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@ARTICLE{Xie:1047253,
      author       = {Xie, Zhiqiang and Wu, Jianchang and Tian, Jingjing and Li,
                      Chaohui and Zhang, Difei and Chen, Lijun and Loi, Maria
                      Antonietta and Osvet, Andres and Brabec, Christoph},
      title        = {{A}dditive-{E}ngineered {C}s{P}b{B}r 3 -{B}ased
                      {P}erovskite {M}emristors for {N}euromorphic {C}omputing and
                      {A}ssociative {L}earning {A}pplications},
      journal      = {ACS applied materials $\&$ interfaces},
      volume       = {17},
      number       = {38},
      issn         = {1944-8244},
      address      = {Washington, DC},
      publisher    = {Soc.},
      reportid     = {FZJ-2025-04184},
      pages        = {53704 - 53715},
      year         = {2025},
      abstract     = {Perovskite memristors have emerged as promising candidates
                      for neuromorphic computing due to their simple fabrication
                      process and mixed ionic and electronic properties. Among
                      them, all-inorganic CsPbBr3 perovskites have garnered
                      significant interest due to their excellent stability.
                      However, the low solubility of cesium bromide (CsBr) in most
                      common solvents poses a major challenge in fabricating
                      high-quality, pinhole-free CsPbBr3 films for memory device
                      applications using a convenient one-step solution method. In
                      this work, a facile one-step spin-coating approach was
                      employed to fabricate CsPbBr3-based memristors,
                      incorporating a carbohydrazide (CBH) additive into the
                      perovskite precursor to enhance device performance. The
                      modified device exhibited an improved ON/OFF ratio, enhanced
                      endurance, and longer retention time. Furthermore, it
                      successfully emulated key synaptic functions, including
                      excitatory postsynaptic current, paired-pulse facilitation,
                      long-term potentiation/depression, and
                      learning–forgetting–relearning behaviors, effectively
                      mimicking biological synapses. Additionally, an associative
                      learning experiment inspired by Pavlov’s dog experiment
                      was conducted, demonstrating memory formation and extinction
                      under optical and electrical stimuli. The fabricated
                      perovskite memristor was further evaluated in a
                      convolutional neural network for Fashion MNIST
                      classification, achieving a high recognition accuracy of
                      $89.07\%,$ confirming its potential for neuromorphic
                      computing applications. This study highlights the
                      effectiveness of additive engineering as a strategy for
                      developing high-performance perovskite-based neuromorphic
                      electronics.},
      cin          = {IET-2},
      ddc          = {600},
      cid          = {I:(DE-Juel1)IET-2-20140314},
      pnm          = {1214 - Modules, stability, performance and specific
                      applications (POF4-121)},
      pid          = {G:(DE-HGF)POF4-1214},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.1021/acsami.5c10525},
      url          = {https://juser.fz-juelich.de/record/1047253},
}