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Volume 589 Issue 7840, 7 January 2021

Atomic insights

The rich phase behavior exhibited by amorphous silicon under high pressures has been studied extensively with a view to obtaining a deeper understanding of structurally disordered materials in general. Yet a detailed mechanistic understanding of these behaviours has remained elusive. In this week’s issue, Volker Deringer and his colleagues show how atomistic machine-learning models, used to simulate pressurized amorphous silicon, can shed light on these behaviours, capturing the full range of structural transitions encountered experimentally. Such computational approaches should open up fresh prospects for predictive materials modelling that encompasses challenging experimental conditions.

Cover image: Volker Deringer.

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