Document type: info:eu-repo/semantics/other
DOI: 10.34810/data1237
Related publications: Prediction of electronic density of states in guanine-TiO2 adsorption model based on machine learning doi: 10.1016/j.csbr.2024.100008
Research group: ASCLEPIUS - Smart Technology for Smart Healthcare
Departament: Enginyeria Informàtica i Matemàtiques
Author: Çetin, Yarkin Aybars; Martorell Masip, Benjamí; Serratosa, Francesc
Repository ingest date: 2025-04-24
Dataset publication year: 2024
Subject matter: Chemistry; Other
Researcher identifier: 0000-0003-2456-5949; 0000-0002-7759-8042; 0000-0001-6112-5913
Related publication's DOI: 10.1016/j.csbr.2024.100008
Language: en
Published by (editorial): Universitat Rovira i Virgili (URV)
Access rights: info:eu-repo/semantics/openAccess
Data type: Experimental data; Textual data
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".
Repositori URV