Atomistic Mechanisms of the Crystallographic Orientation‐Dependent Cu<sub>1.8</sub>S Conductive Channel Formation in Cu<sub>2</sub>S‐Based Memristors
Achieving multiple types of resistive switching in a single material with controlled ionic motion is a key challenge in neuromorphic computing, traditionally addressed by combining materials with distinct switching behaviors. Here, Cu<sub>2-x</sub>S is identified as a promising candidate to overcome this limitation due to its hierarchical phase transitions. Using in situ biasing experiments, reversible and non-reversible phase transitions (and resistive switching) are demonstrated in γ-Cu<sub>2</sub>S by controlling the compliance current. The formation of parallel high-digenite Cu<sub>1.8</sub>S channels, orientated along the γ-Cu<sub>2</sub>S [201] crystallographic direction, drives the nonvolatile resistive switching. These channels emerge via an intermediate δ-Cu<sub>2</sub>S phase and are stabilized at room temperature by residual strains, alongside β-Cu<sub>2</sub>S phase. The work clarifies the complex, electrically triggered phase transformations in γ-Cu<sub>2</sub>S, and highlights the potential of Cu<sub>2-x</sub>S as a versatile material for neuromorphic computing.
Authors
- Shaobo Cheng (ORCID: https://orcid.org/0000-0001-8791-5315)
- Chongxin Shan (ORCID: https://orcid.org/0000-0001-7119-5325)
- Yi Xu (ORCID: https://orcid.org/0000-0003-1679-3271)
- Dongyang Wang (ORCID: https://orcid.org/0000-0001-8149-7394)
- Xing Li (ORCID: https://orcid.org/0000-0002-4524-600X)
- Yimei Zhu (ORCID: https://orcid.org/0000-0002-1638-7217)
- Ying Guo (ORCID: https://orcid.org/0000-0002-8188-4818)
- Wentao Huang (ORCID: https://orcid.org/0000-0003-2976-7953)
- W. Yan (ORCID: https://orcid.org/0009-0006-9312-6164)
Institutions
- Brookhaven National Laboratory (US)
- Zhengzhou University of Light Industry (CN)
- Henan Academy of Sciences (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Advanced Materials
- Published
- 2025-05-24
- DOI
- https://doi.org/10.1002/adma.202501300
- Citations
- 3
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 2.19
Funders
- U.S. Department of Energy
- National Natural Science Foundation of China
- Natural Science Foundation of Henan Province
- National Supercomputing Center, Korea Institute of Science and Technology Information