  Correlated analysis of (sub)grains and particles in alloys is important to
understand transformation processes and control material properties. A
multimodal data fusion workflow directly combining subgrain data from electron
backscatter diffraction (EBSD) and particle data from backscatter electron
(BSE) images in the scanning electron microscope is presented. The BSE images
provide detection of particles smaller than the applied step size of EBSD down
to 0.03 $\mu$m in diameter. The workflow is demonstrated on a cold-rolled and
recovered Al-Mn alloy, where constituent particles formed during casting and
dispersoids formed during subsequent heating affect recovery and
recrystallization upon annealing. The multimodal dataset enables statistical
analysis including subgrains surrounding constituent particles and dispersoids'
location with respect to subgrain boundaries. Among the subgrains of
recrystallization texture, Cube{001}$\left<100\right>$ subgrains experience an
increased Smith-Zener drag from dispersoids on their boundaries compared to
CubeND{001}$\left<310\right>$ and P{011}$\left<\bar{5}\bar{6}6\right>$
subgrains, with the latter experiencing the lowest drag. Subgrains at
constituent particles are observed to have a growth advantage due to a lower
dislocation density and higher boundary misorientation angle. The dispersoid
size per subgrain boundary length increases as a function of misorientation
angle. The workflow should be applicable to other alloy systems where there is
a need for analysis correlating grains and grain boundaries with secondary
phases smaller than the applied EBSD step size but resolvable by BSE imaging.
