Subject matter: Chemistry; Other
Access rights: info:eu-repo/semantics/openAccess
Researcher identifier: 0000-0003-2456-5949; 0000-0002-7759-8042; 0000-0001-6112-5913
Published by (editorial): Universitat Rovira i Virgili (URV)
Language: en
Related publications: Prediction of electronic density of states in guanine-TiO2 adsorption model based on machine learning doi: 10.1016/j.csbr.2024.100008
Abstract: This dataset houses a research poster and its poster abstract. The set of documents was first presented at the doctoral days organized by the Doctoral Committee of the Nanoscience, Materials and Chemical Engineering program at Escuela Técnica Superior de Ingeniería Química (ETSEQ) of Universitat Rovira i Virgili (URV) on 16 May 2024 (19th Edition). Poster Title: "Machine Learning Prediction for Electronic Density of States in Guanine-TiO2 Adsorption Model".
Data type: Experimental data; Textual data
Departament: Enginyeria Informàtica i Matemàtiques
DOI: 10.34810/data1237
Document type: info:eu-repo/semantics/other
Related publication's DOI: 10.1016/j.csbr.2024.100008
Repository ingest date: 2025-04-24
Author: Çetin, Yarkin Aybars; Martorell Masip, Benjamí; Serratosa, Francesc
Keywords: Molecular Dynamics; Poster; Computational Chemistry; Titania; Guanine; Machine Learning
Research group: ASCLEPIUS - Smart Technology for Smart Healthcare
Dataset publication year: 2024
Dataset title: Machine Learning Prediction for Electronic Density of States in Guanine-TiO2 Adsorption Model
Repositori URV