Robust Metal and Semiconductor Phase Transition Memristor Using Ag‐Intercalated Transition Metal Dichalcogenide

Metal (1T/1T')-semiconductor (2H) phase transition memristors (PTMEMs) based on intercalated alkali metal ions (Li<sup>+</sup>) in transition metal dichalcogenides (TMDs) exhibit excellent electrical properties, including heterosynaptic plasticity. However, the low stability of Li<sup>+</sup> ions limits retention and on/off ratios of the PTMEMs. Here, a phase transition in MoTe<sub>2</sub> induced by intercalated Ag<sup>+</sup> ions is demonstrated for the first time, enabling robust memristor operation. The migration of Ag<sup>+</sup> ions, controlled by voltage biases, clearly realizes reversible 2H-1T/1T' phase transitions, as revealed by transmission electron microscopy, X-ray photoelectron spectroscopy, and Raman mapping. The memristive mechanism of MoTe<sub>2</sub> shifts from doping (4-8 h) to phase transition (12 h) as Ag intercalation time increases, achieving a 200 000 on/off ratio at a 4 nm thickness. MoTe<sub>2</sub> exhibits the most evident phase transition due to its low transition barrier (0.84) compared to other TMDs (>1.22). Intercalated Ag<sup>+</sup> ions provide outstanding memristive performance over Li<sup>+</sup> ions, with a 100 times higher on/off ratio, 300 times better retention, and 8 times lower non-linearity (β<sub>Ag</sub> = 0.5-0.6, β<sub>Li</sub> = 4.0). Ag<sup>+</sup>MoTe<sub>2</sub> PTMEM achieves 91.7% accuracy in MNIST recognition, surpassing the 81.7% accuracy of Li<sup>+</sup>MoS<sub>2</sub> PTMEM. These findings demonstrate that Ag<sup>+</sup>MoTe<sub>2</sub> PTMEM holds great potential for advanced memory-based neural network applications.

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Publication Details

Journal
Advanced Materials
Published
2025-10-27
DOI
https://doi.org/10.1002/adma.202516115
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46
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Robust Metal and Semiconductor Phase Transition Memristor Using Ag‐Intercalated Transition Metal Dichalcogenide

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Robust Metal and Semiconductor Phase Transition Memristor Using Ag‐Intercalated Transition Metal Dichalcogenide

Heejun Yang, Ji Son, Whan Kyun Kim, Woo Jong Yu, Gil Young Cho, Min Seok Kim, Thi Thanh Huong Vu, Yong Seon Shin, Yong Ha Shin, Huang Yun
article en
2 citations

Abstract

Metal (1T/1T')-semiconductor (2H) phase transition memristors (PTMEMs) based on intercalated alkali metal ions (Li<sup>+</sup>) in transition metal dichalcogenides (TMDs) exhibit excellent electrical properties, including heterosynaptic plasticity. However, the low stability of Li<sup>+</sup> ions limits retention and on/off ratios of the PTMEMs. Here, a phase transition in MoTe<sub>2</sub> induced by intercalated Ag<sup>+</sup> ions is demonstrated for the first time, enabling robust memristor operation. The migration of Ag<sup>+</sup> ions, controlled by voltage biases, clearly realizes reversible 2H-1T/1T' phase transitions, as revealed by transmission electron microscopy, X-ray photoelectron spectroscopy, and Raman mapping. The memristive mechanism of MoTe<sub>2</sub> shifts from doping (4-8 h) to phase transition (12 h) as Ag intercalation time increases, achieving a 200 000 on/off ratio at a 4 nm thickness. MoTe<sub>2</sub> exhibits the most evident phase transition due to its low transition barrier (0.84) compared to other TMDs (>1.22). Intercalated Ag<sup>+</sup> ions provide outstanding memristive performance over Li<sup>+</sup> ions, with a 100 times higher on/off ratio, 300 times better retention, and 8 times lower non-linearity (β<sub>Ag</sub> = 0.5-0.6, β<sub>Li</sub> = 4.0). Ag<sup>+</sup>MoTe<sub>2</sub> PTMEM achieves 91.7% accuracy in MNIST recognition, surpassing the 81.7% accuracy of Li<sup>+</sup>MoS<sub>2</sub> PTMEM. These findings demonstrate that Ag<sup>+</sup>MoTe<sub>2</sub> PTMEM holds great potential for advanced memory-based neural network applications.

Advanced MaterialsVol. 38(5)
Korea Advanced Institute of Science and Technology (KR), Samsung (South Korea) (KR), Sungkyunkwan University (KR)
Openalex Percentile: Top 15%
Advanced Memory and Neural Computing
1.46
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