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High-throughput screening to identify two-dimensional layered phase-change chalcogenides for embedded memory applications

来源:    发布时间 : 2025-01-17   点击量:  
年份 专利号
授权公告日 发明人
期号、页码 10, 189 (2024) 期刊名称 npj Computational Materials
文章作者 Suyang Sun, Xiaozhe Wang, Yihui Jiang, Yibo Lei, Siyu Zhang, Sanjay Kumar, Junying Zhang, En Ma, Riccardo Mazzarello, Jiang-Jing Wang & Wei Zhang

Chalcogenide phase-change materials (PCMs) are showing versatile possibilities in cutting-edge applications, including non-volatile memory, neuromorphic computing, and nano-photonics. However, for embedded phase-change memory applications, conventional PCMs suffer from insufficient thermal stability because of their relatively low crystallization temperatures (Tx). Although doping with additional alloying elements could improve the amorphous stability, it also increases the tendency towards compositional partitioning and phase separation. Recently, a two-dimensional (2D) layered compound CrGeTe3 (CrGT) was developed as a PCM, showing a high Tx ~ 276 °C with an inverse change in resistive-switching character upon phase transition. Here, we report a high-throughput materials screening for 2D layered phase-change chalcogenides. We aim to clarify whether the high Tx and the inverse electrical resistance contrast are intrinsic features of 2D PCMs. In total, twenty-five 2D chalcogenides with CrGT trilayer structures have been identified from a large database. We then focused on selected layered tellurides by performing thorough ab initio simulations and experimental investigations and confirming that their amorphous phase indeed has a much higher Tx than conventional PCMs. We attribute this enhanced amorphous stability to the structurally complex nuclei required to render crystallization possible. Overall, we regard InGeTe3 as a balanced 2D PCM with both high thermal stability and large electrical contrast for embedded memory applications.


Link:High-throughput screening to identify two-dimensional layered phase-change chalcogenides for embedded memory applications | npj Computational Materials

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