Precursor-Directed Microstructure Engineering of CuS for Tunable Charge Transport and Memristive Performance
Source abstract
Abstract
The performance of memristive devices is fundamentally determined by the microstructure of the dielectric layer and the associated charge-transport mechanisms. Here, we report a precursor-directed microstructure engineering strategy to modulate copper sulfide (CuS) films through a room-temperature chemical bath deposition process. By simply switching the copper precursor from CuCl 2 to CuSO 4, the CuS morphology evolves from dense microspheres to a nanoparticle-assembled (NPA) porous architecture. This structural transformation induces a transition in the dominant transport mechanism from Schottky emission to Fowler−Nordheim (FN) tunneling. Systematic electrical analysis reveals a transition voltage of −0.52 V, corresponding to the onset of FN tunneling. The ratio between the transition voltage and the extracted barrier height (0.62 eV) falls within the theoretical range of 0.8−1.2, derived by equating direct tunneling and FN tunneling current densities under the Wentzel−Kramers−Brillouin (WKB) approximation. Fitting results yield a barrier width of ∼1.8 nm and trap energy depths of 0.15−0.18 eV, providing quantitative evidence for tunneling-dominated and trap-assisted transport in the NPA structure. Furthermore, modulation of the bottom electrode work function enables control over switching polarity and rectification direction. Neural network simulations based on experimentally measured synaptic characteristics achieve 93% accuracy on the Fashion-MNIST dataset within 30 training epochs. This work establishes a quantitative structure−mechanism−function correlation and provides a physically grounded framework for the rational design of customizable neuromorphic devices.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Copper-based nanomaterials and applications · Nanomaterials and Printing Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Physical Science and Technology
Southwest Jiaotong University
School of Integrated Circuit Science and Engineering
Sichuan Polytechnic University
School of Materials Science and Engineering, Southwest Jiaotong University
The Institute of Smart City and Intelligent Transportation
Frontier Institute of Science and Technology and Interdisciplinary Research Center of Frontier Science and Technology Xi’an Jiaotong University
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