LEADER 00905nam0-2200289---450 001 990009652170403321 005 20171031120333.0 010 $a8814172919 035 $a000965217 035 $aFED01000965217 035 $a(Aleph)000965217FED01 035 $a000965217 100 $a20121130d2012----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $ay-------101yy 200 1 $a<>rito accusatorio a vent'anni dalla grande riforma$econtinuità, fratture, nuovi orizzonti$eatti del convegno$eLecce, 23-25 ottobre 2009 210 $aMilano$cGiuffrè$d2012 215 $a477 p.$d23 cm 225 1 $aAssociazione tra gli studiosi del processo penale$v17 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990009652170403321 952 $a3-13(21)$b6307$fDSPCP 959 $aDSPCP 996 $aRito accusatorio a vent'anni dalla grande riforma$9840175 997 $aUNINA LEADER 03904nam 22006375 450 001 9910484237103321 005 20251113182940.0 010 $a3-030-68310-9 024 7 $a10.1007/978-3-030-68310-8 035 $a(CKB)4100000011807057 035 $a(MiAaPQ)EBC6531655 035 $a(Au-PeEL)EBL6531655 035 $a(OCoLC)1244623672 035 $a(PPN)254719589 035 $a(DE-He213)978-3-030-68310-8 035 $a(EXLCZ)994100000011807057 100 $a20210326d2021 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence for Materials Science /$fedited by Yuan Cheng, Tian Wang, Gang Zhang 205 $a1st ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (231 pages) 225 1 $aSpringer Series in Materials Science,$x2196-2812 ;$v312 311 08$a3-030-68309-5 327 $aChapter 1. Brief Introduction of the Machine Learning Method -- Chapter 2. Machine learning for high-entropy alloys -- Chapter 3. Two-way TrumpetNets and TubeNets for Identification of Material Parameters -- Chapter 4. Machine learning interatomic force fields for carbon allotropic materials -- Chapter 5. Genetic Algorithms -- Chapter 6. Accelerated Discovery of Thermoelectric Materials using Machine Learning -- Chapter 7. Thermal nanostructure design based on materials informatics. - Chapter 8. Machine Learning Accelerated Insights of Perovskite Materials. 330 $aMachine learning methods have lowered the cost of exploring new structures of unknown compounds, and can be used to predict reasonable expectations and subsequently validated by experimental results. As new insights and several elaborative tools have been developed for materials science and engineering in recent years, it is an appropriate time to present a book covering recent progress in this field. Searchable and interactive databases can promote research on emerging materials. Recently, databases containing a large number of high-quality materials properties for new advanced materials discovery have been developed. These approaches are set to make a significant impact on human life and, with numerous commercial developments emerging, will become a major academic topic in the coming years. This authoritative and comprehensive book will be of interest to both existing researchers in this field as well as others in the materials science community who wish to takeadvantage of these powerful techniques. The book offers a global spread of authors, from USA, Canada, UK, Japan, France, Russia, China and Singapore, who are all world recognized experts in their separate areas. With content relevant to both academic and commercial points of view, and offering an accessible overview of recent progress and potential future directions, the book will interest graduate students, postgraduate researchers, and consultants and industrial engineers. 410 0$aSpringer Series in Materials Science,$x2196-2812 ;$v312 606 $aMaterials science 606 $aMachine learning 606 $aMaterials 606 $aMaterials Science 606 $aMachine Learning 606 $aMaterials Engineering 606 $aMachine Learning 615 0$aMaterials science. 615 0$aMachine learning. 615 0$aMaterials. 615 14$aMaterials Science. 615 24$aMachine Learning. 615 24$aMaterials Engineering. 615 24$aMachine Learning. 676 $a620.110285 702 $aCheng$b Yuan 702 $aWang$b Tian 702 $aZhang$b Gang 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484237103321 996 $aArtificial intelligence for materials science$91905207 997 $aUNINA