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Density Functional Theory (DFT) is a cornerstone in computational quantum chemistry and condensed matter physics, offering a powerful framework for understanding and predicting the properties of atoms, molecules, and solids. It provides a computationally efficient alternative by focusing on the electron density rather than the many-body wave functions, significantly reducing the computational cost while retaining accuracy. DFT has been successfully applied to a wide variety of materials and systems encountered in chemistry, physics, materials science and beyond. It also plays a crucial role in tackling many-body problems in quantum mechanics, offering a versatile and efficient approach to understanding the electronic structure and properties of complex systems. Many-body problems involve interactions between multiple particles, making traditional wave function-based methods computationally demanding, and often impractical for large systems. This book provides a comprehensive and accessible exploration of the principle, methodologies, and practical applications of ab-initio computational techniques in the fields of material science. Starting from the basics of quantum mechanics, the book introduces readers to the theoretical foundations necessary for understanding ab-initio methods. It then systematically covers various computational approaches, including density functional theory (DFT), Hartree-Fock theory, and post-Hartree-Fock methods, offering insights into their underlying principles, and advantages. Additionally, the reader is introduced to the many important roles of DFT in revealing the electronic structure of materials, including band structures, energy gaps, Fermi surfaces, and NMR studies as well as in determining the effect of hydrostatic pressure on the optoelectronic and thermoelectric properties of materials.Moreover, it highlights DFT's ability to accurately predict structural optimizations, phase transitions, and magnetic properties, offering invaluable insights into the behaviour of materials under diverse conditions. The editors believe that this book will serve as an indispensable resource for researchers, students, and practitioners who wish to leverage the predictive power of DFT in advancing scientific understanding and technological advances. |
