AI-Guided Design and Property Prediction for Zeolites and Nanoporous Materials 1st Edition

by German Sastre (Editor), Frits Daeyaert (Editor)

AI-Guided Design and Property Prediction for Zeolites and Nanoporous Materials

A cohesive and insightful compilation of resources explaining the latest discoveries and methods in the field of nanoporous materials

In Artificial Intelligence for Zeolites and Nanoporous Materials: Design, Synthesis and Properties Prediction a team of distinguished researchers delivers a robust compilation of the latest knowledge and most recent developments in computational chemistry, synthetic chemistry, and artificial intelligence as it applies to zeolites, porous molecular materials, covalent organic frameworks and metal-organic frameworks. The book presents a common language that unifies these fields of research and advances the discovery of new nanoporous materials.

The editors have included resources that describe strategies to synthesize new nanoporous materials, construct databases of materials, structure directing agents, and synthesis conditions, and explain computational methods to generate new materials. They also offer material that discusses AI and machine learning algorithms, as well as other, similar approaches to the field.

Readers will also find a comprehensive approach to artificial intelligence applied to and written in the language of materials chemistry, guiding the reader through the fundamental questions on how far computer algorithms and numerical representations can drive our search of new nanoporous materials for specific applications.

Designed for academic researchers and industry professionals with an interest in synthetic nanoporous materials chemistry, Artificial Intelligence for Zeolites and Nanoporous Materials: Design, Synthesis and Properties Prediction will also earn a place in the libraries of professionals working in large energy, chemical, and biochemical companies with responsibilities related to the design of new nanoporous materials.

From the Back Cover

A cohesive and insightful compilation of resources explaining the latest discoveries and methods in the field of nanoporous materials

In Artificial Intelligence for Zeolites and Nanoporous Materials: Design, Synthesis and Properties Prediction a team of distinguished researchers delivers a robust compilation of the latest knowledge and most recent developments in computational chemistry, synthetic chemistry, and artificial intelligence as it applies to zeolites, porous molecular materials, covalent organic frameworks and metal-organic frameworks. The book presents a common language that unifies these fields of research and advances the discovery of new nanoporous materials.

The editors have included resources that describe strategies to synthesize new nanoporous materials, construct databases of materials, structure directing agents, and synthesis conditions, and explain computational methods to generate new materials. They also offer material that discusses AI and machine learning algorithms, as well as other, similar approaches to the field.

Readers will also find a comprehensive approach to artificial intelligence applied to and written in the language of materials chemistry, guiding the reader through the fundamental questions on how far computer algorithms and numerical representations can drive our search of new nanoporous materials for specific applications.

Designed for academic researchers and industry professionals with an interest in synthetic nanoporous materials chemistry, Artificial Intelligence for Zeolites and Nanoporous Materials: Design, Synthesis and Properties Prediction will also earn a place in the libraries of professionals working in large energy, chemical, and biochemical companies with responsibilities related to the design of new nanoporous materials.

About the Author

German Sastre, PhD, is a member of the Structure Commission of the International Zeolite Association. His research focus is on solid state computational chemistry as applied to nanoporous materials, including zeolites and metal-organic frameworks.

Frits Daeyaert, PhD, has a background in computational drug design in the pharmaceutical industry. As visiting scientist at Rice University he has developed and applied de novo design methods for the design of organic structure directing agents for zeolite synthesis. He is a co-recipient of the 2019 Donald W. Breck award in Molecular Sieve Science for his contribution to the discovery of enantiomerically enriched STW zeolite.

Product details

• Publisher ‏ : ‎ Wiley; 1st edition (January 30, 2023)

• Language ‏ : ‎ English

• Hardcover ‏ : ‎ 464 pages

• ISBN-10 ‏ : ‎ 111981975X

• ISBN-13 ‏ : ‎ 978-1119819752