Materials Informatics - Methods, Tools, andApplications
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- Wiley
More About This Title Materials Informatics - Methods, Tools, andApplications
English
A one-stop source on recent advances in the application of data mining to materials science, this book provides an up-to-date overview of the latest software and tools.
Clearly structured and divided into two parts, the first focuses on current progress in data mining and machine learning for materials science, while the second part addresses developments in software, databases and high-throughput computational activities.
Successful case studies illustrate the power of materials informatics in guiding the experimental discovery of novel materials. A practical approach is maintained throughout, with hints on how to use already existing databases of materials' properties and an accompanying website with interactive applications.
A must-have for material scientists, chemists and engineers interested in these time-saving methods.
Clearly structured and divided into two parts, the first focuses on current progress in data mining and machine learning for materials science, while the second part addresses developments in software, databases and high-throughput computational activities.
Successful case studies illustrate the power of materials informatics in guiding the experimental discovery of novel materials. A practical approach is maintained throughout, with hints on how to use already existing databases of materials' properties and an accompanying website with interactive applications.
A must-have for material scientists, chemists and engineers interested in these time-saving methods.
English
Olexandr Isayev is a Research Scientist at UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill. In 2008, he received his Ph.D. in computational chemistry. He was a Postdoctoral Research Fellow at the Case Western Reserve University and scientist at the government research lab before joining UNC in 2013. He received the "Emerging Technology Award" from the American Chemical Society (ACS) and the GPU computing award from NVIDIA in 2014. His research interests focus on making sense of chemical data with molecular modeling and machine learning.
Alexander Tropsha, PhD, is K.H. Lee Distinguished Professor and Associate Dean for Research at the UNC Eshelman School of Pharmacy, UNC-Chapel Hill. Prof. Tropsha obtained his PhD in Chemical Enzymology in 1986 from Moscow State University, Russia. He came to UNC-Chapel Hill in 1989 as a postdoctoral fellow and became faculty in the School of Pharmacy in 1991. His research interests are in the areas of Computer-Assisted Drug Design, Cheminformatics, Structural Bioinformatics and Computational Toxicology. He has authored or co-authored more than 190 peer-reviewed research papers, reviews and book chapters and co-edited two monographs.
Stefano Curtarolo studied Electrical Engineering and Physics in Padova, Italy, and received his PhD in Materials Science from MIT in 2003. He then joined the faculty of Materials Science and Physics at Duke University. During his time at Duke, he received the ONR-Young-Investigator, the NSF-Career, and the Presidential PECASE Awards in addition to the International Union of Pure and Applied Physics - Young Scientist Prize in Computational Physics. He was promoted to Associate Professor in 2008, to Full Professor in 2012 and he started the Center for Materials Genomics in July 2012.
Alexander Tropsha, PhD, is K.H. Lee Distinguished Professor and Associate Dean for Research at the UNC Eshelman School of Pharmacy, UNC-Chapel Hill. Prof. Tropsha obtained his PhD in Chemical Enzymology in 1986 from Moscow State University, Russia. He came to UNC-Chapel Hill in 1989 as a postdoctoral fellow and became faculty in the School of Pharmacy in 1991. His research interests are in the areas of Computer-Assisted Drug Design, Cheminformatics, Structural Bioinformatics and Computational Toxicology. He has authored or co-authored more than 190 peer-reviewed research papers, reviews and book chapters and co-edited two monographs.
Stefano Curtarolo studied Electrical Engineering and Physics in Padova, Italy, and received his PhD in Materials Science from MIT in 2003. He then joined the faculty of Materials Science and Physics at Duke University. During his time at Duke, he received the ONR-Young-Investigator, the NSF-Career, and the Presidential PECASE Awards in addition to the International Union of Pure and Applied Physics - Young Scientist Prize in Computational Physics. He was promoted to Associate Professor in 2008, to Full Professor in 2012 and he started the Center for Materials Genomics in July 2012.
English
METHODOLOGICAL ASPECTS OF MATERIALS INFORMATICS
Big Data in Chemistry
Genetic Algorithms, Crystal Structure Prediction
Machine Learning in Materials Science
MQSPR Modeling in Materials Informatics
Machine Learning Predictions of Molecular Properties
Statistical Modeling for Material Databases
Machine Learning Models in Chemical Space
Big Data in Materials Informatics
Topological Analysis of Crystal Structures
SOFTWARE AND TOOLS FOR MATERIALS INFORMATICS
AFLOWLIB
Harvard Clean Energy
Python Software for MI
High-Throughput Computational Screening of Materials
Open Quantum Materials Database
Computational Materials Repository
ICSD Database
Open Crystallography Database
Big Data in Chemistry
Genetic Algorithms, Crystal Structure Prediction
Machine Learning in Materials Science
MQSPR Modeling in Materials Informatics
Machine Learning Predictions of Molecular Properties
Statistical Modeling for Material Databases
Machine Learning Models in Chemical Space
Big Data in Materials Informatics
Topological Analysis of Crystal Structures
SOFTWARE AND TOOLS FOR MATERIALS INFORMATICS
AFLOWLIB
Harvard Clean Energy
Python Software for MI
High-Throughput Computational Screening of Materials
Open Quantum Materials Database
Computational Materials Repository
ICSD Database
Open Crystallography Database
