An Introduction to Materials Informatics Advanced Machine Learning | 256.31 MB
Title: An Introduction to Materials Informatics Advanced Machine Learning
Author: Tongyi Zhang
Category: Nonfiction, Science & Nature, Technology, Material Science, Mathematics, Statistics, Computers, Advanced Computing, Artificial Intelligence
Language: English | 914 Pages | ISBN: 3031174852
Description:
This book introduces how the rapid advancement of artificial intelligence（AI）is transforming the field of materials informatics, viz., AI+ materials. Around the world, self-driving materials laboratories and robotic systems-the “hard foundation” of this field-are emerging with remarkable speed. At the same time, a diverse array of AI-driven algorithms and computational tools-the “soft foundation”-are accelerating materials discovery and design. In particular, the development of large materials models has been significantly propelled by large language models. We are now entering the AI era, where AI for science (AI4S), AI for engineering (AI4E), and AI for materials (AI4M) are extremely important aspects. In this context, it is essential to equip materials scientists, engineers, and students with a solid understanding of fundamental and advanced AI methods and algorithms and their applications in materials science and engineering.
This book introduces how the rapid advancement of artificial intelligence（AI）is transforming the field of materials informatics, viz., AI+ materials. Around the world, self-driving materials laboratories and robotic systems-the “hard foundation” of this field-are emerging with remarkable speed. At the same time, a diverse array of AI-driven algorithms and computational tools-the “soft foundation”-are accelerating materials discovery and design. In particular, the development of large materials models has been significantly propelled by large language models. We are now entering the AI era, where AI for science (AI4S), AI for engineering (AI4E), and AI for materials (AI4M) are extremely important aspects. In this context, it is essential to equip materials scientists, engineers, and students with a solid understanding of fundamental and advanced AI methods and algorithms and their applications in materials science and engineering.
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