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Скачать или смотреть Atomistic simulation of phase change materials for non-volatile memories

  • Institut Català de Nanociència i Nanotecnologia
  • 2021-12-09
  • 397
Atomistic simulation of phase change materials for non-volatile memories
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Описание к видео Atomistic simulation of phase change materials for non-volatile memories

By Marco Bernasconi (Department of Materials Science, University of Milano-Bicocca)

Title: Atomistic simulation of phase change materials for non-volatile memories

Abstract:
Phase change chalcogenide alloys are among the most promising materials for in-memory computing and for the emulation of synapses and neurons in neural network devices. These applications rest on a fast and reversible transformation between the amorphous and crystalline phases induced by Joule heating. The large difference in the electrical resistivity between the two phases enable encoding a binary, multilevel or even analogical information if partial crystallization could be controlled. The same features are exploited in phase change electronic memories (PCMs) which already entered the global market as a first example of storage class memories that combine non-volatility with access time close to that of the volatile DRAM. Materials in the same class are also investigated for embedded phase change memories operating at high temperatures for the automotive sector. In this talk, we will discuss two recent examples on the use of electronic structure calculations to elucidate the relationship between the structure and composition of phase change alloys and their functional properties exploited in the devices. In the first example, we will discuss the results of high throughput DFT calculations aimed at tuning the composition of GeSbTe ternary alloys to raise their crystallization temperature. The second example addresses the effect of confinement on the crystallization kinetics of ultrathin films of Sb which is an example of a monoatomic phase change material. Large scale simulations of Sb in confined geometries have been performed by using an interatomic potential generated by fitting a large DFT database with a neural network method.

The INTERSECT Workshop was held in Barcelona, at UAB’s Casa Convalescència, on November 10-12 2021.
For more information about the workshop: https://intersect-workshop.icn2.cat/

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 814487.

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