About this Research Topic
This Research Topic deals with computational materials science as a key in the discovery of new functional molecules and materials by exploring the huge uncharted territory of the chemical and structural space of materials. As such, it will help to overcome current global challenges like the quest for efficient and sustainable use of energy resources.
In that spirit, this collection of review articles will:
(i) educate scientists in the relevant techniques: electronic-structure theory, spectroscopy, ab initio thermodynamics and statistical mechanics, multi-scale modeling, and machine learning approaches to potential parametrization, big-data dimensionality reduction (e.g. machine learning and compressed sensing), and property prediction;
(ii) extend the existing canon of electronic-structure theory text books and reviews through a practically oriented introduction of distinct timely topics that are relevant in modern materials and molecular simulations.
The orientation toward real-world examples and the tutorial style of this review collection ensures that theoretical knowledge will become practical skills. Thematically, this Research Topic is at the forefront of a paradigm change in materials science from trial-and-error experiments to informed data-driven design.
List of Contributions
• Editorial by Carsten Baldauf, Volker Blum, Matthias Scheffler
• Introduction and overview of electronic-structure theory by Matthias Scheffler and John Perdew
• The practical basics of electronic structure theory by Volker Blum
• The basics of electronic structure theory for periodic systems by Peter Kratzer and Jörg Neugebauer
• Perspectives of the theory of defects by Jürgen Spitaler and Stefan Estreicher
• Van der Waals interactions by Troy Van Voorhis and Alexandre Tkatchenko
• Wave-function theory for materials by Igor Ying Zhang and Andreas Grüneis
• Excited states and spectroscopy by Patrick Rinke and Silke Biermann
• Time-dependent DFT and Bethe-Salpeter equation by Claudia Draxl and Lucia Reining
• Searching conformational/configurational space by Carsten Baldauf and David Wales
• Ab initio molecular dynamics and statistical mechanics by Mariana Rossi and Luca Ghiringhelli
• Thermodynamics and cluster expansion by Sergey Levchenko and Chris Sutton
• Kinetic Monte-Carlo Simulations by Mie Andersen and Karsten Reuter
• Nuclear Dynamics in Solid Materials: How Phonons and Electron-Phonon Coupling Affect Macroscopic Material Properties by Christian Carbogno and Ramamurthy Ramprasad
• (Big) data analytics by Luca Ghiringhelli and Matthias Scheffler
Keywords: Solid-State Physics. Quantum Chemistry, Computer Simulations, Machine Learning, Big Data
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.