Application of artificial intelligence in new materials discovery / edited by Inamuddin, Maha Khan, Jafar Mazumder.

Format:

Book

Contributor:

Inamuddin, editor.

Khan, Maha, editor.

Mazumder, Jafar, editor.

Series:

Materials research foundations

Materials Research Foundations ; Vol. 147

Materials Research Foundations Series ; v.147

Language:

English

Subjects (All):

Artificial intelligence--Engineering applications.

Artificial intelligence.

Physical Description:

1 online resource (147 pages)

Edition:

1st ed.

Place of Publication:

Millersville : Materials Research Forum LLC, 2023.

Summary:

The book is concerned with the use of Artificial Intelligence in the discovery, production and application of new engineering materials.

Contents:

Intro

front-matter

Table of Contents

Preface

1

Artificial Intelligence Nano-Robots

1. Introduction

2. Composites

2.1 Liquid crystal elastomers

2.2 Shape memory polymers

2.3 Hydrogels

2.4 CNT actuators

2.5 Conducting polymers

3. Components and materials

4. Movement in nanorobots

5. Mechanism and stimulation

6. Trust dimensions

6.1 Reliability and safety

6.2 Explainability and interpretability

6.3 Privacy and security

6.4 Performance and robustness

7. Actuators

7.1 Thermally responsive actuators

7.2 Photo-responsive actuators

7.3 Magnetically responsive actuators

7.4 Electrically responsive actuators

8. Applications

8.1 Cancer detection and its treatment

8.2 Nanorobots in the diagnosis and treatment of diabetes

8.3 Artificial oxygen carrier nanorobot

9. Future challenges

Conclusion and future scope

Conflict of interest

Acknowledgment

References

2

Data Mining in Material Science

2. Machine learning and materials science

3. ML algorithms in materials science

4. Steps in machine learning for materials science

4.1 Experience

4.2 Task

4.3 Classification

4.4 Regression

4.5 Clustering

4.6 Dimension reduction and conception

4.7 Efficient searching

4.8 Performance measure

4.9 Model particulars

4.10 Supervised model

Conclusion

3

Artificial Intelligence Applications in Solar Photovoltaic Renewable Energy Systems

1.1 Overview of Solar PV Renewable Energy System and Artificial Intelligence (AI) Technology

1.2 Solar energy generation

1.3 Classification of solar energy technologies (SET)

1.3.1 Concentrated solar-thermal power (CSP)

1.3.2 Solar photovoltaic energy

2. Artificial intelligence (AI)

2.1 Machine learning

2.2 Deep learning.

2.2.1 Convolutional neural networks (CNNs)

2.2.2 Long short-term memory (LSTM)

2.2.3 Generative adversarial network (GAN)

3. Application of AI in solar PV system

3.1 Monitoring of PV systems

3.2 PV fault detection and diagnosis (FDD) methods

3.3 Employment of AI technologies for sizing PV systems

3.4 Modelling of a solar PV generator

3.5 Solar water heating systems (SWHs)

4. Challenges of effective AI application in solar PV system

4.1 Solar energy optimization

4.2 PV-dependent hybrid facility optimization

4.3 External factors of solar energy generation

4.4 Challenges in the development of solar energy systems

4.5 Solar energy transformation

5. Prospects and future work consideration

4

Artificial Intelligence in Material Genomics

2. Material genomics

3. Strength of artificial intelligence

4. Artificial intelligence in material genomics

5

Applications of Artificial Intelligence in Polymer Manufacturing

1.1 Advantages and disadvantages of artificial intelligence in polymer manufacturing

2. Classification of artificial intelligence

2.1 Classification of AI based on capabilities

3. Key Developments and commercialization in the polymer industry

4. Application of artificial intelligence in polymer manufacturing

4.1 Artificial intelligence and polymer manufacturing

4.2 Biodegradable polymers and artificial intelligence

4.3 Artificial intelligence and packaging industries

4.4 Agriculture and artificial intelligence

4.5 Healthcare and artificial intelligence

4.6 Artificial intelligence and dentistry

4.7 Food industry and artificial intelligence

4.8 Cosmetic artificial intelligence

5. Future prospects and conventional challenges.

6. Guidelines, rules, and regulations for polymeric manufacturing

Conflict of Interest

Reference

6

Artificial Intelligence for Energy Conversion

2. Alternative sources of energy and artificial intelligence

3. Machine learning and its application in material sciences

4. Limitation of principled method and how ML can intervene

5. Applications of AI in the domain of energy conversions

5.1 AI in photonics

5.2 AI in electrochemical catalyst

5.3 AI in electrolysis

5.4 AI in fuel cell technology

Conclusions

Acknowledgments

back-matter

Keyword Index

About the Editors.

Notes:

Description based on publisher supplied metadata and other sources.

Other Format:

Print version: Inamuddin Application of Artificial Intelligence in New Materials Discovery

ISBN:

1-64490-253-2

OCLC:

1381709195