Electrocatalysis and Catalyst Screening from Density Functional Theory Calculations - Fuel Cell Catalysis: A Surface Science Approach - page 86

Pt - Bi ir precursor has been annealed to 500 8C and a surface alloy has formed,
the activity is found to be superior to that of pure Pt (Fig. 3.21).
The experimental results are in complete agreement with the predictions of our
computational screening approach; the annealed BiPt sample shows enhanced HER
activity compared with pure Pt. As mentioned above, this result is rather counterintui-
tive, given that Bi itself is a notoriously poor electrocatalyst for the HER [Trasatti,
1972]. Hence, it appears that our computational, combinatorial screening procedure
is capable of identifying improved catalysts for electrochemical reactions that are
not immediately apparent from simple intuitive arguments.
The above results demonstrate that computational screening is promising technique
for use in electrocatalyst searches. The screening procedure can be viewed as a general,
systematic, DFT-based method of incorporating both activity and stability criteria into
the search for new metal alloy electrocatalysts. By suggesting plausible candidates
for further experimental study, the method can, ultimately, result in faster and less
expensive discovery of new catalysts for electrochemical processes.
3.7 CONCLUSION
The goal in this chapter has been to show that it is possible to perform simulations
relevant to electrochemistry-based ab initio surface calculations, without including
all known physical effects. Focusing on trends and differences rather than absolute
values, the approach in some cases yields not only qualitative results, but also (semi)-
quantitative predictions.
With this approach, one is able to link electrochemical measurements, e.g., cyclic
voltammograms, directly to atomic-level events taking place on the electrode surface.
It is thereby possible to gain new insight into the electrochemical reactions and reac-
tion “descriptors.” These descriptors, in turn, form the basis for computational search
and fast-screening algorithms for promising new electrocatalyst materials. The study
of PtBi surface alloys is an example where insight at the atomic level has lead to exper-
iments and to an improved catalyst at the macroscopic level. This type of knowledge-
based computational screening may, in the future, become an important supplement to
current experimental methods in catalyst development.
Development of our models and screening methods is ongoing, and, in order to
further develop and benchmark this method, we will rely on well-defined and well-
characterized experiments, varying one parameter at the time. Our hope is that our simu-
lations, in turn, will provide new insight and thereby give inspiration to new experiments.
ACKNOWLEDGMENTS
The Center for Atomic-Scale Materials Design is supported by the Lundbeck Foundation. The
Center for Nanoscale Materials/Argonne National Laboratory is supported by the US
Department of Energy, Office of Science, Office of Basic Energy Sciences, under
Contract DE-AC02-06CH11357.