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Structural Biology Planet

March 21, 2019

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Machine learning for data-driven discovery in solid Earth geoscience

Understanding the behavior of Earth through the diverse fields of the solid Earth geosciences is an increasingly important task. It is made challenging by the complex, interacting, and multiscale processes needed to understand Earth’s behavior and by the inaccessibility of nearly all of Earth’s subsurface to direct observation. Substantial increases in data availability and in the increasingly realistic character of computer simulations hold promise for accelerating progress, but developing a deeper understanding based on these capabilities is itself challenging. Machine learning will play a key role in this effort. We review the state of the field and make recommendations for how progress might be broadened and accelerated.

by Bergen, K. J., Johnson, P. A., de Hoop, M. V., Beroza, G. C. at March 21, 2019 05:45 PM

Comment on "Insulator-metal transition in dense fluid deuterium"

Celliers et al. (Reports, 17 August 2018, p. 677), in an attempt to reconcile differences in inferred metallization pressures, provide an alternative temperature analysis of the Knudson et al. experiments (Reports, 26 June 2015, p. 1455). We show that this reanalysis implies an anomalously low specific heat for the metallic fluid that is clearly inconsistent with first-principles calculations.

by Desjarlais, M. P., Knudson, M. D., Redmer, R. at March 21, 2019 05:45 PM