Conjunts de dades de producció científicaEnginyeria Informàtica i Matemàtiques

New descriptors in toxicology prediction of nanomaterials: Using quasi-ab initio MD simulations for the estimation of aqueous ZnO and TiO2 surface structure parameters

  • Dades identificatives

    Identificador:  PC:4302
    Autors:  Çetin, Yarkın Aybars; Escorihuela, Laura; Martorell Masip, Benjamí; Serratosa, Francesc
    Resum:
    This dataset houses a research poster, its poster abstract, and its award certificate. The set of documents was first presented at The Virtual 10th International Conference on Nanotoxicology (NanoTox2021) poster presentation, 20th - 22nd April 2021. Poster Title: "New descriptors in toxicology prediction of nanomaterials: Using quasi-ab initio MD simulations for the estimation of aqueous ZnO and TiO2 surface structure parameters.” Our research focuses on understanding the toxicity of nanomaterials, highlighting the need for in-silico methods due to their diverse structures and compositions. We investigate the interactions and surface parameters of ZnO and TiO2 nanoparticles with water using Molecular Dynamics simulations at Density Functional – Tight Binding level methods. By incorporating new structural parameters, we aim to contribute toxicology prediction models and improve safety assessments of nanomaterials. The poster selected and awarded with attendees’ bursary, which is given to 49 attendees over 384 registered attendees, and one of the "Best Student Poster - Highly Commended" prize among 117 poster presentations. (2024-04-09)
  • Altres:

    Matèria: Chemistry; Other
    Drets d'accés: info:eu-repo/semantics/openAccess
    Identificador del investigador: 0000-0003-2456-5949; 0000-0002-6350-2396; 0000-0002-7759-8042; 0000-0001-6112-5913
    Publicat per (editora): Universitat Rovira i Virgili (URV)
    Idioma: en
    Publicacions relacionades: Article Submitted for Review
    Resum: This dataset houses a research poster, its poster abstract, and its award certificate. The set of documents was first presented at The Virtual 10th International Conference on Nanotoxicology (NanoTox2021) poster presentation, 20th - 22nd April 2021. Poster Title: "New descriptors in toxicology prediction of nanomaterials: Using quasi-ab initio MD simulations for the estimation of aqueous ZnO and TiO2 surface structure parameters.” Our research focuses on understanding the toxicity of nanomaterials, highlighting the need for in-silico methods due to their diverse structures and compositions. We investigate the interactions and surface parameters of ZnO and TiO2 nanoparticles with water using Molecular Dynamics simulations at Density Functional – Tight Binding level methods. By incorporating new structural parameters, we aim to contribute toxicology prediction models and improve safety assessments of nanomaterials. The poster selected and awarded with attendees’ bursary, which is given to 49 attendees over 384 registered attendees, and one of the "Best Student Poster - Highly Commended" prize among 117 poster presentations. (2024-04-09)
    Departament: Enginyeria Informàtica i Matemàtiques
    DOI: 10.34810/data1234
    Tipus de document: info:eu-repo/semantics/other
    Data alta repositori: 2024-04-10
    Autor: Çetin, Yarkın Aybars; Escorihuela, Laura; Martorell Masip, Benjamí; Serratosa, Francesc
    Paraules clau: Molecular Dynamics, Zinc Oxide, Titania, Poster
    Any de publicació de la dataset: 2024
    Acció del programa de finançament: European Commission (EC): H2020-NMBP-14-2018-814426
    Títol del conjunt de dades: New descriptors in toxicology prediction of nanomaterials: Using quasi-ab initio MD simulations for the estimation of aqueous ZnO and TiO2 surface structure parameters
  • Paraules clau:

    Chemistry; Other
    Molecular Dynamics, Zinc Oxide, Titania, Poster
  • Documents:

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