{
  "abstract": "Defect engineering of memristive materials offers a powerful strategy for regulating ionic transport and analog resistive switching required for neuromorphic computing. Here, we report a wet chemical synthesis route for chloride-vacancy (VCl) engineering in lead-free all-inorganic KCuCl3-x thin films and establish a direct correlation between defect concentration, electronic structure, transport dynamics, and neuromorphic performance. Controlled precursor-ratio variation systematically tunes the VCl concentration in KCuCl3-x thin films, driving preferential vacancy formation at the terminal chloride sites, band-gap narrowing, and enhanced electronic disorder. W/KCuCl3-x/FTO memristors exhibit stable bipolar VCM-type resistive switching, with increasing VCl concentration promoting forming-free operation. An optimal VCl concentration (~ 1.3*10^21 cm^-3) provides a balance between ionic mobility and defect controllability, resulting in highly linear potentiation/depression characteristics and superior pulse endurance (>104 cycles). When the experimentally measured conductance characteristics of the optimized memristor are implemented as synaptic weights in artificial neural network simulations, recognition accuracies of 98.96% and 91.82% are achieved on the MNIST and Fashion-MNIST datasets, respectively. These findings establish precursor ratio-controlled VCl engineering as an effective strategy for simultaneously optimizing ionic transport, analog switching, and neuromorphic learning in lead-free halide perovskite memristors, providing a general materials design principle for energy-efficient neuromorphic electronics.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.35436",
  "author_total": 3,
  "authors": [
    {
      "name": "Chinmayee Mandar Mhaskar"
    },
    {
      "name": "Sangeeta Roy Chaudhuri"
    },
    {
      "name": "Ayan Roy Chaudhuri"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5nrr8prhwrc49.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.35436",
  "fulltext_url": null,
  "id": "5nrr8prhwrc49",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.35436",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cond-mat.dis-nn"
    ],
    [
      "arxiv",
      "cond-mat.mtrl-sci"
    ],
    [
      "openalex",
      "2208|Advanced Memory and Neural Computing"
    ]
  ],
  "openalex": "W7223781127",
  "pdf_url": "https://arxiv.org/pdf/2610.35436",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-26",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/5nrr8prhwrc49.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:35:35Z",
      "native_id": "2610.35436",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.35436"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:cond-mat.dis-nn",
      "subfield": "condensed-matter"
    }
  ],
  "title": "Precursor Ratio-Controlled Chloride Vacancies in Lead-Free KCuCl3-x Memristors for Forming-Free Gradual Resistive Switching and Neuromorphic Learning",
  "title_text": "Precursor Ratio-Controlled Chloride Vacancies in Lead-Free KCuCl3-x Memristors for Forming-Free Gradual Resistive Switching and Neuromorphic Learning",
  "type": "preprint",
  "updated_at": "2026-10-30T12:35:35Z",
  "url": "https://research.draconitic.com/paper/5nrr8prhwrc49",
  "venue": "arXiv",
  "versions": []
}