{
  "abstract": "Algal bioplastics are emerging as a promising class of sustainable materials, but their development is limited by an incomplete understanding of how processing governs structure. Establishing principles connecting processing to structure is hindered by manual analysis and the complexity of structural data. Here thermomechanical processing conditions (time, temperature, and pressing force) are mapped to structural descriptors of Limnospira platensis (spirulina) bioplastics. Quantifiable features are derived from Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) to summarize the chemical and physical structure. Informative FTIR regions are selected by principal component regression (PCR), and interpretable Gaussian bands are automatically deconvolved from the spectra. SEM micrographs are encoded using a self-supervised vision transformer (DINOv3), projected into two dimensions, and clustered. Overall, 201 features are combined into a structural fingerprint and fed to a gradient boosted model that is inverted to recover processing conditions. The inverted model reveals that temperature strongly influences the structural features, while pressing time acts as a secondary logarithmic modulator. Conversely, pressing force is recoverable only as a regime, behaving as a consolidation threshold near 5 kN. Together, these results demonstrate that complex structural signatures can be transformed into interpretable processing–structure relationships, enabling rational design of algal bioplastics.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 13,
  "authors": [
    {
      "name": "Kuotian Liao"
    },
    {
      "name": "Yiyang Sun"
    },
    {
      "name": "Ian R. Campbell"
    },
    {
      "name": "Hareesh Iyer"
    },
    {
      "name": "Richard Sheridan"
    },
    {
      "name": "Arthur Gim"
    },
    {
      "name": "Etta Shack"
    },
    {
      "name": "Sebastian Sosa"
    },
    {
      "name": "Thea Zabala"
    },
    {
      "name": "Linda S. Schadler"
    },
    {
      "name": "L.C. Brinson"
    },
    {
      "name": "Cynthia Rudin"
    },
    {
      "name": "Eleftheria Roumeli",
      "orcid": "0000-0002-2828-1428"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7fd0fdvb8k0mj.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15008361/v1",
  "fulltext_url": null,
  "id": "7fd0fdvb8k0mj",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008361/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": "W7211900277",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-06",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/7fd0fdvb8k0mj.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:17Z",
      "native_id": "10.26434/chemrxiv.15008361",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008361/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "openalex:2505|Machine Learning in Materials Science",
      "subfield": "materials-polymers"
    }
  ],
  "title": "Interpretable Processing–Structure Relationships in Spirulina Bioplastics through Automated Spectral and Microstructural Analysis",
  "title_text": "Interpretable Processing–Structure Relationships in Spirulina Bioplastics through Automated Spectral and Microstructural Analysis",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:17Z",
  "url": "https://research.draconitic.com/paper/7fd0fdvb8k0mj",
  "venue": "ChemRxiv",
  "versions": []
}