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


ABSTRACT: The Gibbs energy, G, determines the equilibrium conditions of chemical reactions and materials stability. Despite this fundamental and ubiquitous role, G has been tabulated for only a small fraction of known inorganic compounds, impeding a comprehensive perspective on the effects of temperature and composition on materials stability and synthesizability. Here, we use the SISSO (sure independence screening and sparsifying operator) approach to identify a simple and accurate descriptor to predict G for stoichiometric inorganic compounds with ~50?meV atom-1 (~1?kcal?mol-1) resolution, and with minimal computational cost, for temperatures ranging from 300-1800?K. We then apply this descriptor to ~30,000 known materials curated from the Inorganic Crystal Structure Database (ICSD). Using the resulting predicted thermochemical data, we generate thousands of temperature-dependent phase diagrams to provide insights into the effects of temperature and composition on materials synthesizability and stability and to establish the temperature-dependent scale of metastability for inorganic compounds.

SUBMITTER: Bartel CJ 

PROVIDER: S-EPMC6177451 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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

Bartel Christopher J CJ   Millican Samantha L SL   Deml Ann M AM   Rumptz John R JR   Tumas William W   Weimer Alan W AW   Lany Stephan S   Stevanović Vladan V   Musgrave Charles B CB   Holder Aaron M AM  

Nature communications 20181009 1


The Gibbs energy, G, determines the equilibrium conditions of chemical reactions and materials stability. Despite this fundamental and ubiquitous role, G has been tabulated for only a small fraction of known inorganic compounds, impeding a comprehensive perspective on the effects of temperature and composition on materials stability and synthesizability. Here, we use the SISSO (sure independence screening and sparsifying operator) approach to identify a simple and accurate descriptor to predict  ...[more]

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