{
  "abstract": "Ammonia is a vital commodity of key importance for global agriculture, but its traditional synthesis via the energy-intensive Haber-Bosch process features a high ecological footprint, contributing to ≈2% of the overall carbon dioxide emission. An eco-friendly and sustainable alternative is offered by electrochemical NO ₃ ⁻ reduction (e-NO ₃ RR), enabling also to simultaneously reduce the concentration of nitrate, a widespread water pollutant. Herein, we report on the ultra-dispersion of CuFe ₂ O ₄ , NiFe ₂ O ₄ , or Fe ₂ O ₃ nanoparticles (NPs) on graphitic carbon nitride (gCN), yielding heterostructured oxide@gCN systems as potential e-NO ₃ RR catalysts. The target materials, fabricated by gCN electrophoretic deposition on carbon cloth (CC), followed by radio frequency (RF)-sputtering of oxide NPs in very low amounts, were subjected to a multi-technique characterization aimed at investigating their morphological, structural, compositional, and optoelectronic properties. The results indicate that gCN provides a robust, electronically coupled scaffold anchoring ultra-dispersed oxides, and evidence a gCN → oxide electron donation. Electrochemical tests coupled with ion chromatographic analyses highlight CuFe ₂ O ₄ @gCN as the best-performing catalyst, affording a Faradaic efficiency towards NH ₄ ⁺ of 21% at -1.15 V vs. the reversible hydrogen electrode (RHE), together with a comparatively higher ammonium production rate and reduced NO ₂ ⁻ generation. Altogether, our results may pave the way to the potential implementation of functional catalysts for ammonia generation from nitrate‑containing aqueous media.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "name": "Gian Andrea Rizzi"
    },
    {
      "name": "Davide Barreca"
    },
    {
      "name": "Nikša Krstulović"
    },
    {
      "name": "Oleg I. Lebedev"
    },
    {
      "name": "Lidia Soldà"
    },
    {
      "name": "Andrea Tapparo"
    },
    {
      "name": "Chiara Maccato"
    },
    {
      "name": "Alberto Gasparotto"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/aqwsgazr7pw5j.bib",
  "cited_by": 0,
  "doi": "10.1038/s41598-026-73907-8",
  "fulltext_url": null,
  "id": "aqwsgazr7pw5j",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://www.nature.com/articles/s41598-026-73907-8",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0",
  "metadata_licence": null,
  "native_subjects": [
    [
      "hal",
      "0.chim"
    ],
    [
      "openalex",
      "1503|Ammonia Synthesis and Nitrogen Reduction"
    ]
  ],
  "openalex": "W7218353527",
  "pdf_url": "https://www.nature.com/articles/s41598-026-73907-8_reference.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-03",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/aqwsgazr7pw5j.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:22Z",
      "native_id": "10.1038/s41598-026-73907-8",
      "source": "crossref",
      "url": "https://www.nature.com/articles/s41598-026-73907-8"
    },
    {
      "first_seen": "2026-10-30T12:18:02Z",
      "native_id": "hal-05841835",
      "source": "hal",
      "url": "https://hal.science/hal-05841835v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "openalex:1503|Ammonia Synthesis and Nitrogen Reduction",
      "subfield": "catalysis"
    }
  ],
  "title": "Ultra-dispersed metal oxide nanoparticles on graphitic carbon nitride as functional platforms for electrochemical nitrate valorization",
  "title_text": "Ultra-dispersed metal oxide nanoparticles on graphitic carbon nitride as functional platforms for electrochemical nitrate valorization",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:02Z",
  "url": "https://research.draconitic.com/paper/aqwsgazr7pw5j",
  "venue": "Scientific Reports",
  "versions": []
}