{
  "abstract": "The growing need has pushed the development of autonomous laboratory automation for high-throughput materials research. Although self-driving laboratories (SDL) and automated liquid handling have advanced significantly, robotic material handling remains poorly integrated with high-temperature thermal processes. In this study, a solution-based synthesis autonomous robotic process was designed, developed, calibrated, and validated. Two cooperative robotic arms, a bespoke pneumatic pipetting end-effector, an RS485-controlled syringe pump, a modular crucible assembly, and automated furnace control were all integrated into the developed platform via a centralised Python-based architecture that uses Modbus TCP and RTU communication. The system handles liquid dispensing, sample mixing, robotic transfer, furnace loading, thermal treatment, controlled cooling, and sample retrieval on an independent basis. Deionised (DI) water, ethanol, and zirconium (Zr) acetate solution were used to calibrate the dispensing system to assess performance across liquids with various physical characteristics. With dispensing accuracy of 98.4%, all liquids showed excellent linearity between scheduled and dispensed quantities. After fluid-specific calibration, an error propagation study showed strong mechanical repeatability and predictable systematic error buildup, validating the system's capability for dependable automated precursor production. The independent synthesis of gadolinium zirconate (Gd2Zr2O7), a highly sought-after thermal barrier coating (TBC) composition for the next generation of aero gas turbines, was used to test the entire operation. The robotic platform effectively completed precursor dispensing, solution homogenisation, furnace processing at 1600 °C, controlled cooling, and sample recovery.",
  "abstract_shown": true,
  "affiliations": [
    "Coatings and Surface Engineering, Faculty of Engineering",
    "University of Nottingham",
    "Cobot Maker Space"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Mohammadreza Lalegani Dezaki"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Pushpender Singh"
    },
    {
      "affs": [
        2,
        1
      ],
      "name": "Dominic Price"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Vikram Hastak"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Rajib Das"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Tanvir Hussain"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/a9rrhvev0scb8.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15010111/v1",
  "fulltext_url": null,
  "id": "a9rrhvev0scb8",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010111/v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2505|Machine Learning in Materials Science"
    ]
  ],
  "openalex": "W7220931753",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15010111/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-08",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/a9rrhvev0scb8.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:22Z",
      "native_id": "10.26434/chemrxiv.15010111",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010111/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "openalex:2505|Machine Learning in Materials Science",
      "subfield": "materials-polymers"
    }
  ],
  "title": "Autonomous Robotic Workflow for Solution-Based Synthesis and High-Temperature Thermal Processing toward Self-Driving Laboratories",
  "title_text": "Autonomous Robotic Workflow for Solution-Based Synthesis and High-Temperature Thermal Processing toward Self-Driving Laboratories",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:22Z",
  "url": "https://research.draconitic.com/paper/a9rrhvev0scb8",
  "venue": "ChemRxiv",
  "versions": []
}