Название: Artificial Intelligence in Science and Engineering: From Porous Materials to Drug Discovery, Volumes 1–2
Автор: Muhammad Sahimi
Издательство: Wiley-VCH
Год: 2027
Страниц: 811
Язык: английский
Формат: pdf
Размер: 23.7 MB

Apply AI and ML to solve complex problems across sciences.

Many problems in physics, engineering, and applied sciences resist traditional modeling approaches. Artificial Intelligence in Science and Engineering: From Porous Materials to Drug Discovery presents AI and ML methods for tackling otherwise unsolvable problems in complex systems. Written by Muhammad Sahimi, who brings over 40 years of research experience to the topic, this reference spans multiple scientific domains.

The book covers AI and ML applications in hydrodynamics, porous media characterization, molecular dynamics simulation, and biological phenomena including protein folding. It addresses environmental applications and drug discovery, connecting computational methods with domain-specific challenges in fluid dynamics, materials science, and biology. Readers gain access to methods that model, predict, and optimize processes difficult to approach through conventional techniques.

As the name suggests, Artificial Intelligence (AI) refers to the ability of computers and robots for emulating human thoughts and capabilities, but also going beyond them to carry out tasks in real-world environments. In particular, AI-enabled programs analyze datasets to provide information and insights into them, and in many cases they automatically trigger actions without human interference. With its rapid development, AI is already used with many technologies that we use in our daily lives, ranging from smart devices, to such voice assistants as Siri on Apple devices that are used by millions of people. Two important techniques, namely, natural language processing—the ability of computers to use human language—and computer vision—the ability to interpret images—are being utilized to automate tasks, accelerate decision making, and enable customer conversations with chatbots. As AI becomes a more mature technology, finding ever larger number of applications, the buzzwords and acronyms surrounding it also expand and spread. In addition to natural language processing (NLP) and computer vision, some of such buzzwords include Deep Learning, neural networks, data analytics, Data Science and Big Data, Generative AI, and Machine Learning (ML).

Readers will also find:

Detailed treatment of AI and ML approaches applied to complex systems in fluid dynamics and porous media research
Coverage of molecular dynamics applications where machine learning accelerates simulation and prediction of material properties
Methods for protein folding prediction and drug discovery leveraging current artificial intelligence and computational biology techniques
Environmental science applications demonstrating how AI-driven modeling addresses problems resistant to traditional analytical methods
Cross-disciplinary frameworks connecting physics, engineering, materials science, and biology through unified computational approaches

Physicists, materials scientists, engineers, computer scientists, and computational biologists will find this volume a substantive reference for applying AI and ML across their research domains. By unifying coverage of diverse complex systems under one framework, the book serves both academics and practitioners working at the intersection of computation and applied science.

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