• Produktbild: Computational and Data-Driven Chemistry Using Artificial Intelligence
  • Produktbild: Computational and Data-Driven Chemistry Using Artificial Intelligence

Computational and Data-Driven Chemistry Using Artificial Intelligence Fundamentals, Methods and Applications

177,99 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

25.10.2021

Abbildungen

Approx. 180 illustrations

Herausgeber

Takashiro Akitsu

Verlag

Elsevier Science & Technology

Seitenzahl

280

Maße (L/B/H)

22,9/15,2/1,5 cm

Gewicht

380 g

Sprache

Englisch

ISBN

978-0-12-822249-2

Beschreibung

Portrait

Takashiro Akitsu is a full Professor of Chemistry at Tokyo University of Science. He completed his under graduate school training (chemistry) at Osaka University, Japan and his graduate school training (physical & inorganic chemistry, especially coordination, crystal and bioinorganic chemistry) at Osaka University (Ph.D. 2000). Following positions at Keio University, Japan, and Stanford University, USA, he moved to his current affiliation in 2008. He has published almost 220 articles in peer-reviewed journals and has presented multiple posters at international exhibitions. Prof Akitsu has been a peer reviewer of many journals and acted as an organizing committee of several international conferences.

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

25.10.2021

Abbildungen

Approx. 180 illustrations

Herausgeber

Takashiro Akitsu

Verlag

Elsevier Science & Technology

Seitenzahl

280

Maße (L/B/H)

22,9/15,2/1,5 cm

Gewicht

380 g

Sprache

Englisch

ISBN

978-0-12-822249-2

EU-Ansprechpartner

Kolibri 360 GmbH
Ettore-Bugatti-Straße 6-14
51149 Köln
DE
produktsicherheit@kolibri360.de

Herstelleradresse

Elsevier Science & Technology
125 London Wall
EC2Y 5AS London
GB
tradeorders@elsevier.com

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  • Produktbild: Computational and Data-Driven Chemistry Using Artificial Intelligence
  • Produktbild: Computational and Data-Driven Chemistry Using Artificial Intelligence
  • 1. Introduction to Computational and Data-Driven Chemistry Using AI
    2. Goal-directed generation of new molecules by AI methods
    3. Compounds based on structural database of X-ray crystallography
    4. Approaches using AI in Medicinal Chemistry
    5. Application of Machine learning algorithms for use in material chemistry
    6. Predicting Conformers of Flexible Metal Complexes using Deep Neural Network
    7. Predicting Activity and Activation Factor of Catalytic Reactions Using Machine Learning
    8. Convolutional Neural Networks for the Design and Analysis of Non-Fullerene Acceptors