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:

    Tipus de document: info:eu-repo/semantics/other
    DOI: 10.34810/data1234
    Publicacions relacionades: Article Submitted for Review
    Departament: Enginyeria Informàtica i Matemàtiques
    Autor: Çetin, Yarkın Aybars; Escorihuela, Laura; Martorell Masip, Benjamí; Serratosa, Francesc
    Data alta repositori: 2024-04-10
    Acció del programa de finançament: European Commission (EC): H2020-NMBP-14-2018-814426
    Any de publicació de la dataset: 2024
    Matèria: Chemistry; Other
    Identificador del investigador: 0000-0003-2456-5949; 0000-0002-6350-2396; 0000-0002-7759-8042; 0000-0001-6112-5913
    Idioma: en
    Publicat per (editora): Universitat Rovira i Virgili (URV)
    Drets d'accés: info:eu-repo/semantics/openAccess
    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)
  • Paraules clau:

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

  • Cerca a google

    Search to google scholar