  Analysis of thermal dust emission spectra for dust mineralogy and physical
grain properties depends on laboratory-measured or calculated comparison
spectra. Often, the agreement between these two kinds of spectra is not
satisfactory because of the strong influence of the grain morphology on the
spectra. We investigate the ability of the statistical light-scattering model
with a distribution of form factors (DFF model) to reproduce experimentally
measured infrared extinction spectra for particles that are small compared to
the wavelength. We take advantage of new experimental spectra measured for free
particles dispersed in air with accompanying information on the grain
morphology. For the calculations, we used DFFs that were derived for aggregates
of spherical grains, as well as for compact grain shapes corresponding to
Gaussian random spheres. Irregular particle shapes require a DFF similar to
that of a Gaussian random sphere with sigma=0.3, whereas roundish grain shapes
are best fitted with that of a fractal aggregate of a fractal dimension
2.4-1.8. In addition we used a fitting algorithm to obtain the best-fit DFFs
for the various laboratory samples. In this way we can independently derive
information on the shape of the grains from their infrared spectra. For
anisotropic materials, different DFFs are needed for the different
crystallographic axes. This is due to a theoretical problem, which is inherent
to all models that are simply averaging the contributions of the
crystallographic directions.
