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Reliable Low-Current and Multilevel Memristive Electrochemical Neuromorphic Devices with Semi-Metal Sb Filament.

Chenyu ZhugeYukun ZhangJiandong JiangXiang LiYanfei ZhaoYujun FuQi WangDeyan He
Published in: Small (Weinheim an der Bergstrasse, Germany) (2024)
Memristors are used in artificial neural networks owing to their exceptional integration capabilities and scalability. However, traditional memristors are hampered by limited resistance states and randomness, which curtails their application. The migration of metal ions critically influences the number of conductance states and the linearity of weight updates. Semi-metal filaments can provide subquantum conductance changes to the memristors due to the smaller single-atom conductance, such as Sb (≈0.01 G 0 = 7.69 × 10 -7 S). Here, a memristor featuring an active electrode composed of semi-metal Sb is introduced for the first time. This memristor demonstrates precise conductance control, a large on/off ratio, consistent switching, and prolonged retention exceeding 10 5 s. Density functional theory (DFT) calculations and characterization methods reveal the formation of Sb filaments during a set process. The interaction between Sb and O within the dielectric layer facilitates the Sb filaments' ability to preserve their morphology in the absence of electric fields.
Keyphrases
  • density functional theory
  • molecular dynamics
  • neural network
  • gold nanoparticles
  • molecular dynamics simulations
  • gene expression
  • single cell
  • mass spectrometry
  • molecular docking
  • ionic liquid
  • molecularly imprinted