£121.18

Springer - Anharmonic Vibration and Dielectric Properties Book

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Description

Explore the intersection of computational physics and advanced technology with this Springer thesis. This academic work focuses on a first-principles and machine learning study regarding the anharmonic vibration and dielectric properties of materials. It serves as a specialized resource for researchers and students working within the fields of computer science, artificial intelligence, and machine learning. By integrating machine learning approaches with first-principles methods, this text provides a deep look into material properties. It is a valuable addition to any professional or academic library centered on computing, internet technologies, and advanced material science studies. This book is part of the respected Springer Theses series, ensuring a high standard of academic research and technical depth for those studying the evolution of AI and machine learning in physical sciences.

Key Features

Focuses on the application of machine learning to study material properties and anharmonic vibration.

Provides a detailed first-principles approach to understanding dielectric properties in materials.

Part of the Springer Theses series, offering high-quality academic research and technical insights.

Ideal for students and professionals specializing in AI, machine learning, and computer science.

Supports advanced research in the field of computational material science and physics.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
31 May 2025
Listed Since
26 January 2025

Barcode

No barcode data available

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