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LARMOR LECTURE From superconductors to giant planets: a computational window on materials

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Modern methods for computing the properties of realistic materials from first principles (starting from quantum mechanics) have resulted in robust, efficient, and easy to use computer codes.

With with the explosion of available computational resources, and increasingly, machine learning, it has become possible to search though the vast space of compositions and arrangements of atoms to “discover” new materials with extreme properties, or under extreme and experimentally difficult to access conditions.

Examples range from the computational prediction of superconductors with very high superconducting transition temperatures, which at least in some cases have been confirmed experimentally, to the prediction of the behaviour of matter in the centre of giant planets, or even white dwarf stars.

This talk is part of the Cambridge Philosophical Society series.

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