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Powered by DFT: Screening methods that accelerate materials development for hydrogen in metals applications.

Kelly M Nicholson1, Nita Chandrasekhar, David S Sholl

  • 1School of Chemical & Biomolecular Engineering Georgia Institute of Technology 311 Ferst Drive Atlanta, Georgia 30332-0100, United States.

Accounts of Chemical Research
|June 18, 2014
PubMed
Summary

Scientists are screening metal hydrides for efficient hydrogen storage in fuel cell vehicles and developing advanced metal membranes for hydrogen purification. Computational methods accelerate the discovery of materials with optimal properties for these critical energy applications.

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Area of Science:

  • Materials Science
  • Computational Chemistry
  • Energy Storage

Background:

  • Hydrogen is crucial for chemical processes and projected as a key energy carrier for green energy systems.
  • Light metal hydrides are investigated for hydrogen storage, requiring specific thermodynamic properties and kinetics.
  • Hydrogen behavior in metals is vital for developing membranes used in hydrogen purification.

Purpose of the Study:

  • To conduct large-scale screening of metal-based systems for hydrogen storage in metal hydrides.
  • To identify promising materials for onboard fuel cell vehicles.
  • To discover metal membranes with high hydrogen permeability for purification from mixed gas streams.

Main Methods:

  • Density Functional Theory (DFT)-based methods to predict thermodynamic properties, reaction pathways, and phase diagrams.
  • Grand canonical linear programming for screening millions of metal, metal hydride, and alloy mixtures.
  • Combination of DFT, Monte Carlo techniques, and simplified models to predict hydrogen permeabilities in metal membranes.

Main Results:

  • Efficient screening of numerous metal-based systems identified promising hydrogen storage materials.
  • Accurate prediction of hydrogen permeabilities for metal membranes, enabling large-scale alloy library screening.
  • Identification of candidate alloys for hydrogen separation membranes, addressing limitations of pure Pd.

Conclusions:

  • Computational screening accelerates the discovery of advanced materials for hydrogen storage and purification.
  • DFT and related methods provide accurate predictions for material properties crucial for energy applications.
  • Further development in computational methods is needed to reduce costs and expand the scope of material discovery.