A comprehensive review published in Chemical Reviews explores the evolution and applications of electron density-based methods in chemistry and materials science. These methods, rooted in the quantum mechanical concept of electron density as a physical observable, have profoundly influenced the understanding of chemical bonding and redox reactions, especially in areas like battery technology. While traditional methods like Density Functional Theory (DFT) are widely used, they are computationally intensive. Recent advancements combining electron density topology with machine learning promise more efficient large-scale simulations, enabling the study of phenomena such as light excitations and reaction mechanisms. The international collaboration bridges distinct subfields, providing a roadmap for future research to enhance computational materials science and deepen our understanding of matter.
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Virtual Lab Inc., the parent company of the Materials Square platform
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Email: gabriele@simulation.re.kr
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