
AbstractNeuromorphic devices constitute a novel approach to computing that takes inspiration from the brain to unify the processing and storage units. Memories based on phase‐change materials (PCMs) are potential candidates for such devices due to their non‐volatility and excellent scalability, however their use is hindered by their conductance variability and temporal drift in resistance. Recently, it has been shown that the utilization of phase‐change heterostructures consisting of nanolayers of the Sb2Te3 PCM interleaved with a transition‐metal dichalcogenide, acting as a confinement material, strongly mitigates these problems. In this work, superlattice heterostructures made of TiTe2 and two prototypical PCMs, respectively GeTe and Ge2Sb2Te5 are considered. By performing ab initio molecular dynamics simulations, it is shown that it is possible to switch the PCMs without destroying the superlattice structure and without diffusion of the atoms of the PCM across the TiTe2 nanolayers. In particular, the model containing Ge2Sb2Te5 shows weak coupling between the two materials during the switching process, which, combined with the high stability of the amorphous state of Ge2Sb2Te5, makes it a very promising candidate for neuromorphic computing applications.
phase‐change heterostructures, Science, Q, chalcogenide phase‐change materials; neuromorphic computing; phase‐change heterostructures, chalcogenide phase‐change materials, neuromorphic computing, Research Article
phase‐change heterostructures, Science, Q, chalcogenide phase‐change materials; neuromorphic computing; phase‐change heterostructures, chalcogenide phase‐change materials, neuromorphic computing, Research Article
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
