COVID-19 Update: We are currently shipping orders daily. However, due to transit disruptions in some geographies, deliveries may be delayed. To provide all customers with timely access to content, we are offering 50% off Science and Technology Print & eBook bundle options. Terms & conditions.
Computational and Data-Driven Chemistry Using Artificial Intelligence - 1st Edition - ISBN: 9780128222492

Computational and Data-Driven Chemistry Using Artificial Intelligence

1st Edition

Fundamentals, Methods and Applications

Editor: Takashiro Akitsu
Paperback ISBN: 9780128222492
Imprint: Elsevier
Published Date: 15th October 2021
Page Count: 310
Sales tax will be calculated at check-out Price includes VAT/GST

Institutional Subscription

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.


Computational and Data-Driven Chemistry Using Artificial Intelligence: Volume 1: Fundamentals, Methods and Applications highlights fundamental knowledge and current developments in the field, giving readers insight into how these tools can be harnessed to enhance their own work. Offering the ability to process large or complex data-sets, compare molecular characteristics and behaviors, and help researchers design or identify new structures, Artificial Intelligence (AI) holds huge potential to revolutionize the future of chemistry. Volume 1 explores the fundamental knowledge and current methods being used to apply AI across a whole host of chemistry applications.

Drawing on the knowledge of its expert team of global contributors, the book offers fascinating insight into this rapidly developing field and serves as a great resource for all those interested in exploring the opportunities afforded by the intersection of chemistry and AI in their own work. Part 1 provides foundational information on AI in chemistry, with an introduction to the field and guidance on database usage and statistical analysis to help support newcomers to the field. Part 2 then goes on to discuss approaches currently used to address problems in broad areas such as computational and theoretical chemistry; materials, synthetic and medicinal chemistry; crystallography, analytical chemistry, and spectroscopy. Finally, potential future trends in the field are discussed.

Key Features

  • Provides an accessible introduction to the current state and future possibilities for AI in chemistry
  • Explores how computational chemistry methods and approaches can both enhance and be enhanced by AI
  • Highlights the interdisciplinary and broad applicability of AI tools across a wide range of chemistry fields


Chemistry graduates, post-graduates and researchers across both academia and industry interested in developing and/or applying artificial intelligence approaches to enhance their own work. AI researchers and data scientists interested in chemistry as a source of new problems for them to address through their work

Table of Contents

  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


No. of pages:
© Elsevier 2021
15th October 2021
Paperback ISBN:

About the Editor

Takashiro Akitsu

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.

Affiliations and Expertise

Professor of Chemistry, Tokyo University of Science, Japan

Ratings and Reviews