (GeTe/Sb2Te3)16 iPCM showed relatively excellent synaptic characteristics by implementing a gradual conductance modulation, a nonlinearity value of 0.32, and 40 LTP/LTD conductance states by using identical pulse trains. Our results demonstrate the general applicability of the artificial synaptic device for potential use in neuro-inspired computing and next-generation, non-volatile memory.
Highlights
As artificial intelligence (AI) technologies have recently generated considerable research interest, technological advancements for handling large amounts of data are increasingly necessary [1,2,3]
It can be seen that the full width at half maximum (FWHM) of the peaks in the (00l) direction are broadened in the (GeTe/Sb2 Te3 )16 structure
GeTe/Sb2 Te3 with a superlattice structure based on interfacial phase change memory
Summary
As artificial intelligence (AI) technologies have recently generated considerable research interest, technological advancements for handling large amounts of data are increasingly necessary [1,2,3]. Based on this melting-quenching mechanism, the change in analog conductance for neuro-inspired computing in phase change materials can be classified according to the volume ratio of the crystalline and amorphous states [2,9] Due to these characteristics, GST225 is well known to have advantages in terms of scalability, reliability, and multi-level resistance programming. It is difficult to precisely control the phase change volume to implement gradual conductance state changes and long-term potentiation (LTP) and longterm depression (LTD), which are used to emulate synaptic weight [9] This issue can be overcome with the use of 2-PCM architecture and peripheral circuit design, there are still limitations with respect to complex device operation and scalability [12]. Films and (GeTe/Sb2 Te3 ) interfacial materials fabricated with different annealing temperatures
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