Researchers at the Department of Energy’s National Energy Technology Laboratory (NETL) and Carnegie Mellon University have developed a new computational modeling tool that could ultimately make the research and development to discover new systems for hydrogen production quicker and less expensive.

The research, supported by the DOE’s Office of Fossil Energy and reported in the current issue of Science, predicts hydrogen flux through metal alloy separation membranes that could be used to produce pure hydrogen.

Such membranes allow pure hydrogen to pass through, while blocking impurities that are present with other gases in the production of hydrogen from fossil energy resources. Impurities lessen the effective use of hydrogen, and separation is a critical component of hydrogen production.

Metal membranes play a vital role in hydrogen purification. Defect-free membranes can exhibit effectively infinite selectivity but must also provide high fluxes, resistance to poisoning, long operational lifetimes, and low cost. Alloying offers one route to improve on membranes based on pure metals such as palladium. We show how ab initio calculations and coarse-grained modeling can accurately predict hydrogen fluxes through binary alloy membranes as functions of alloy composition, temperature, and pressure.

Kamakoti et. al., Science, Vol 307, Issue 5709, 569-573 , 28 January 2005

This research demonstrates our vision of coupling computational and experimental methods to facilitate rapid research and development of advanced technologies. In essence, we are developing the computational tools to prescreen hydrogen separation membranes.

Anthony Cugini, focus area leader of Computational and Basic Sciences at NETL

The use of computational modeling to determine the ability of candidate membranes to produce pure hydrogen would be a time- and money-saving step for hydrogen researchers. Instead of having to produce a large suite of alloys with various proportions of metals—such as palladium and copper—and then test them to determine optimum compositions for maximum hydrogen purification, they could predict in advance which compositions would have the desirable properties.