General solution to the inverse near-forward-scattering particle-sizing problem in multiple-scattering environments:...

Area of Science:

• Optical Physics
• Particle Characterization
• Scattering Theory

Background:

• Accurate measurement of particle size distribution is crucial in various scientific and industrial applications.
• Optically thick media pose challenges for traditional light scattering techniques due to multiple scattering effects.
• Existing methods often require assumptions about the particle size distribution function, limiting their generality.

Purpose of the Study:

• To develop a general solution for measuring large particle size distribution in optically thick media using small-angle light scattering.
• To overcome the limitations of methods requiring prior knowledge of the particle size distribution function.
• To accurately model and account for multiple scattering phenomena.

Main Methods:

• Utilizing a successive order, discrete ordinates approach to model multiple scattering.
• Interrogating the particle field with an array of near-forward input light angles.
• Determining the scattering redistribution matrix for numerical inversion.
• Employing conventional inverse scattering methods to reconstruct particle size distribution from single-scattering signatures.

Main Results:

• A general solution for particle size distribution measurement in optically thick media was established.
• The method successfully retrieves the single-scattering signature by inverting the scattering redistribution matrix.
• Particle size distribution can be reconstructed from near-forward light scattering patterns without assuming distribution form.

Conclusions:

• The presented approach offers a robust and general method for characterizing large particles in challenging optically thick environments.
• This technique advances the field of particle size analysis by removing the need for pre-defined distribution models.
• The developed method has potential applications in fields requiring precise particle characterization, such as materials science and atmospheric studies.