Fig. 4 | Nature Communications

Fig. 4

From: Physical descriptor for the Gibbs energy of inorganic crystalline solids and temperature-dependent materials chemistry

Fig. 4The alternative text for this image may have been generated using AI.

High-throughput reaction engineering. a A comparison of experimental reaction energetics (labels) to those predicted using the machine-learned descriptor for Gδ(T) (dashed curves). b Reaction product distribution between MoO2, Mo2N, N2, H2, H2O, and NH3 based on Gibbs energy minimization subject to molar conservation and fixed pressure of 1 atm. In both figures, pred applies the SISSO-learned descriptor to Gδ(T) of the solid phases and experimental data for all other components

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