  Information about size and shape of particles produced in various
manufacturing processes is very important for process and product development
because design of downstream processes as well as final product properties
strongly depend on these geometrical particle attributes. However, recovery of
particle size and shape information in situ during crystallisation processes
has been a major challenge. The focused beam reflectance measurement (FBRM)
provides the chord length distribution (CLD) of a population of particles in a
suspension flowing close to the sensor window. Recovery of size and shape
information from the CLD requires a model relating particle size and shape to
its CLD as well as solving the corresponding inverse problem.
  This paper presents a comprehensive algorithm which produces estimates of
particle size distribution and particle aspect ratio from measured CLD data.
While the algorithm searches for a global best solution to the inverse problem
without requiring further a priori information on the range of particle sizes
present in the population or aspect ratio of particles, suitable regularisation
techniques based on relevant additional information can be implemented as
required to obtain physically reasonable size distributions. We used the
algorithm to analyse CLD data for samples of needle-like crystalline particles
of various lengths using two previously published CLD models for ellipsoids and
for thin cylinders to estimate particle size distribution and shape. We found
that the thin cylinder model yielded significantly better agreement with
experimental data, while estimated particle size distributions and aspect
ratios were in good agreement with those obtained from imaging.
