LEADER 04101nam 22006855 450 001 9911018746403321 005 20250729130235.0 010 $a9783031899836$b(electronic bk.) 010 $z9783031899829 024 7 $a10.1007/978-3-031-89983-6 035 $a(MiAaPQ)EBC32250647 035 $a(Au-PeEL)EBL32250647 035 $a(CKB)40072506700041 035 $a(DE-He213)978-3-031-89983-6 035 $a(OCoLC)1530373798 035 $a(EXLCZ)9940072506700041 100 $a20250729d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence for Materials Informatics /$fedited by S. Sachin Kumar, Neelesh Ashok, N. Sukumar, Neethu Mohan, K. P. Soman, Sabu Thomas 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (310 pages) 225 1 $aStudies in Computational Intelligence,$x1860-9503 ;$v1213 311 08$aPrint version: Sachin Kumar, S. Artificial Intelligence for Materials Informatics Cham : Springer,c2025 9783031899829 327 $aTopological indices-based vector representation of graphs -- Toxicity Prediction Using Convolutional Neural Networks: A Study of Deep Learning Approach -- AI and ML in Polymer Science: Enhancing Material Informatics through Predictive Modelling -- Transforming Carbon-Based Material: The Role of AI and ML Regression Techniques in Material Science -- Physics Informed Neural Networks: Fundamentals & Application to Phase Field Models -- Application of AI to help leverage Density Functional Theory computations in Materials Informatics -- XAI Approaches in Genetic Biomaterial Analysis -- AI-Driven Robotic Solutions in Material Engineering -- Implications of high-entropy energy materials in healthcare, environment and agriculture, along with the applications of artificial intelligence -- Advancements in Agricultural Materials: Machine Learning Models for Precision Fertilizer Prediction. 330 $aThis comprehensive book explores the transformative impact of AI on materials informatics, delving into machine learning/deep learning, and material knowledge representation. Embracing the transformative power of artificial intelligence (AI), the field of materials informatics has witnessed a remarkable revolution in its methodology and applications. AI has revolutionized the field of materials informatics, enabling researchers to discover, design, and optimize materials with enhanced properties at an accelerated pace. It showcases how AI is accelerating materials discovery, property prediction, providing case studies, and a comprehensive bibliography for further exploration. This essential resource equips researchers, scientists, and engineers with the knowledge and tools to harness the power of AI for groundbreaking advancements in materials science. 410 0$aStudies in Computational Intelligence,$x1860-9503 ;$v1213 606 $aComputational intelligence 606 $aMaterials science 606 $aEngineering$xData processing 606 $aArtificial intelligence 606 $aComputational Intelligence 606 $aMaterials Science 606 $aData Engineering 606 $aArtificial Intelligence 615 0$aComputational intelligence. 615 0$aMaterials science. 615 0$aEngineering$xData processing. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aMaterials Science. 615 24$aData Engineering. 615 24$aArtificial Intelligence. 676 $a006.3 700 $aSachin Kumar$b S$01836637 701 $aAshok$b Neelesh$01836638 701 $aSukumar$b N$01806540 701 $aMohan$b Neethu$01836639 701 $aSoman$b K. P$01836640 701 $aThomas$b Sabu$0851308 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9911018746403321 996 $aArtificial Intelligence for Materials Informatics$94414835 997 $aUNINA