LEADER 00886nam0-22002651i-450- 001 990002225410403321 005 20110707160236.0 035 $a000222541 035 $aFED01000222541 035 $a(Aleph)000222541FED01 035 $a000222541 100 $a20030910d1913----km-y0itay50------ba 101 0 $aita 102 $aIT 200 1 $aCompendio di lezioni di chimica inorganica farmaceutica e tossicologica$eper uso degli studenti di farmacia, dei farmacisti e dei medici$fD. Vitali 210 $aTorino$cUnione tipografico-editrice torinese$d1913 215 $aXXI, 750 p.$d24 cm 700 1$aVitali,$bDioscoride$0273277 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990002225410403321 952 $a80 XXVII 728$b8012$fFFABC 959 $aFFABC 996 $aCompendio di lezioni di chimica inorganica farmaceutica e tossicologica$9396806 997 $aUNINA LEADER 04238nam 22006855 450 001 9910987695603321 005 20250314115303.0 010 $a3-031-78728-5 024 7 $a10.1007/978-3-031-78728-7 035 $a(CKB)37916641400041 035 $a(DE-He213)978-3-031-78728-7 035 $a(MiAaPQ)EBC31960083 035 $a(Au-PeEL)EBL31960083 035 $a(OCoLC)1509167186 035 $a(EXLCZ)9937916641400041 100 $a20250314d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMaterials Informatics II $eSoftware Tools and Databases /$fedited by Kunal Roy, Arkaprava Banerjee 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (XVI, 297 p. 102 illus., 95 illus. in color.) 225 1 $aChallenges and Advances in Computational Chemistry and Physics,$x2542-4483 ;$v40 311 08$a3-031-78727-7 327 $aPart 1. Introduction -- Introduction to Machine Learning for Predictive Modeling I -- Introduction to Machine Learning for Materials Property Modeling -- Part 2. Cheminformatic and Machine Learning Models for Nanomaterials -- Machine learning models to study electronic properties of metal nanoclusters -- Applications of Machine Learning Predictive Modeling for Carbon Quantum Dots -- Assessing the toxicity of quantum dots in healthy and tumoral cells with ProtoNANO, a platform of nano-QSAR models to predict the toxicity of inorganic nanomaterials -- Applications of predictive modeling for fullerenes -- Computational Analysis of Perovskite Materials AlXY3 (X = Cu, Mn; Y = Br, Cl, F) invoking the DFT Method -- Applications of predictive modeling for dye-sensitized solar cells (DSSCs) -- Introduction to multiscale modeling for One Health approaches -- DIAGONAL Decision Support System (DSS) for Advanced Nanomaterial Risk Management powered by Enalos Cloud Platform -- Part 3. Software Tools and Databases for Applications in Materials Science -- Machine Learning algorithms, tools, and databases for applications in Materials Science -- Machine Learning-Driven Web Tools for Predicting Properties of Materials and Molecules. 330 $aThis contributed volume explores the application of machine learning in predictive modeling within the fields of materials science, nanotechnology, and cheminformatics. It covers a range of topics, including electronic properties of metal nanoclusters, carbon quantum dots, toxicity assessments of nanomaterials, and predictive modeling for fullerenes and perovskite materials. Additionally, the book discusses multiscale modeling and advanced decision support systems for nanomaterial risk management, while also highlighting various machine learning tools, databases, and web platforms designed to predict the properties of materials and molecules. It is a comprehensive guide and a great tool for researchers working at the intersection of machine learning and material sciences. 410 0$aChallenges and Advances in Computational Chemistry and Physics,$x2542-4483 ;$v40 606 $aCheminformatics 606 $aMaterials 606 $aChemistry 606 $aComputer simulation 606 $aMachine learning 606 $aArtificial intelligence 606 $aCheminformatics 606 $aComputational Design Of Materials 606 $aMachine Learning 606 $aArtificial Intelligence 615 0$aCheminformatics. 615 0$aMaterials. 615 0$aChemistry. 615 0$aComputer simulation. 615 0$aMachine learning. 615 0$aArtificial intelligence. 615 14$aCheminformatics. 615 24$aComputational Design Of Materials. 615 24$aMachine Learning. 615 24$aArtificial Intelligence. 676 $a542.85 702 $aRoy$b Kunal$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBanerjee$b Arkaprava$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910987695603321 996 $aMaterials Informatics II$94339800 997 $aUNINA