  The development of new engineering alloy chemistries is a time consuming and
iterative process. A necessary step is characterization of the
nano/microstructure to provide a link between the processing and properties of
each alloy chemistry considered. One approach to accelerate the identification
of optimal chemistries is to use samples containing a gradient in composition,
ie. combinatorial samples, and to investigate many different chemistries at the
same time. However, for engineering alloys, the final properties depend not
only on chemistry but also on the path of microstructure development which
necessitates characterization of microstructure evolution for each chemistry.
In this contribution we demonstrate an approach that allows for the in-situ,
nanoscale characterization of the precipitate structures in alloys, as a
function of aging time, in combinatorial samples containing a composition
gradient. The approach uses small angle x-ray scattering (SAXS) at a
synchrotron beamline. The Cu-Co system is used for the proof-of-concept and the
combinatorial samples prepared contain a gradient in Co from 0% to 2%. These
samples are aged at temperatures between 450{\textdegree}C and
550{\textdegree}C and the precipitate structures (precipitate size, volume
fraction and number density) all along the composition gradient are
simultaneously monitored as a function of time. This large dataset is used to
test the applicability and robustness of a conventional class model for
precipitation that considers concurrent nucleation, growth and coarsening and
the ability of the model to describe such a large dataset.
